DEV Community: Harish Rajora

Major Challenges of Performance Testing and Solutions

Harish Rajora — Thu, 14 Aug 2025 10:11:03 +0000

Performance testing comes with its own set of challenges, ranging from test infrastructure issues and high test execution times to inconsistent test environments. Identifying and addressing these performance testing challenges is important to build more efficient, reliable and scalable software applications.

Top Challenges of Performance Testing

Performance testing challenges vary by team, but QA needs to be ready for these common ones:

1. Unrealistic Test Scenarios or Inadequate Test Data

Unrealistic test scenarios often lead to inaccurate results because they fail to replicate real-world conditions such as varying network environments, user traffic patterns, and peak system loads. This makes it difficult to assess software performance accurately.

Similarly, inadequate test data can compromise performance testing results. Without large or diverse datasets including edge cases (null values or maximum input sizes), the tests may not reflect real user behavior, leading to insufficient test coverage and undetected issues.

Solution: Start with proper requirement analysis and involve stakeholders to define real-world scenarios like peak traffic and user behavior. Create test cases that mimic actual conditions.

Use enough test data to cover typical and edge cases, including large inputs and unexpected values. If real data isn’t available, generate synthetic data that’s close to production. It helps ensure your tests reflect real performance, not just best-case results.

2. High Setup Time and Maintenance Overhead

Setting up performance test environments often demands significant time and effort. Managing dependencies, configuring infrastructure, and maintaining consistent environments become ongoing headaches.

This overhead drains engineering resources and delays test execution, preventing teams from running frequent and reliable tests. Traditional setups simply don’t scale well with Agile development needs.

Solution: In such cases, an AI-native cloud test orchestration platform like HyperExecute is a good option. It supports container-based and scriptless setups, auto-installs dependencies, and can even run in your private cloud or virtual private cloud. So you spend less time configuring and more time actually testing.

3. Limited Scalability of Test Infrastructure

Effective performance testing requires infrastructure that can simulate high stress and load conditions. However, setting up and maintaining such test infrastructure can be costly and often demands regular scaling and upgrades.

This creates a challenge for teams, either early in the development process or later as the software scales. Similar to inconsistent test environments, the limited scalability of test infrastructure can also be a challenge when your software application scales.

Solution: Opting for a third-party tool like WebLOAD is a smarter choice, as such tools have a highly scalable infrastructure in place. They provide a platform to the team where the testers can mimic real-world high-stress scenarios and perform various types of performance testing seamlessly.

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4. Bottlenecks in Load Generation

Simulating large-scale traffic, such as 10,000+ concurrent users or geographically distributed load, is complex and resource-intensive. Many organizations face infrastructure bottlenecks and high costs when trying to generate realistic loads at scale.

Manual provisioning and limited test environments slow down testing cycles and limit the ability to accurately stress-test applications under real-world conditions.

Solution: You can leverage platforms such as HyperExecute, which provides a scalable, cloud-based infrastructure that can simulate thousands of users from multiple regions, on demand.

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5. Version Drift Between Environments

Sometimes, the staging environment used for testing doesn’t exactly match the production environment where the software actually runs. These differences can include parameters like configuration settings or hardware, and network setups. When this happens, it’s called environmental drift.

Because of this drift, performance issues might show up only in production, not during testing on staging environments. This makes test results less reliable and makes it harder for teams to understand what’s causing the issue or how to fix it.

Solution: Teams can leverage the HyperExecute platform to run every test in a clean, isolated environment that mirrors production as closely as possible. That means fewer environment-related issues and accurate results.

6. Insufficient Collaboration Between Teams

Having involvement from so many teams helps analyze the performance from different angles and inspect it at various points. In such a highly collaborative environment, communication is the key to efficient execution, and a lot of times, there is a gap in this domain.

Insufficient collaboration not only delays the testing process through many unresolved feedback loops but also transmits wrong expectations and metrics to the testing team.

As a result, the team may start testing using the wrong benchmarks, only to later find out they need to start again. Insufficient collaboration in performance testing is also a major reason for inadequate test data, a challenge discussed in the first section.

Solution: It is important to encourage regular communication and collaboration between dev, QA, Ops, and business teams from the start. Use shared collaboration tools and clear documentation to align on requirements and expectations.

Also, platforms like HyperExecute promote shared access, role-based dashboards, and collaborative debugging to keep everyone in the loop.

7. Lack of Continuous Performance Testing in CI/CD Pipelines

Performance tests are often scheduled late in the release cycle, typically during pre-production or staging. By that point, discovering performance bottlenecks means scrambling to fix issues under tight deadlines.

This delay causes longer release cycles and increased costs, as bugs identified late require significant effort to troubleshoot and resolve. Teams lose valuable time that could have been saved with earlier insights.

Solution: To address this challenge, consider using an end-to-end test orchestration platform like HyperExecute that lets you run performance tests early, right from your CI/CD pipeline.

So, whether you’re using GitLab, Azure DevOps, or something else, you can trigger load tests with every PR or nightly build. That means quicker feedback and avoiding the last-minute chaos before release.

8. Poor Monitoring and Logging During Tests

A challenge that is not just confined to performance testing but spans across all the phases of SDLC is the lack of efficient monitoring and logging systems. Monitoring and logging are two different aspects of the testing phase.

This seems easy to achieve, as all one has to do is implement monitoring and logging software. However, it becomes a challenge because of the additional elements that tag along with this software.

For instance, more logging per user means more data will be stored for each user in the database. It means the database infrastructure has to be of that capability, or there will be higher bills for cloud databases.

Either way, it accounts for large costs. Similarly, more monitoring means more dedicated resources and so on.

Solution: This challenge can only be overcome by putting additional money into this part of performance testing, especially when the application is scaling rapidly.

9. Time and Budget Constraints

Performance testing is not an isolated testing phase. It invites teams to collaborate, share, and include multiple phases in itself. Phases like simulating high-traffic and load conditions demand time, with the infrastructure constituting expensive hardware that needs constant upgradation.

For teams looking to develop and run an on-premise infrastructure, time and budget will always be constraints. Using hardware with low configuration and unrealistic test scenarios will only degrade the testing quality, application performance, and user experience.

Solution: The solution for the teams that do not have enough time to spare and run low on budget is to opt for cloud-based platforms like WebLOAD and spend a fraction of the costs on executing performance tests.

10. Improper Workload Modeling

An improper workload modeling means the team is considering their test scenarios simulation to be similar to the real world, but in reality, these test scenarios are imprecise, giving a false impression. Multiple reasons can contribute to improper workload modeling in performance testing.

The primary reasons include inadequate test data, which does not represent real-world metrics, unrealistic expectations, either due to wrong interpretations or a communication gap, and not considering all the data parameters, but only a portion of them.

This is a major challenge with performance testing because it can lead to a lot of financial losses, delivery delays, and most of all, testers may not even know that their modeling is wrong due to incorrect expectations, which are assumed to be correct.

Solution: To overcome this challenge, it’s crucial to understand the project, have correct expectations, and have high-quality data on your end. Workload modeling has to be an iterative process that should be improved or modified based on the website usage patterns and a better understanding of the data.

11. Overlooking System and Test Script Errors

Performance testing is executed using multiple parameters and, unlike functional testing, not all of them rely on strict assertions. It consists of simulating conditions, mimicking user behavior under high load, and throwing millions of requests at a single point to identify bottlenecks.

Therefore, the testing team cannot expect the system trace and test script errors to be as explicit as they are in regression or functional testing. This can result in an unknown challenge where the team might consider only explicit errors and ignore implicit ones that require additional debugging.

Solution: Teams can overcome this challenge by analyzing the performance testing operations, looking beyond trace errors towards varying metrics, and keeping an eye on scripting errors, which may not be pointed out by the system but only through analysis.

12. Neglecting to Test Under Peak Load Conditions

Peak load refers to the maximum ability of the infrastructure to withstand stress without breaking. High load, on the contrary, means a generic high load witnessed each day. Testing peak load is not as easy as it may sound. Peak load represents the maximum power the system can hold. It means testing has to be done on an infrastructure equal to the one hosted for production.

It is an extremely challenging acquisition that most organizations resist. It requires high costs and many resources, demanding a lot of dedicated time for test execution. Moreover, if peak load analysis exceeds the actual handling capacity, it can impact resources, including servers and databases.

Solution: To test for peak load conditions without investing much time and cost, use cloud-based third-party platforms. Using cloud-based platforms, you can simulate heavy user traffic on your staging or pre-production environments. It helps evaluate the performance of your software application before pushing it live.

13. Executing Tests in Production Environments

Sometimes, due to budget or resource limitations, teams conduct performance testing directly in the production environment to avoid the expense of setting up a separate testing environment. This environment is often used to test peak load or high-traffic scenarios.

There are two ways to do this: either share production resources during periods of low spikes or temporarily suspend production users to fully use the infrastructure for testing. The first approach doesn’t allow for accurate peak load testing, while the second can negatively affect user experience and pose a risk of revenue loss.

Solution: This situation is more of a compulsion than a challenge for the organization. If the team is unwilling to use third-party providers for any reason, there is no other solution other than risking their business reputation.

14. Selection of Inappropriate Performance Testing Tools

Finally, the choices a team makes during each performance testing phase determine their testing quality. During each step, the team has to analyze their requirements carefully and look for the best tool that suits these requirements.

These choices range from picking an IDE to choosing a CI/CD tool for managing the pipeline. Choosing the wrong tool can make it hard for testers to work efficiently and limit their testing options.

Solution: This challenge can be overcome by spending time in the performance testing planning stage and selecting a tool after careful analysis, brainstorming, and discussing with the team members.

Choosing the right tools helps save a lot of money in the future. For instance, JMeter is an open-source tool that has been in the market for a long time. However, it lacks a cloud infrastructure that supports performance testing.

Selecting an AI-native test orchestration platform like HyperExecute can eliminate this overhead and directly run JMeter tests on its infrastructure (with parallelism and integrated AI).

Conclusion

Inadequate application performance can turn out to be a huge loss for the team in terms of time, costs, resources, reputation, and much more. While a software application might not show any unusual behavior normally, nobody can predict how it will behave when there are sudden loads without any warning, for which the team was never prepared.

Since high-stress conditions are not in our hands, performance testing shows the way to get prepared for the same and ensure that the bottlenecks and thresholds are clearly defined for the current infrastructure in place.

However, this testing phase poses unique challenges that are hard to tackle for the team. This post highlights those challenges and the solutions through which the team can avoid them or minimize the damage. Once these challenges are tackled, the application is ready to face all types of conditions, including sudden spikes and unexpected loads, smoothly.

19 Best Practices for Automation Testing with Node.js

Harish Rajora — Wed, 25 Jun 2025 02:38:50 +0000

Node.js has become one of the most popular frameworks for web development, powering millions of applications. As projects grow in complexity, automation testing with Node.js is essential to ensure seamless performance. This article explores the best practices for Node.js automation testing in 2025, helping you build reliable, high-quality applications.

While testing a weather forecast app in Node.js could be highly complex due to multiple data sources, APIs, and location tracking, this guide simplifies the process. Instead of diving into such a large-scale application, we’ll walk through a step-by-step approach to automation testing with Node.js, ensuring you understand the fundamentals and best practices for automation testing.

Initializing A Simple Test In Node JS

If you are new to node.js then here I will initialize a simple test in node.js for you to understand the procedure of testing in node.js. Let us create a basic function of multiplying two numbers:

function mul(x,y)
{
return x\*y;
}

This is a basic function for multiplication. But, this function is not valid for every case and can stand invalid for various other numbers. We cannot perform testing in such a situation. We will extend this function to validate the equality feature.

function mul(x,y)
{
return x\*y;
}
function testMul()
{
var x = 4;
var y = 5;
val mul = x\*y;
var mul2 = mul(4,5);
if(mul == mul2)
console.log(‘Equality Test Passed’);
else
console.log(‘Equality Test Failed’);
}
testMul();

After writing the basic tests, we will initialise the new node project by hooking it up to the npm.

npm init

Now you need to install the modules. As we discuss further in this article you will learn more about the importance of Mocha and Chai in the node js testing. Mocha gives you a good platform to define your test case suites, hooks and use assertion of whatever library you want to use. Chai on the other hand is used for writing the assertions only. These assertions are the human readable test codes which has advantages of its own.

npm install --save-dev mocha chai

After this, I have created two js files. One being test.js and other mull.js . Save the test.js in the test folder and mull.js in the root directory.

Now paste the function mul written above with an extra line.

function mul(x,y)
{
return x\*y;
}
module.exports = mul;

Exporting it will help us in adding it to the require line as we perform testing with node.js.

Open your test.js file in the tests folder and write the following test code given below to go-ahead testing with node.js. This test code will test the equality of the two functions. The expect variable is the object code from chai library to write the “expect” part of the assertion and multiply will be the variable that contains the exported module of the code given just above it (module.exports = mul).

var expect = require(‘chai’).expect;
var multiply = require(‘../mul’);
describe(‘mul()’, function(){
    it(‘should multiply two number’, function(){
var x = 4;
var y = 5;
val mul = x\*y;
var mul2 = mul(4,5);
expect(mul2).to.be.equal(mul)
});
});

Just run your tests now through npm test in the console window and you are good to go.

Best Practices For Testing Node JS

Testing tells the stability of your application and if not, makes it more stable which in turn save you from a sudden wrong commit which can take the whole software down with it.

Testing is required before you push your code to your users so that no one is bugged by any of the unwanted behaviour of the application. Being this important, we will see some of the best practices for testing Node JS in 2025.

1. Isolated and Atomic

Test should be atomic and isolated. Every test should run independently and without being dependant on each other. If neither test is dependent on any other test then if one test fails, other tests are not affected. Also, the tests should follow the atomicity property. It should not fail in between suddenly. A test should be entered and exited with the pass or fail result smoothly.

You should also keep in mind that the data you are testing upon should be separate for every test. More than one tests working on the same global data harms the overall motive of using the tests upon the application. Your time will absolutely increase leading to good performance but it is of no point. Keep your data specific to the tests.

2. Naming Of Your Test

This is one of the most basic and important feature for writing effective test cases. A test should be named meaningful and easily understood by other departments who are not related to testing such as development team. A name should not be any random name such as foo() being used popularly. After seeing that your test is no random word, you should focus on what you should name your test. A test name should constitutes of

What is being tested?
What are the different scenarios under which you are testing?
What should be the expected result of the test?

Here is an example of a meaningful naming convention for testing node.js.

function CheckCountryLanguage()
{
//code to check if the application is showing data in the country’s official language
}

The above test name makes sense because we can easily get what that function would be doing. What if I had written the function name as foo? Then I would have to read the complete code to understand the working of the function.

3. Using Assertions

An assertion in the programming language is a statement for which we declare at the time of coding. This declaration may or may not be true and hence provides the boolean output with true or false. The declaration itself contains the meaning of the test code such as expect(‘age’).to.be.equal(23).

This is self-explanatory and cuts the code lines’ logic to a great extent. If the variable ‘age’ is equal to 23 then True is printed or else False.

Assertions are more beneficial than normal tests because they already provide a statement in the test case. Also, when an assertion is run, you don’t need to know what was the response and why you got it. It would just provide you whether the test failed or passed.

A test will use logic in test cases while assertions are the human readable forms where you write tests in human readable forms. This helps when analyzing the tests after they are run.

expect(‘currentweather’).to.be(‘string’);

Such assertions are human readable and are self-explanatory about the test they are performing. This expect shows that the currentWeather has to be a string such as Hazy, Clear or Rainy etc.

4. Use Test Runner

A test runner is a library or a tool that takes a source code directory which contains the unit tests and runs tests on it. After executing the tests, it writes the results back on the console or the log files. It is always recommended to use a good test runner and some of the testers use their own test runners too.

While having a test runner can be advantageous with the databases as it can take the database values (dummy or real) and execute different tests on it. It can load fixtures too.

Mocha is a test runner. Mocha can provide you a programmatic way to run the tests via command line tools on ES6 codebase.

5. Focus On Test Coverage

A test coverage while writing the tests is the amount of source code you are covering in your test. In simple words it can also be said the amount of application as a whole you are covering for your test. While writing the tests, it is considered the most important thing to work upon. So how can you increase your test coverage?

First of all, you should always keep in mind that test coverage percentage is totally depended upon the nature of your application. If it is some application say Music Player then it need not have 100% test coverage because as we increase the test coverage it becomes more and more expensive for the company.

But if you have an important application like any real time application receiving data from satellite or an application for the manufacturer of Airplanes then you need to have 100% coverage because it will affect the application to a great extent.

We will focus on test coverage for the upcoming points. For this you can use Mocha along with Istanbul and run your Mocha tests over Istanbul.

6. Use Plugins For Test Coverage

Plugins are available which tests all the test coverage. Plugins will not help you in writing the tests that covers maximum code but it will definitely help you analyze your test and tell you if a test is skipped or not. It will also show if all the test cases are covered or not.

This way you might be thinking that you have written the tests that covers some percentage of the code but in reality some tests are skipped bringing down the overall percentage.

7. Analyse The Test Coverage Report

A test coverage report can be generated with the help of Istanbul and Mocha. Once you have generated the test coverage report, try to analyze the report. A report with say 90% test coverage that you might think will not be covering the complete 90% code with its test cases.

While using Istanbul it is quite easy and straightforward to analyse the test coverage report. Also, you should take the failed test seriously and analyse them as to why did they fail and check if there is an issue or not.

8. Use Mutation Testing

Mutation testing is the type of testing in which the test cases’ logical condition are tweaked (mutated) to deliberately fail the tests or if it failed then to pass it. The logics can also be changed for the same reasons. It is also popularly called as planting a bug. There are various libraries that you can get on the internet but one of them and most popular being Stryker can be used for the same purpose.

9. Check Plagiarism On Tests

While testing node.js on the source code, you should always check for plagiarism on the code. It is not so uncommon to copy and paste the code from the internet to make the software work. You might never know the source code can be licensed and your organisation can fall into serious trouble for the same.

These things violate the copyright issues also. So always remember to check the code for plagiarism in order to tweak the code a little but for the advantage of your organisation.

In order to use the plagiarism checker, you can install the node js npm plagiarism-checker package.

To install it just type the following code:

npm i plagiarism-checker

After that, in order to use that SDK, type the following code:

var a = require('plagiarism-checker');
var b = new a();
var config = b.getConfig();

Download the code from this repository and add it to your project. Keep in mind the following dependencies are installed

$ npm install lodash
$ npm install request
$ npm install request-promise
$ npm install mime-types

10. Use Realistic Inputs

Many times it so happens that the testers use the inputs that are not realistic or according to the real life scenarios. For example an input demanding phone numbers should be tested on numbers which resemble the real phone numbers. So you should always use realistic inputs while testing your application.

The best library available for this purpose is Faker library. According to GitHub, Faker library is a php library that generates fake data for the input you are willing to test upon.

You should also keep in mind to use more and more inputs for a single input parameter so as to test heavily. As in real life, many inputs will be processed on the same function, you should use as many as possible to test them.

A simple portrayal of the situation can be the same weather application that we discussed in the beginning of this chapter.

function CountryName(string country)
{
//code
}

Now, this function should be tested with realistic inputs such as

function CountryName(India)
{
//code
}
function CountryName(Netherlands)
{
//code
}

Instead of :

function CountryName(abc)
{
//code
}
function CountryName(foo)
{
//code
}

11. Use Linters

According to Wikipedia, linter is a tool that analyzes the source code to flag programming errors, bugs, stylistic errors and suspicious constructs. Linters are great at finding certain classes of bugs including assignment to undeclared variable and use of undefined variables. Using linters can help you a lot in determining the bugs in the structural way of the code. For Node JS, you can use ESLint for the same purpose.

12. Property Based Testing

Property based testing depends on different properties of the function. It is used to check the property of the entity (function, program etc) in particular. A property is a characteristic of the entity. For example, if you have a function that takes the input arguments as a,b and holds the property that b is always even then by property based checking, we check whether b is always even or not.

for all(a,b)

b is always an even number

Property based testing helps us as it

Contains the scope of all inputs and that can generate a huge number of test cases
Can take us to the failure in a very short time as it has something specific to put as the input like even numbers in the above case. It can keep on inserting even numbers until a point that it fails and we can get the threshold value of the function quite easily.

You can use FastCheck, QuickCheck or Mocha Test Check for property based testing.

13. Use Chai Library

Error catching should be done with specific libraries such as Chai library. It expects the assertions and hence give you what the error was about. This might not be the case with try-catch-finally statement. A Try-Catch-Finally statement will throw some generic error statement because it takes the exceptions as a whole class of exceptions and errors and does not give the specific result about the same. It then takes lot of time to decode what the error was actually about.

For example,

expect(‘a’).to.not.have.property(‘b’);

this way few lines of code is summarised to a single line of chai assertion.

14. Check For Exceptional Scenarios

While the test cases and scenarios that you design might cover everything on the source code but there are few exceptions that are very important while testing the application behaviour/response/outcome. Let say there is a feature in your application that sends email when a new user is added.

The email is sent to both admin and the user. This becomes an exceptional scenario as the method must be passing correctly but you might not be getting any email.

These things should be tested. The testing should also include forcefully sending different response code from the server side so that we can know how the application behaves in such a way and what values are returned.

If you go to the normal approach of checking the JS conditions and test cases internally then you will be able to check the internal conditioning but will never get if your application behaves in the same way practically or not.

Many firms develop their own methods to achieve these things. A good example is Netflix which has developed something they call Chaos Engineering which tests their functions and method by killing off their servers one by one.

This way they are also assured that even if one server fails, the application works correctly.

15. Follow The Testing Pyramid

While testing with node.js, you should try to follow the test automation pyramid. As seen from the following image the unit test should be taken as the base of all the testing.

We do so because unit test will cover the basic units of functionality independently of one another. After the unit tests are done then move ahead to the integration testing. Integration testing will let you test the different modules combined with one another as a group. After that we move on to the next part of the pyramid and test the front-end or User-Interface testing using Selenium or similar tools.

As you can see, the cost incurred keeps on increasing as we move on to the pyramid but the speed keeps on decreasing. Unit test takes most of the time to execute while the front end is tested fastest because of the less complexities and modules.

16. Use Component Testing

Component testing tests the functionality of the modules which are separately testable. The input/output behaviour of the test object is verified by the component testing.

As seen in the image, each component has a test plan and every test plan has various different tests under it and then they are tested to check the functionality of the component. It is recommended to use the component testing after the unit testing in the pyramid. Component testing is a very good approach and has a great coverage and speed greater than unit testing.

17. Keep Infrastructure Issues In Mind

More often, testers think that the testing of source code with the above practices kept in mind is the all they have to do for the proper functioning of the application. But, they are wrong. Testers tend to forget the infrastructure issues and testing them which have a great percentage of happening in the real life practical scenarios.

These infrastructure issues include memory overloading and how the application behaves when it happens. Other infrastructure issues may include the sudden shutdown of the server or API becoming 50% slower which is used in the application. Infrastructure testing include testing of these issues and providing a feedback report on it so that they can efficiently managed.

18. Going Parallel

Parallel testing means running multiple test cases, simultaneously. Running different tests in parallel has its own advantages. If you are not following parallelism then you will run one test and provide the feedback about it then you will run another tests and provide feedback about it and so on.

These feedbacks are then analysed and are worked upon. Then the team will check the feedback of the second test you did and then resolve them. While following parallelism, you can drastically reduce the feedback loop and provide feedback of many tests altogether which can be resolved in a lesser time as before. This way you can save a lot of time and resources of the company.

Many libraries are available for achieving parallel testing, most popular of them being Mocha and Jest.

19. Automate The Updation Of Your Dependencies

Running the tests and following different rules require lot of libraries and different tools to work altogether in order to achieve the perfect testing. But it sometimes happen that the dependencies become out of date and other dependency require the latest version to run with each other.

This creates disturbance in the smooth running of the tests and can be resolved by automating the updation of your dependencies. Once you automate the updation, every dependency will update by itself and will not require to manual intervention after raising the flag for the same.

Use An Online Selenium Grid For Cross Browser Testing

Talking about automation, everyone favors Selenium as an open-source for performing cross browser testing. However, there are a limitation on the number of browser and machines you get access to as you go ahead setting up your Selenium grid. Performing a thorough round of automated cross browser testing calls for a cloud-based provider such as LambdaTest.

LambdaTest is an AI-native test orchestration and execution platform that lets you run manual and automated tests at scale on over 5000 real devices , browsers, and OS combinations.

You can automate your testing process and can even perform testing with node.js in parallel. You can even perform test using any other test automation framework with respect to different languages such as Python, PHP, C#, Java and more.

Well, that was all from my end. Testing with node.js may look a little scary at first. However, you can get rid of hesitation and perform it like a professional by keeping the above best practices for testing Node JS in mind. Let me know if there is a special practice that I have missed, and you feel is indispensable for the article. Happy testing! 🙂

Conclusion

Testing is a crucial part of ensuring the stability and reliability of your Node.js application. By following these best practices, you can ensure that your tests are efficient, effective, and maintainable. Isolated and atomic tests, proper naming conventions, assertions, and the use of test runners like Mocha can help create a solid testing foundation.

Additionally, focusing on test coverage, using plugins, and practicing mutation testing will help you spot potential issues early on. The inclusion of realistic inputs, linters, and property-based testing further strengthens the quality of your tests. By continuously analyzing reports, checking for exceptional scenarios, and automating dependency updates, you can stay ahead of any issues.

Implementing parallel testing and component testing ensures efficiency and scalability, while keeping infrastructure issues in mind adds an extra layer of reliability. With these best practices, you’ll be able to take your Node.js testing to the next level in 2025.

Best Mobile App Testing Frameworks for Android and iOS

Harish Rajora — Mon, 23 Jun 2025 08:10:57 +0000

Mobile app testing framework helps automate the testing of your native apps. It reduces test execution time and identifies bugs before the app goes live. Once a mobile application is developed, it is moved ahead to the testing phase, where it is decided whether the application is fit to be delivered to the people or needs more work.

In this blog we will learn the best mobile app testing frameworks for 2025, the list of frameworks mentioned in this blog will help mobile app developers take better decision to build mobile apps in more effect way.

Different mobile app testing frameworks offer different features and may confuse the app tester in choosing the best one according to the situation. To resolve this, we have crafted this post that brings out all the mobile app testing frameworks, popular features, and other relevant information.

Types of Mobile App Testing Frameworks

Mobile app testing frameworks come in three strict divisions:

Strictly Android testing framework.
Strictly iOS testing Automation framework.
Cross platform testing framework (for both Android latest version and latest iOS version).

We have divided this post into three sections and arranged all the mobile app testing frameworks accordingly.

Android Test Automation Frameworks

The following section highlights the most popular mobile app testing frameworks available only for Android applications.

In this blog, we will discuss some of the best Android test automation frameworks, such as Espresso, Selendroid, and MonkeyRunner.

Espresso

“Use Espresso to write concise, beautiful and reliable Android UI tests” — Google.

Espresso is a Google-made Android testing framework and has been a popular choice due to its high performance. Espresso believes in creating very simple and straightforward tests without worrying about the application’s infrastructure. Furthermore, it is open-source, which gives the developers the power to customize the framework.

Key Features of Espresso

Google promotes Espresso as a quick-to-learn Android testing framework.
Espresso is comparatively faster in test execution.
Espresso is a highly stable Android test automation framework as it can detect when the main thread is idle and run the UI tests at an appropriate time to prevent load on the system.
If you are using Android Studio to develop Android applications, Espresso could be the best choice for you as it is easy and quick to integrate.
Espresso is based on JUnit, a very popular testing language. Therefore, app testers can quickly pick the APIs when opting for this framework.

Selendroid

“Test automation for native or hybrid Android apps and the mobile web with Selendroid.” — Selendroid

Selendroid is an Android test automation framework based on Selenium. Selendroid uses Selenium 2.0 for writing test scripts for Android apps. Currently, Selendroid is only an Android test automation framework, although they plan to extend it to iOS applications soon. Selendroid recommends using the iOS driver with the Webdriver for testing the iOS applications, which is just a workaround.

Key Features of Selendroid

Selendroid can be used with Android emulator online, real devices, and Selenium Grid for selenium android testing and selenium for iOS testing.
Selendroid uses Selenium which is hugely popular among app testers, and they can start right away with the Android test automation framework without investing time in learning.
Selendroid comes with advanced user interaction support APIs for faster testing. These may include human interaction such as swipe and drag and drop.
The Android testing framework comes with the support of the JSON Wire protocol.
Selendroid comes with an advanced inspector that can detect the UI elements quickly.

MonkeyRunner

“The MonkeyRunner tool is not related to the UI/Application Exerciser Monkey, also known as the monkey tool.” — Google.

The MonkeyRunner mobile app testing framework is an Android test automation framework designed to control the Android applications outside the Android code. Monekyrunner uses the Jython language, which implements the Python programming language using Java language. These popular languages make it extremely easy for the app testers to develop the tests. The tool is designed to test the Android based applications at the functional or framework level or for running the unit tests. Although, the developers of the framework define the tool to be used in any way the app testers or the developers want.

Key Features of MonkeyRunner

MonkeyRunner can be attached to more than one Android emulator or real device simultaneously. Through this single connection, you can run multiple test cases (or test suites) on all of them per your program/sequence, etc.
MonkeyRunner can provide you with a complete start-to-end test script for an Android application. The app tester can take multiple output screenshots whenever he feels through the test scripts.
The most popular feature of MonkeyRunner is its ability to compare multiple screenshots for correctness. The app tester can compare the present screenshot (the one taken from the current test run) and the screenshot, which is correct.
MonkeyRunner mobile app testing is a set of API toolkits, and hence it can be customized up to any level as the developer wants. Now test with free APK emulator online!!!

iOS Testing Frameworks

The following mobile app testing frameworks are available exclusively for iOS mobile applications.

XCTest

XCTest is considered the primary and most popular iOS automation testing framework when you have to test an iOS mobile application. The iOS testing framework uses instance methods and creates a friendly environment for the iOS app developers. XCTest uses Objective-C and Swift programming languages for testing and is compatible with XCode 5.0+.

Key features of XCTest

The XCTest is a powerful iOS testing framework and can be used for unit testing, mobile performance testing, and UI testing.
The languages used for writing the test cases are similar to development, and therefore the developers and app testers can start testing right away.
XCTest gives good control over continuous integration facilities.
XCTest also allows the user interface recording and enhancement.

OCMock

OCMock has a rich feature set for many different use cases. — OCMock

Another open-source mobile app testing framework designed for iOS applications is the OCMock. As the name suggests, OCMock focuses on the testing done through mock objects. OC here refers to the Objective-C language. OCMock provides three types of mocks — partial, dynamic, and stubs. The details of using each of them can be found on the official page of OCMock.

Key Features of OCMock

OCMock is an iOS test automation framework that provides deep and detailed documentation with many examples for the testers.
The framework uses Objective-C language, which is used in iOS development also. Therefore, it becomes very easy to learn and create suites in OCMock.
OCMock is open-source and, therefore, is free to use, is actively developed, and has established a very active community.
The latest version of OCMock (OCMock 3.0) has included modern syntax that uses macros. This benefits from separating method calls and mock setup and provides a better error reporting mechanism.

KIF

“The magic of KIF is that it allows you to drive your UI from your unit tests and reap all the advantages of testing in-process.” — KIF.

KIF is an iOS test automation framework used for testing iOS mobile applications. The framework builds the tests using the XCTest targets, and therefore it becomes easier for people already familiar with XCTest to create instant tests. Since KIF is used for UI testing, app testers and developers often add it to the user interface testing target. However, the official documentation advises developers and app testers not to do that as KIF works from the unit test target and should be added to it only.

Key Features of KIF

KIF uses Objective-C language just like OCMock, and the ease of learning is well appreciated.
KIF mobile app testing framework can be integrated directly in XCode, and there is no need to install any additional libraries, etc.
The framework uses tap events for testing, similar to a user’s action giving this framework an additional benefit over others.

Detox

“We believe the only way to tackle flakiness head-on is by moving from black-box testing to gray box testing. That’s where Detox comes into play.” — Detox.

Detox is an iOS test automation framework for end-to-end testing. They focus on eliminating flakiness, a major issue in mobile app testing frameworks.

Key Features of Detox

Detox writes test cases in Javascript, which is an extremely popular language among developers all around the globe.
Detox tests the mobile application after running it on the simulator/emulator, which resembles a real user-like testing behavior.
The framework brings advanced monitoring techniques into the environment.
Detox can run end-to-end tests integrating with CI tools such as Travis very smoothly.
Detox is open-source, and hence the community is very active.
The framework is test runner independent until you are using Javascript test runners.

Frameworks for iOS And Android

Appium

“Appium is built on the idea that testing native apps shouldn’t require including an SDK or recompiling your app.” — Appium

If you are in the testing field, there is a high chance you have already heard of Appium. Appium has been in test automation for the last 8.5 years, and its popularity has only increased since.

This mobile app testing framework is highly versatile and officially states that it aims to automate any mobile app in any language in any framework. Therefore, it is one of the most recommended frameworks by app testers.

Key Features of Appium

Appium supports almost every programming language and every framework. So the app tester need not learn a new framework or language and can start testing right away.
Appium mobile app testing framework facilitates reusability of the code by using the same APIs for multiple platforms.
The framework has an extremely large and active community that can help you with every problem in no time.
Appium works with real devices, emulators and simulators as well.
Appium does not let you compile the application in the Appium environment because of the issues it creates later on after shipping in a different environment. Hence, Appium runs its test on the same development framework and language to give confidence around the application development.
The framework can be integrated with CI/CD tools very easily.

LambdaTest is a cloud based mobile app testing platform. LambdaTest offers a reliable, scalable, secure Appium test execution cloud that helps app testers accelerate their release cycles. You can test using emulators, simulators, and real device cloud. In addition, you can access any device you need directly from your desktop browser. Up your game with free Android automation testing via Appium.

LambdaTest

“A Boatload of Capabilities with Surprisingly Few Obstacles” — LambdaTest user

Key Features of LambdaTest

LambdaTest is an AI-native test orchestration and execution platform that lets you run manual and automated tests at scale with over 3000+ real devices cloud, browsers and OS combinations.
The platform provides unique features such as geolocation testing, localization testing, app test automation etc., that are not available on many other platforms.
LambdaTest provides a lot of integrations for the app testers to enhance the platform’s functionality and provide a one-stop solution to app testers.
The platform is easy to learn and is faster to launch the applications on their virtual testing platform and real device cloud.
Run tests in parallel on Appium mobile device cloud at scale. Run tests at scale across multiple devices at a time and reduce your overall test execution time by more than 10X.

What’s your favorite tool?

Mobile app testing frameworks are on the rise today due to their software development and delivery needs. While there are many more mobile app testing frameworks, we focused on the top four in each category and gave insights about them. But a framework is good as long as people like us prefer it in our day-to-day testing scenarios. Let us know your personal favorite mobile app testing framework and the reason you prefer them above all else. Please mention your answers and suggestions in the comment section below.

I hope this post helps you decide your mobile app testing framework if you are new in testing or helps you recalibrate your existing choices. Till then, happy mobile testing!

What Is AI Unit Test Generation: Key Strategies and Tools

Harish Rajora — Fri, 20 Jun 2025 07:28:35 +0000

Writing test scripts for all unit test cases can be time-consuming and prone to human error. To mitigate this challenge, you can use intelligent techniques such as AI unit test generation.

With AI unit test generation, you can streamline the process of writing unit test scripts by automating test creation, reducing manual effort, and enhancing your overall testing process.

What Is AI Unit Test Generation?

AI unit test generation is the process of using artificial intelligence to automatically create unit test scripts for software applications.

Instead of manually writing test cases for unit testing, AI tools analyze the the logic, structure, and behavior of the code to identify key functions, edge cases, and potential failure points. Based on this analysis, they generate unit tests that include inputs, expected outputs, and assertions.

Importance of AI Unit Test Generation

When unit tests are generated through artificial intelligence, the team reaps the following benefits, impacting the method and quality of software development process.

Test cases generated through AI cover a wider range, as the goal of the software is to cover all aspects of the functionality. This includes edge cases as well that testers often overlook.
AI unit test generation targets each line of code, even if the tests may become more complex. This results in better test coverage and, therefore, a better unit test suite.
AI-based unit testing can automatically modify the unit test scripts when the codebase is changed or updated, so you do not need to maintain these tests.
When AI is deployed to generate unit tests, you have more time to invest in code enhancement or work on other functionalities.
Since you invest time in other development tasks, this can be directly associated with costs that have a visible ROI. AI unit test generation, therefore, becomes a great way for the team to save costs in unit testing.

Framework for AI-Based Unit Test Generation

Generating unit tests using AI requires integration between machine learning models and software testing processes. At a higher level, a framework is designed whose high-level components look as follows:

Large Language Model Configuration and Integration: To work on AI technology, an LLM model is required. This model is tuned and fed according to the tasks it will perform. The team and the organization decide which model to choose. The model automates the generation of unit test scripts in the desired programming language. It can also have additional functionalities, such as prioritizing functions and providing options to regenerate tests if required. However, these are considered enhancements rather than core requirements.
Test Generation: The integrated LLM model generates test scripts and saves them in a separate file with extensions that match the targeted programming language.
Test Execution: In this stage, the tests generated in the previous stage are executed. This stage also connects with the reporting module, where the test results are documented automatically.
Analysis and Regeneration: The final results are presented to the tester, and if regeneration is required, the model has to be run again. Here, there can be multiple modifications according to the tester’s requirements. For instance, the tester can run a different model to see if it generates better output. If the framework is designed autonomously, all these options can also be chosen automatically.

This is a generic framework design for AI unit test generation. You can also add other modules to make it more productive and efficient, depending on their requirements. However, the stated modules have to be present as a foundation.

Key Strategies for Using AI in Unit Test Generation

To make effective use of AI for unit testing, there are some strategies that you can follow:

Use AI to generate realistic synthetic test data. This type of data covers a variety of test cases and may be used to assess how a software application will behave across a variety of conditions.
Define specific goals for your AI unit testing efforts. Also, defined objectives to ensure a focused and structured testing approach, targeting key areas effectively.
Test individual components in isolation to unearth issues within specific units. It will make your debugging simpler and efficient.
Adopt a Test-Driven Development (TDD) approach, where you first write automated tests, then develop the code required to pass those tests. By doing so, you can have a good understanding of the expected behavior of all the components of the software application, and at the same time, your test scripts will cover all functionality from the beginning. It also makes it easier to find and fix issues quickly during the development process.
Besides leveraging AI, integrate your test suites with CI/CD tools. This way, the tests will execute on each code commit, keeping high code quality and ensuring faster bug detection.

Top AI Tools for Unit Test Generation

Unit tests can be generated automatically through AI using the following tools.

1. KaneAI

KaneAI is a GenAI native end-to-end test assistant for high-speed quality engineering teams. It is built on modern LLMs, where you can write test steps in natural language command instructions.

It can be used to generate unit tests using high-level objectives or tags through third-party software such as Jira, Slack, and GitHub, and debug errors automatically. The unit tests generated here can be integrated with the CI/CD pipeline for enhanced testing.

Once tests are generated, they need to be run and managed regularly. You can look for tools that do more than just basic input-output tasks, and that’s where LambdaTest’s AI-native Test Manager comes in.

With LambdaTest Test Manager, you get everything in one place — test case creation, management, execution, and reporting. You can create test cases manually or use AI to speed things up.

2. ChatGPT

ChatGPT is one of the most popular GenAI tools. It takes English-based prompts (test steps) and generate unit tests.

It helps you with code explanation, refactoring, debugging, and optimization. It supports multiple programming paradigms, such as object-oriented and functional programming, tailoring responses based on user requirements.

3. Claude

Claude is an AI assistant built by Anthropic, working on Generative AI technology similar to ChatGPT. It takes input from the user and presents the output after analysis. For AI unit test generation, the input can be the instructions to generate unit tests.

Similar to ChatGPT, it comes in free and paid versions. The free version has limited features and a reduced model performance compared to the paid version. The tool is more inclined towards code generation, which makes it a good choice for automatically generating unit tests.

4. GitHub Copilot

GitHub Copilot is an AI unit test generation tool that seamlessly integrates into Visual Studio Code and provides multiple model options for interaction.

It can take multiple programming files as input and update all of them based on the input provided. Therefore, when unit test generation is required, you need not worry about finding the context of multiple files to edit, which ultimately saves a lot of time.

5. Diffblue Cover

Diffblue Cover helps you generate unit tests, specifically in Java. It can be integrated into IntelliJ and CI pipelines, generating automatic unit tests by understanding the code in the files and covering all the edge cases.

It monitors the code files for which the unit tests were generated, and when any change is found, the unit test cases are automatically adjusted accordingly. In addition, this AI unit test generation tool can provide test coverage details in a visual format.

6. Workik

Workik is an AI-powered platform that simplifies the software development process by automating various tasks, including unit test generation. It has an AI-driven unit test case generator that generates test cases for multiple programming languages.

It provides a VS Code extension that enables effortless test case generation and debugging assistance within the code editor.

7. Functionize

Functionize is an AI-powered testing platform that leverages machine learning to automate test creation and reduce the need for manual test creation.

It can detect and fix issues on its own, so you don’t have to spend time troubleshooting. With Generative AI, Functionize also generates a variety of test cases, making regression testing more thorough and keeping software stable.

8. Bito

Bito is an AI-driven coding assistant that streamlines your development process by automating test generation and code reviews. It integrates seamlessly into your development lifecycle, automatically generating and updating unit tests to achieve 100% code coverage.

Its capabilities extend to generating function/method tests, including boundary and edge cases. This enhances code reliability and reduces the time developers spend writing tests.

9. UnitTestBot

UnitTestBot is an IntelliJ plugin that generates tests and human-readable test descriptions. The test cases generated through UTBot do not require manual intervention. They are “ready to use” with valid inputs, method bodies, assertions, and comments.

The rest of everything is taken care of by the tool. UTBot also claims to find hidden bugs in the source code with a 0 rate of false positives. It means all the hidden bugs it finds are indeed real and would have impacted the application at some time. This is a great feature to increase the test coverage and enhance the application’s quality.

10. Windsurf

Windsurf is an AI-powered extension available for popular IDEs such as JetBrains, VS Code, Eclipse, Visual Studio, and Xcode.

It can be used to interact with the code editor and generate unit tests in simple English. However, instead of automatically generating the tests, the tester has to specify the method name using “@,” and the tool can only generate 60–70% of the tests.

Challenges With AI Unit Test Generation

Though AI unit test generation can help optimize your testing process but it comes with a few challenges:

AI models heavily rely on large volumes of high-quality data for training and decision-making. However, gathering and curating such data is often more difficult than it seems. If the data is insufficient or of low quality, it can result in incorrect predictions and reduce the effectiveness of the AI model.
Some AI models — especially those based on deep learning can make it hard to understand how they reach their conclusions. So, this lack of transparency can lead to mistrust, especially when the model makes predictions that turn out to be wrong or unexpected.
AI models may sometimes report defects that don’t exist (false positives) or miss real ones (false negatives). These issues can lead to wasted effort or overlooked bugs, reducing the overall testing efficiency.
You also need to frequently maintain and update AI models to retain their effectiveness when scaling software applications. Without proper efforts towards updates and maintenance, such models can quickly lose their respective relevance and turn out to be outdated.

Conclusion

Unit tests play an important role in reducing bugs, maintenance time, and all the costs associated with these processes. They can point out bugs at specific locations at the start of the cycle and perfect each module as the code base increases.

However, with strict deadlines and shorter timelines, unit testing does get sidelined, often completing the test cases for formalities and writing them according to the methods so that they do not fail and consume more time.

While we cannot shorten the time it takes to write test scripts for the feature, we can leverage AI to generate unit tests automatically, and need not worry about maintaining them in the long run.

What Is Machine Learning Automation (AutoML)

Harish Rajora — Fri, 20 Jun 2025 06:05:04 +0000

Machine learning automation, or AutoML, is a technique used to automate the process of design, training, optimization, and deployment of machine learning models.

AutoML techniques help stakeholders create ML models and deploy them efficiently, even for those without deep expertise. Various tools streamline the machine learning pipeline to implement automation. Some tools focus on specific tasks, such as model selection, while others automate the entire workflow.

In this blog, let’s look at how to use machine learning automation to automate the process of creating ML models.

What Is Machine Learning in Automation?

Automated machine learning, or machine learning automation, involves automating the process of developing a machine learning model. A machine learning model is the final result of a long chain of sequential processes, where the output from one process goes to another.

For instance, a machine learning model first preprocesses the data, prepares the data for training, trains on the data, tests on the testing data, uses an algorithm based on the goal of the product (such as a classifier), and then repeats all these steps on different models to check highest compatibility.

All these steps have to be performed each time a model needs to be developed, and they consume a lot of time. AutoML or machine learning automation automates all these processes and provides a final model ready to be incorporated into the software backend.

Why Is Automated Machine Learning Important?

Automated machine learning provides a lot of benefits to the team working on it:

Since AutoML automates all the manual work to develop the models, non-experts in machine learning can also use AutoML to achieve the same outputs.
Big tech giants use AutoML tools with a dedicated team that works only on machine learning. They constantly tune their machine learning automation process and include high-quality algorithms with greater accuracy.
When it comes to time savings, AutoML saves a lot of time, as almost all the work is done by AutoML tools. Moreover, since human resources are not involved in the machine learning model development process, the time saved can be utilized in other processes, such as model integration, enhancing the team’s productivity. Hence, the software can be built in less time, which means the cost involved will also be less.

How Does AutoML Work?

AutoML works in various steps, the end of which generates a model for implementation in the software application.

Collect Data: The first step in AutoML is data collection. This step is manual and testers are expected to either search for a dataset or create their own (not recommended as it takes a lot of time). It is an extremely crucial step as all the AutoML steps are performed after it considers data for their execution. If the data quality is inappropriate, the model will also show anomalies. The collected data is then fed to the AutoML system as input.
Define the Problem: In this step, a problem is defined within the AutoML tool, enabling it to understand the context, relate it to the data, and generate the most suitable model. Examples of this are classification and forecasting.
Preprocess Data: The next step is the preprocessing of data which is done by the AutoML tool automatically. In this step, the data is cleaned and transformed according to the requirements of machine learning automation. While this process is done by AutoML tools, it is highly recommended to manually preprocess the data as well for higher quality.
Configure Parameters: The AutoML tool provides various parameters to tweak during the model development process. Developers can provide the values and alter the default values based on their requirements.
Train the Model: In the next step, the AutoML tool trains a model on the submitted data, determining its performance and accuracy based on various parameters.
Identify the Correct Model: The data is then trained using various models. This step determines the best model according to the data and the problem defined.
Review the Model: The model leaderboard is then generated and presented to the user with results that include parameters like accuracy. The team can review the model, test it using different data, and if satisfied, start using it in their software application.

Except for the data collection and defining the problem, everything is taken care of by the AutoML tool.

AutoML for Different Data Types

Machine learning models are created for different purposes and each of those purposes is satisfied by only a certain type of input data.

For instance, if you want to create a model that can detect fraudulent transactions in a banking system, you have to train that model using financial transaction data where each transaction is labeled as “Fraud” or “Legitimate.”

Users leveraging AutoML tools can work with various data types, including:

Image Data

Computer vision is a discipline of machine learning in which the model can recognize and classify an object according to pre-defined labels based on the training data.

When machine learning automation is brought into the picture, it takes over the identification tasks of certain features that will guide the model in classifying that particular object without manual intervention.

The quality of data, however, plays a key role in the training of the model. The images used should be diverse, including the object requiring classification.

Video Data

Image-based categorization can be extended to video data, incorporating additional factors for analysis. AutoML tools working on video data can generate models that can identify objects in a video, analyze their actions, and understand voice commands.

However, it is worth noting that AutoML tools with video support are not currently commonly available due to their higher complexities and low accuracy.

Tabular Data

Tabular data provides information in the tabular form, where the identifier is the class to which each data point belongs. The main goal behind training with the tabular data using AutoML is categorizing the new data into pre-defined classes.

For instance, the team can provide the data based on identifiers that result in declaring an email as spam or not spam. These identifiers can be words used, emails used, etc.
When the same process is done on numerical values, it is called regression. In this data, the final classes are not categories but numerical values.

Another branch of tabular data is time-series forecasting. In this process, the goal is to forecast a certain value in the future based on current trends and past values.

Time-series forecasting is kept as a separate discipline because of its dynamicity and involvement of a high number of variables, such as seasonality and changing trends with time.

Due to such variables, a large number of quality models often fail to work on time-series, and AutoML is often the recommended path to follow.

Textual Data

Textual data is used to train machine learning models primarily for natural language processing. In this discipline, AutoML tools aim to understand the text and make sense of it.

It is done by training the model with appropriate text with pre-defined categorization of information. AutoML tools are expected to include high-quality Bidirectional Encoder Representations from Transformers (BERT)-based models that are finely tuned and work with very high efficiency when it comes to natural language processing.

The type of data to use depends on the problem the team is trying to solve. The team should take its time collecting data, as the quality and type of this data, will determine the quality and type of subsequent phases, resulting in a better model.

Role of Machine Learning in Automation Testing

The inclusion of machine learning in automation testing has played a critical role in revolutionizing how a tester used to perform tasks earlier. It has seeped into almost every task associated with testing, bringing immense benefits to the team.

Machine learning in test automation includes:

Supervised Learning: It uses labeled datasets to assess risks.
Unsupervised Learning: It detects errors and patterns in data.
Reinforcement Learning: In this, neural networks improve through a reward-and-punishment system to minimize flaws.

Here are the use cases of using machine learning in test automation:

Test Case Generation

Machine learning can also generate test cases automatically when a context is given to it.

For instance, providing input such as “test login functionality on www.abcwebsite.com/login" can generate all the steps automatically in the English language without any manual interruption.

Let’s take an example of an AI-native unified Test Manager platform by LambdaTest. It comes with integrated test case authoring and execution capabilities that centralize all test case-related information.

Test Data Generation

Many domains of automation testing require extensive, diverse, and boundary-scenario-covering high-quality data. Defining, collecting, and arranging such data takes a lot of time, as the table can sometimes expand to hundreds of rows. However, machine learning can perform all these steps within a few seconds.

Depending on the model on which the tool is developed using AutoML, generating high-quality data is often just a simple query away as “generate data for login functionality where the password needs to be alphanumeric and contain one special character”.

It is also essential to know that the better your prompts are structured, the better the model will understand the context. You can learn more about the best AI/ChatGPT prompts for software testing.

Test Generation

Authoring and maintaining tests (especially complex ones) has been one of the most time-consuming tasks of automation testing. They require specific programming skills and tools to conduct testing.

Machine learning has been a savior and most widely implemented technology when it comes to test authoring or when you have to generate tests. The NLP branch of machine learning can eliminate the use of programming language, take the script input in the English language, and understand the context (or intent) behind it.

For instance, GenAI native test agents like KaneAI by LambdaTest leverage natural language processing to generate tests effortlessly through natural language command instructions.

To get started, refer to this getting started guide on KaneAI.

With the rise of AI in testing, its crucial to stay competitive by upskilling or polishing your skillsets. The KaneAI Certification proves your hands-on AI testing skills and positions you as a future-ready, high-value QA professional.

Visual Testing

Identifying visual anomalies manually on a web page is difficult. The testers have to go through each pixel and match it to the base image to verify the page’s correctness.

When manual inspection is completed, the pixels are often matched through scripted programming for each web page on the website. This takes a lot of time and if a bug is found, the whole process has to repeat.

Machine learning automation can identify pixel differences (down to single pixel differences) within a few seconds. They are the most efficient solution to this problem and can also be included in regression test suites and run hundreds of times daily.

For example, AI-native platforms like SmartUI offer smart visual UI testing to check websites and mobile apps for visual deviations.

Defect Prediction

Machine learning automation lets you predict future failures in the current code or infrastructure. This helps identify potential bugs (and defects) in code that have passed regression and functional tests but will raise issues in the future.

Such bugs have the highest probability of breaking the production and spoiling the user experience. That’s why having models that can predict failures is a valuable asset to the team.

What ML Tasks Should You Automate?

Machine learning automation can be used in different domains to accomplish a variety of tasks. Some of the tasks where the users can opt for AutoML are as follows:

Text-based content is all over the Internet and serves as a great medium to communicate with the reader. However, when automated tools like chatbots interact with such content, they may not understand the intent and emotion of the text. This results in straightforward, machine-like responses that can be frustrating for the end-user. Automating intent detection with ML models can improve user interactions. For example, in a custom support tool or system, these models can automatically recognize the intent of the messages (positive, negative, or urgent) and prioritize tickets accordingly for faster resolution.
Analyzing images is one of the most common use cases of machine learning. When there is a task where images are to be analyzed, and certain objects are to be identified in them, it is best to automate these tasks with finely tuned models available.
Prediction and forecasting help in getting future value based on past data, current trends, and other variables. Such predictions and forecasting are extremely valuable in strategizing before the time and getting a glimpse of the future to evaluate it.
Classification is one of the most focused areas of machine learning due to its wide usage across different domains. No matter what field the team is working on, they can easily spot an area where classification can fit perfectly.

Machine Learning Automation Tools

To take advantage of machine learning automation, you need to adapt to the right tool built for building models.

The most commonly used tools for AutoML are as follows:

Google Cloud AutoML: It offers tailored machine learning models for different needs such as AutoML Image for image-based tasks, AutoML Translation for language translation, and more. It follows the same process Google uses, making it a reliable and scalable choice for projects of any size.
Amazon SageMaker Autopilot: SageMaker Autopilot builds ML models with full transparency, handling tasks like classification, regression, and prediction. It can process incomplete datasets, fill in missing values, and rank models based on key metrics like accuracy.
Azure Machine Learning: Azure’s AutoML supports classification, regression, vision, and NLP while integrating with Spark Cluster for scalable cloud-based processing. It also lets users deploy pre-trained models from OpenAI, Hugging Face, Meta, and Cohere.
IBM AutoAI: It extends AutoML by adding features like model testing, scoring, code generation, and risk management. It streamlines AI lifecycle management, embeds ModelOps into workflows and cuts costs by automating the entire process.
H2O AutoML: It supports hyperparameter tuning, iterative modeling, and feature engineering. It works with R, Python, and a no-code GUI and integrates seamlessly with Hadoop, Spark, and Kubernetes for scalable model developon, and a no-code GUI and integrates seamlessly with Hadoop, Spark, and Kubernetes for scalable model development.

Conclusion

Artificial intelligence has become a mandatory technology in our software today. It not only brings a lot of benefits, such as cutting down time and costs for each task but also helps in being competitive and ahead of competitors.

However, the road to this integration is not an easy one. It requires multiple time-consuming steps ranging from data collection, pre-processing, running data on multiple models, feature generation, and many more. Moreover, all this can only be done by an expert in AI who themselves costs a lot of money to the company.

AutoML is the answer to all these problems, bringing machine learning model development into the automation world where each of the above processes can be completed without any manual intervention or monitoring. These software are designed to compare multiple models and provide the best possible solution to the users.

How to Use Accessibility Inspector for iOS Apps

Harish Rajora — Thu, 03 Oct 2024 06:58:11 +0000

Every successful app interaction by an impaired user is backed by engineers who prioritize accessibility, using tools like Accessibility Inspectors. Be it iOS or Android, Accessibility Inspector allows you to develop and debug mobile apps for all users, including users with disabilities.

When it comes to iOS apps, testers depend on the Accessibility Inspector, the official accessibility checking tool offered by Xcode, because of Apple’s restrictive ecosystem. It provides extensive code insight and is widely recognized within the community.

Why Accessibility Matters in iOS Apps?

iOS applications are used by 28.54% of all mobile users. This is a large chunk of the 7 billion people who use a mobile phone. When the application has such high potential with a vast audience, it is the responsibility of developers and testers to build an inclusive application that everyone, with or without a disability, can use.

In addition, the more people use the application, the more beneficial it is for the business. The app can generate more data and earn more revenue if in-app purchases are allowed (a good example of this is eCommerce applications). Brands that provide accessible iOS apps also enjoy positive word of mouth amongst the users.

Moreover, legal complaints against organizations are on the rise today due to inaccessibility of the mobile applications. Several organizations and individuals have started to step up to make the application world inclusive for all. Legal cases end up in court or settlement, both of which are expensive affairs. Instead, this money can be put into hiring additional resources and making the iOS app accessible for all.

What Is an Accessibility Inspector?

Accessibility Inspector is a tool developed by Apple to debug accessibility issues. It can be used for macOS and iOS applications and even for apps that will run on Apple watches.

With Accessibility Inspector, accessibility issues can be identified using the following two scenarios:

Issues in the core elements (its code, behavior, styling, etc.).
Issues in navigating from one element to another (such as scrolling, pop-ups, dropdowns, etc).

Accessibility Inspector With Reset Accessibility Settings

Both of these areas are worked upon by analyzing the code associated with each element, a process facilitated by the inspector. However, to ease things out, the Accessibility Inspector can provide suggestions for improvement in the iOS apps for issues such as inverted colors and contrast issues.

How to Use Accessibility Inspector for iOS Apps?

Accessibility Inspector is not a standalone application. It requires support and environment setup before you start performing accessibility testing of the iOS application.

Prerequisites

Verify that the following prerequisites are met:

Enable macOS: The first step is to get a system running the Mac operating system. You have two options: either use a Mac, which comes with macOS pre-installed or set up a virtual machine with macOS.
Install Xcode: Once you have the Mac operating system, install Xcode from the App Store, which is the official IDE that supports Accessibility Inspectors.

Testing iOS Apps Using Accessibility Inspector

To start testing the iOS application using the Accessibility Inspector, follow the below steps:

On macOS, navigate to Xcode > Open Developer Tool > Accessibility Inspector.
By default, the inspector is set to inspect elements from applications running on your Mac. If no device is connected, you can continue using the Accessibility Inspector for applications already running on Mac. For example, open a URL in a browser and test the accessibility of a web page.
To inspect elements on an iPad or iPhone, connect the device to your Mac before opening the Accessibility Inspector.
Once the device is connected, open the Accessibility Inspector, and the list of connected devices will be shown.
Select the device where the app is running. This will display a list of apps that can be inspected.
Choose the target iOS app to continue inspecting. Once you select the iOS app, the inspector’s home screen will open, displaying elements like Basic, Actions, Advanced, etc.

Shortcomings of Accessibility Inspector

Accessibility Inspector is a great tool for inspecting accessibility issues and is one step towards an inclusive app world. However, there are some shortcomings of this tool that need to be kept in mind.

Need for operating systems: Accessibility Inspector is available only on macOS, which limits its use for developers who might be working on other platforms or need cross-platform accessibility testing.

For people using Windows or Linux, procuring new Mac systems for everyone or installing virtual systems (which is not recommended due to false performance metrics) is a huge monetary and time investment.

Absence of real devices: Accessibility Inspector uses Xcode, which uses simulators to run the application on Apple devices. Simulators are never a good idea, especially for iOS-based applications, due to memory shortage and movable devices (which raises issues like network lags).

They also provide incorrect metrics for vital parameters like network response time, load time, etc. It can create a false illusion of how the application works, which will come back to the team sooner than expected from the end-user.

Need for physical devices: The Accessibility Inspector will require a device connected to the system in case real devices are used. However, the tester may require hundreds of devices with different specifications while performing cross-platform and cross-browser testing at scale. They will also require constant maintenance and upgrades.

Buying all the devices is a heavy dent in the balance sheet of the organization considering this is a recurring cost. In such a scenario, the team can leverage cloud-based AI testing platforms like LambdaTest, which offers a device farm of 5000+ latest and legacy iOS devices where you can test and debug your apps.

Limited resource: Accessibility Inspector runs on limited resources provided by the host system, which in turn could be running on its share of resources in the case of virtual machines. Having limited resources that are shared by multiple applications can produce false timings.

Best Practices for iOS Accessibility Testing

Apart from the predefined settings in the Accessibility Inspector, the tester should also consider other accessibility attributes that must be taken care of while performing mobile accessibility testing of iOS apps:

**Contrast: **The WCAG guideline defines the contrast ratio to be at least 7:1 in stricter terms, but 4.5:1 is also acceptable. Below these limits, the elements become inaccessible to people with disabilities.
Media elements: While text elements can be read aloud by assistive devices, there is no way to know what video is played and what the subject is saying in it. The same is the case with image and audio elements (for people with hearing disabilities).
Logical segment division: It is recommended to divide the text into logical sections with appropriate headings. The headings, when read aloud, give the user context about the text that follows and also provide a logical path to remember the content, which is not possible in single long passages with multiple contexts.
Use descriptive links: A web page will contain a lot of links with redirection to the same website pages or third-party websites. While people without any disabilities can open the link and retrace it if it is irrelevant, people with visual impairment will not get the context if the link is not embedded in the correct word. Therefore, it’s important to use descriptive links that an impaired user can easily understand.

Conclusion

As a user without any impairments, it is easier to forget the features and requirements a mobile application should possess to make the lives of all people easier regardless of their abilities. However, a developer and a tester cannot think this way.

Building an application for iOS, which more than 1 billion people use, is a task that requires technical skills and responsible ethics. For this, the most sought-after solution out there is the Accessibility Inspector. It provides pre-built options to quickly inspect how the application looks when accessibility settings are turned on, or the user is using some assistive device.

Mobile Accessibility: Checklist and How to Test?

Harish Rajora — Tue, 01 Oct 2024 08:02:52 +0000

Mobile devices are now essential in our daily lives, with around 6.92 billion users globally, including 270 million in the United States — survey.

Yet, many people with impairments still encounter difficulties when using mobile applications. That’s why making mobile applications accessible is so important. Mobile accessibility means designing applications so that everyone, regardless of their abilities, can use them with ease.

What Is Mobile Accessibility?

Mobile accessibility involves building mobile applications so that they are usable by everyone, including those with impairments. Applications built with this approach are known as “inclusive applications” because they ensure no one is excluded.

Today, accessibility is not just an add-on but a fundamental part of the development process. It should be a standard consideration in every development or planning phase. This is crucial as impairments and disabilities are common, with the WHO reporting that 16% of people worldwide identify as disabled.

Why Is Mobile Accessibility Important?

Mobile accessibility is crucial for ensuring that all users, including those with disabilities, can effectively interact with mobile applications. By prioritizing accessibility, businesses can expand their reach, improve user experience, and comply with global accessibility standards.

Here is why ensuring mobile accessibility should be a priority:

Right to the Internet: Having a consistent experience without bias to enjoy the freedom of expression is called the “right to the Internet”. It is illegal in many countries, including the United States, to refrain someone from this right by providing an app that is not accessible.
Legal implications: Lawsuits filed for inaccessible applications by end-users are increasing yearly. According to the Digital Accessibility Lawsuits, in July 2024 alone there were 103 lawsuits filed for inaccessibility. What is more surprising is that actions are proactively taken by the courts to settle the lawsuits and make the app accessible to everyone. If your mobile app is inaccessible, it can suffer the same fate in the future.
Moral and ethical responsibility: For developers and testers working behind the application, it is their moral and ethical responsibility to make an application that does not restrict a certain section of society from functioning under any conditions.
Boost for business: Restricting so many people from using your app is a missed opportunity for sure. The more people that use the app, the more user data is collected and the more revenue is generated, which is good for business.

How to Test Accessibility for Mobile Applications?

The checklist is a reminder for the testers to remember the elements they need to take care of while conducting mobile accessibility testing. Once that is noted down and kept as a reference, we can execute the testing.

**Choose a method: **The first step is to choose a method of testing. Accessibility for mobile applications requires both manual and automated testing due to the finer details involved in the process. For manual testing, the tester can choose tasks like inverting the color of the application or verifying if the reader can read the text.

Automated accessibility tests focus mostly on the design and user interface part that can be programmatically scripted. For instance, checking alt text on image elements.

**Start testing with in-built tools: **While there are large numbers of people with disabilities, a very small portion of them have major disabilities that require additional help, like a hardware device. Therefore, operating system providers provide in-built software that can assist most people. A tester should always start with these tools as this is the most convenient way to deal with accessibility issues for an end-user, and they prefer it as well.

In-built tools depend on the operating system in use. For instance, Apple provides VoiceOver to read out the contents and handle gestures to navigate through the mobile app. Android, on the other hand, provides a complete suite of Accessibility elements that can be enabled in the settings.

**Select a cloud-based platform for testing: **Accessibility is a sensitive issue that requires careful testing on all types of devices. Leaving a device out of the testing matrix becomes a huge risk in this scenario. However, the problem comes when we look at the list of devices including all the combinations of different specifications.

Walking down the path of procuring them can be a burden for the organization and a hectic task for the testing team as they all will require regular maintenance. A better way to approach accessibility for mobile applications is to use a cloud-based provider that can manage all the overheads leaving just the testing part for the testers.

**Perform usability or beta testing: **Once testing concludes, they need to move on to the next phase — verifying their testing by preferably non-technical folks. This is called usability testing (for a closed group selected by the team) or beta testing (for an open group who themselves volunteer).

This type of testing has several advantages among which the primary one is that it explores several issues that may miss the pre-defined template used by a technical tester. For instance, how a user will navigate through an application can only be answered by observing a real user’s actions. In this case, the people should all have some impairment for a fair observation.

**Generate reports and share them with stakeholders: **Finally, to make sure that the test plan and the final test results are in sync, testers create a report that marks the end of testing accessibility for mobile applications. The report should contain the accessibility areas covered and how those were handled during testing. The statistics and graph representation should be presented for quick and easy analysis for non-technical stakeholders with a success percentage defined for each of them.

Accessibility testing is essential for both mobile and web applications to ensure they are accessible to everyone, including those with disabilities. Also, it is crucial to test accessibility over various browsers, devices, and operating systems to ensure comprehensive test coverage.

To achieve this, developers and testers use cloud-based testing platforms such as LambdaTest that provide a robust solution for testing accessibility across various browsers and operating systems. LambdaTest is an AI-driven testing platform that lets developers and QA engineers perform accessibility testing across real environments on the cloud.

Developers and testers can also automate accessibility testing on LambdaTest using popular frameworks like Selenium and Cypress. To begin with automated accessibility testing on LambdaTest, check out the guide on Accessibility Automation.

Checklist for Mobile Accessibility Testing

Before stepping on to testing the mobile application, you must understand all the pillars of accessibility for mobile applications around which you can build the test cases.

As a tester, always include the following in the accessibility testing cycles.

**Visual impairments: **36% of the total population deals with visual impairments — WHO. These impairments prohibit a user from seeing the application normally and raise difficulty in taking action on it. As a developer and tester, visual impairments top the priority while making our application accessible to the public as it is the most common disability today.

If a user is unable to see the mobile application, the part a developer needs to focus on is screen readers that can read out everything.

So, for visual impairments, auditory features should exist and work for all elements. Testers should also focus on graphic elements like images. The images should contain “alt-text” so that it can be read out and provide a reference of the image to the user.

**Hearing impairments: **1.5 billion people suffer from hearing disabilities today — WHO This means problems in hearing the sound in normal range partially or completely. This number is expected to increase by more than 60% by 2050. Hence, if we keep features for hearing disabilities today in our application, it will be useful for the user and business for many years to come.
Cognitive impairments: **According to the CDC, **11% of people suffer from cognitive impairments, and this number has also shown growth over the years and is projected to rise in the future as well. A cognitive impairment is associated with the inability of the user to concentrate, memorize something for long, or process the data at normal speeds.
Verify images exist alongside text as textual elements are hard to read for dyslexic audiences.
Verify the use of autocomplete on the elements like search fields to help those who have memory-related
Verify that the elements are distinguishable from each other.
Verify that the textual elements are easily readable, font size is comfortable, and there is enough space between each word and each sentence.
Motor disabilities: A motor disability is said to be when the user faces problems in the movement of muscles or controlling their actions beyond a point. Since any user can face a motor disability at any point, developers and testers should always incorporate solutions to it.
**Assistive technology compatibility: **An assistive technology is a physical hardware device that attaches to a mobile via Bluetooth or cable and assists the user in operating the application. It can also be a pre-installed software or from a third party. A popular example of an assistive technology is a screen reader that reads out the text from the screen for people with motor and visual disability.
**Presence of feedback system: **A feedback system is a medium through which the end-user can portray their thoughts, suggestions, and problems to the developers and testers. It can be a short form at the end of the page or a quick survey to learn more about your audience.

Best Practices for Testing Mobile Accessibility

To ensure that the process of testing accessibility for mobile applications a tester is following and the tasks they are executing are in their most optimal nature, they need to follow a few best practices.

**Include accessibility in the test plan: **The implementation of accessibility for mobile applications starts with a test plan. It defines all the requirements, strategies, design, and anything that a tester will do during the cycle. The inclusion of accessibility in the test plan will ensure that all the elements of the testing will take shape with accessibility at its core.
Include accessibility in the design: A test and development plan generally considers only the testing and development strategies. While focusing only on the test plan, we can miss the accessibility implementation because a lot depends on how the website is designed by UI/UX designers, especially when considering visually impaired people.

Including designers in the process helps shape the application according to accessibility from the first development stage, making a tester’s job much easier.

**Use accessibility tools: **Accessibility metrics need to have precise values. For instance, the contrast for visual impairment has to be between a particular ratio. Similarly, the auditory devices have to provide sound between fixed decibel ratio values depending on the scenario.

All of this is hard to measure manually. Accessibility tools are designed to support accessibility testing with features supporting high accuracy and precision in various testing paradigms.

**Do not focus on a single accessibility: **Accessibility is a large umbrella term. It constitutes a lot of impairments, and there is no low or high priority among them, even though some might suggest so through the statistics.

Focusing on single accessibility and leaving out others is a question of the morals and ethics of the testing and development team. Even if it is done partially, it is a good practice to give certain attention to all types of accessibility issues.

In sensitive areas of testing like accessibility for mobile applications, testers must look beyond business revenues and create an application that looks past the normal perception of boundaries with inclusive templates.

Conclusion

1 in 6 people suffer from at least one accessibility issue. This makes it a serious concern for people behind planning, developing, and testing the application so that it serves its purpose to anyone no matter what issues they face.

The first step in building such an application is to gather all the knowledge about the accessibility issues and how they are tackled. Once this is clear, accessibility testing for mobile applications will be easy to perform. All a tester now needs is good planning, good tools, and good people for initial testing and feedback. When all these elements are acquired by the testing team, they are ready to fulfill their moral, ethical, and professional responsibilities to the world.

Test QR Codes: How to Get Started

Harish Rajora — Thu, 26 Sep 2024 06:05:24 +0000

QR codes on websites and mobile apps enhance user experience by providing quick access to content, streamlining navigation, and facilitating seamless interactions. They enhance marketing by linking flyers and posters to special offers, driving user engagement. In retail, QR enables quick, secure digital payments via smartphones, increasing convenience.

By connecting the offline and online worlds, QR codes create a seamless experience. Therefore, it’s important to test QR codes to ensure they work perfectly, are secure, and maintain user trust.

What Are QR Codes?

QR codes (or Quick Response codes) are barcodes containing black squares on a white background. Along with these squares, a lot of markers are also present that do not represent any shape but are readable by a reading device such as a camera.

This arrangement of squares and markers embeds information encoded in the form of numerics, alphanumeric, binary, or kanji. A popular example of a QR code is embedding URL information to open a website by scanning the code.

Here are some of the key characteristics of QR codes:

QR codes are free to generate and require a scan to fetch the information.
QR codes do not require additional software in normal or SQRC to encrypt or decrypt the information.
QR codes can store up to 7089 characters, representing a vast memory sink.
QR codes are customizable and offer flexibility for further modifications.
QR codes with defects can still be interpreted with its in-built error correction mechanism.

Why Are QR Codes Important?

From file-sharing links to payment-linked methods, QR codes have captured most domains that require sharing information, especially on a large scale.

Let’s look at why QR codes are so popular.

Provide instant access to a wide range of information, from product details and website links to contact information and social media profiles.
Simplify accessing information and create a more seamless and engaging user experience.
Offer a contactless way to share information, make payments, or access services.
Provide a cost-effective way to reach customers through marketing materials.
Store various types of data such as text, URLs, location, contact details, and images.

How to Test QR Codes?

Testing QR codes is important to ensure they are accurately readable and redirect users to the intended information or action without errors. This helps enhance user experience and prevent potential issues. Testing QR codes involves several steps to ensure their functionality and readability.

In this section, we will look into some standard steps to test QR codes.

Ensure the QR code is perfect: The first step of testing is to ensure that the QR code is valid.
Scan for verification: The next step is to start the scanning process on a higher level. The main aim at this level is to ensure that the data integrated into the QR code can be retrieved successfully. The testers can make use of a smartphone camera to pass this basic level.
Scan for errors: Many things can go wrong while scanning a QR code. Sometimes, the Internet connectivity is unpredictable, or the link is broken. Such errors should be handled by the team of testers and developers so that the user gets clarification on why things did not work.
List down metrics: Once the primary check is completed, the tester needs to dive into the depth of QR code testing and list down all the metrics to be tested for performance. The metrics depend on the final aim of the QR code and its business association.
Choose diverse scanning devices: Next, we need to diversify the scanning devices. This includes selecting different operating systems with different installed versions and from various manufacturers. If there can be scenarios where the QR code can be scanned with other devices such as tablets, televisions, or QR code scanners, then their different forms must also be included.
Track performance metrics: The performance metrics should be tracked now against all the selected devices. The metrics should be analyzed, and if there are any issues, they should be reported back to the developers.
Test the QR code associated with the backend: The QR code is also related to the backend of the mobile application. For instance, some QR codes are involved in data metrics where a data processing engine takes note of how many QR codes were scanned, from which geographical locations, and whether the conversion occurred or not. This helps businesses optimize their future strategies and make new strategies accordingly.
Ensure the security of the setup: Two security holes can exist in QR codes. First, it is incorporated into the code for authentication purposes in which only select devices can access complete data. Second, the application infrastructure is associated with the QR code on the server side.
Keep QR code tests in regression: Working in Agile methodology may mean we have limited time to complete many things. When things get congested close to the deadline, some testing areas have to be sacrificed, and QR codes can easily be a soft target in such scenarios.

Users might not worry about the QR code type they scan, but testers must understand the type, its usage, and its impact on user experience while testing QR codes.

Basic model QR codes: The original model 1 stored 1,167 numerals, while model 2, with a maximum size of 177 x 177 modules, stores up to 7,089 numerals. QR codes come in 40 versions, with version 40 being the densest, sustaining more damage without losing information.
Micro QR codes: These are compact and store up to 35 characters or 128 bits. They may not be readable by standard QR code scanners and are used mainly in labeling, like on printed circuit boards. Micro QR codes have a single position detection pattern compared to the three in basic QR codes.
Rectangular Micro QR codes (rMQR): Introduced in 2022, rMQR codes are designed to save space by being rectangular rather than square, making them useful for large packages with limited space. They function similarly to standard QR codes but are less common.
Secret QR codes (SQRC): These QR codes encrypt sensitive information. Only devices with the correct cryptography key can access the encrypted data. A special type, face-authenticated SQRC, uses facial recognition for access.
FrameQR codes: This modern QR code allows images and illustrations in the center, offering a flexible and creative way to share information.

Each QR code type serves a specific purpose, and testers must ensure that the QR code type matches its intended use and functions correctly in all scenarios. For example, FrameQR should work with added illustrations, and SQRC should keep information secure from unauthorized devices.

Ease Your QR Code Testing With LambdaTest

QR codes require a camera, which makes it harder to find a platform that supports this feature. Moreover, it is important to have a better hardware response with the inclusion of automation to conduct testing efficiently. Otherwise, all we are left with is procuring hundreds of devices and performing each test manually on each.

LambdaTest stands out as a platform that provides a camera injection feature to test QR codes on a real device cloud of Android and iOS devices. The platform uses sensor instrumentation that facilitates hardware use in applications such as cameras. This can be done by enabling image injection for the session.

The screenshot below shows an Image Injection toggle that you can enable to test QR codes manually.

You can even automate your QR code tests using app test automation on LambdaTest. For more information, check out this documentation on QR code testing using Camera Image Injection.

Best Practices to Test QR Codes

This blog on how to test QR codes already talks about what a perfect QR code looks like and the parameters we need to consider to ensure our QR code shines out. However, there is a small checklist to keep handy so that the essential points are not missed, and the tester is assured that all the test scenarios are covered before release.

Consider all age groups: When testing a QR code, it’s crucial to consider all age groups to ensure everyone can scan it. Different age groups perceive QR codes differently. A tech-savvy teenager might scan out of curiosity, while an older person might need a reference point and clear expectations. Testers must ensure a smooth scanning process for all users.
Consider all devices: Devices vary in hardware and software configurations, making it hard to predict potential issues. Testing the QR code feature on a wide range of real devices is essential. Using online platforms like LambdaTest can reduce costs while providing accurate testing metrics.
Consider environmental factors: QR codes can be scanned in various environments, from shops to billboards. Factors like poor lighting can affect scans. Testers must ensure QR codes work smoothly in different conditions, as users expect a seamless experience regardless of environmental challenges.
Think like a user: To improve QR code testing, testers should adopt an end-user perspective, identifying potential issues and creating a comprehensive list of test scenarios. This approach minimizes the chance of failures post-release.

Conclusion

QR codes are widely recognized and used by all end-users, therefore, it is expected to function flawlessly across all compatible web browsers and mobile devices. This is where QR code testers play a crucial role. They must ensure that each QR code fulfills its intended purpose.

Although this task can be challenging, our guide provides a step-by-step approach for effective QR code testing and best practices to ensure accuracy. Successful testing requires skill, keen observation, and platforms.

13 Ways To Ensure Easier Accessibility on Your Website

Harish Rajora — Fri, 09 Aug 2024 07:26:38 +0000

Many websites do not comply with WCAG accessibility guidelines, forcing people with disabilities to rely on assistive gadgets, which often lack full functionality. It can lead to significant monetary losses due to legal consequences and a negative user experience.

Easier accessibility benefits all users, including those without impairments, as it enhances the overall user experience. Therefore, it is crucial to dedicate time and resources to focus on website accessibility and ensure compliance with WCAG guidelines.

What Is Website Accessibility?

Website accessibility ensures that a site is usable by everyone, including those with disabilities. It involves considering various needs such as visual, auditory, motor, and cognitive impairments. Addressing accessibility from the beginning prevents the need for costly and time-consuming redevelopment later on.

Individuals with impairments or disabilities represent a substantial portion of the global population. According to the CDC reports, 27% of adults, or about one in four, have a disability. As a result, brands with inaccessible websites neglect a significant segment of the population. Additionally, the number of individuals with disabilities is projected to rise in the coming decades.

Therefore, it is imperative to ensure that your website and web applications are accessible to all users. Adhering to web accessibility checklists and best practices allows developers and testers to create inclusive websites efficiently. Integrating accessibility practices early, you comply with legal standards and contribute to a more inclusive and equitable web.

Best Practices to Ensure Easier Accessibility

Tim Berners-Lee, the founder of the World Wide Web, emphasized that “The power of the web is in its universality. Access by everyone regardless of disability is an essential aspect.” This principle reflects the web’s original intent, but many websites fail to meet accessibility standards. Often, this occurs because speed in development is prioritized over inclusive design.

With this learning from Tim Berners-Lee, we have listed some best practices to address and resolve accessibility issues efficiently. With this list of best practices, you will find methods to achieve easier accessibility, focusing on user-centric approaches and effective testing methodologies. You can also ensure a more inclusive and seamless experience for all users.

Conduct Surveys and Research

The first step to making website accessibility easier is to conduct surveys and gather input from a diverse group. Surveys provide exact insights into what people with impairments expect from a website, which is difficult to brainstorm in a room with only non-impaired individuals. These insights will provide a real-life, personalized experience, assuming the survey questions are carefully crafted to target each aspect of the application.

Besides surveys, independent research will highlight recent problems and their solutions regarding website accessibility. This research can be based on users’ experiences and feedback or backed by research papers and new advancements documented in journals. It is important to understand that, like technology, web accessibility implementation styles change over time, and developers should be aware of such changes to ensure easier accessibility.

This step should be taken before starting the planning and implementation phase of the website.

Accessibility Starts From Day 0

The easiest way to achieve easier accessibility is to include it in the planning phase of the sprint or the product. With this approach, it becomes a part of the coding culture and not a separate entity that requires dedicated resources for inspection and maintenance. Including web accessibility in planning also helps shape the product correctly. If this is not the case, the product may evolve in a way that becomes irreversible and not as accessible as it should be for everyone.

Provide Feedback Options

Implementing accessibility comprehensively can be challenging, and developers may inadvertently overlook specific aspects crucial to users with disabilities. To enhance easier accessibility, offering users a feedback channel is crucial. This enables them to highlight gaps in accessibility and helps improve the experience for all users, ensuring a more inclusive digital environment. While legal actions for inaccessible websites are a last resort, providing feedback options empowers users to contribute early in the development process, fostering continual improvement towards easier accessibility.

In implementing a feedback option, developers should:

Keep forms concise to prevent user frustration and abandonment. Divide longer forms into smaller panels if necessary.
Provide contact options such as callbacks or emails to facilitate detailed, personalized feedback.
Consider offering incentives to motivate user participation, as 33% of respondents seek rewards.
If feasible, consider hiring a survey agency experienced in crafting effective questions for diverse user needs.

After getting the feedback, the next step is implementing the solutions to make the website more accessible to a larger audience. As a moral responsibility, it is important to prioritize easier accessibility over assessing each disability based on business revenue.

Use Structure on a Web Page

People with disabilities face challenges while reading an unstructured web page. This is true even with assistive technologies because they rely on how things have been organized and can understand a structured page better. To achieve an easier accessibility, make sure the following rules are followed on a web page:

Create Regions: Identify and mark up regions on the page.
Label Regions: Label the regions so that they are distinguishable and understandable by the user.
**Structure Headings: **Structure the page into multiple nested headings based on their relationship with the parent heading.
**Use Correct HTML Elements: **HTML contains tags that portray a specific meaning on the web page. Use specific tags as they help the assistive devices understand the meaning of that region and navigate across the page easily.

Structured web pages improve navigation for keyboard users and those using assistive technologies like screen readers, leading to easier accessibility across diverse user needs.

Use Descriptive Links

A web page has many links that target internal pages or external third-party websites. Visually impaired people use assistive technologies like screen readers to read out links and texts on which these links are embedded. If the developer has used descriptive links like this:

Ambiguous version: Read More
Long URL: https://www.lambdatest.com/accessibility-devtools

Users cannot figure out the context of these links and may never be able to navigate them. Instead, use texts and URLs such that they describe the page they are referring to. For instance, in the above case, it will become:

<a href="https://www.lambdatest.com/accessibility-devtools">Accessibility DevTools</a>

Something similar in the lines can be embedded in the URL as well.

Use Text Instead of Images With Text

To achieve easier accessibility, it’s vital to ensure compatibility with assistive technologies like screen readers, which often struggle with embedded text images. Despite their convenience in quickly designing UI elements, these images pose significant accessibility challenges.

Assistive technologies perceive the embedded text as inseparable from the image itself, rendering it inaccessible to visually impaired users and depriving them of crucial contextual information, especially on landing pages where such text communicates key business objectives.

Choosing text over images with embedded text requires more effort but greatly enhances accessibility. It ensures all users can access and understand content effectively regardless of impairments. This approach fosters a more inclusive user experience and supports the broader goal of accessibility in digital design.

Use Tables Wisely

The

tag in HTML serves dual purposes: constructing data tables and designing custom elements on web pages. When used for data tables,

tags provide essential structure and help prevent cross-browser issues, particularly concerning responsiveness adjustments.
However, when overused or misapplied, tables can complicate navigation and readability for all users, including those relying on assistive technologies like screen readers. Therefore, using tables judiciously is essential for ensuring easier accessibility across different devices and improving overall user experience.

However, the same structure will hurt the website’s accessibility when the table is too complex and big to be understood by a screen reader. For instance, this is a big and complex table from accessibility and web responsiveness point of view:

When screen readers encounter a

, they announce the rows and columns along with their headings, aiding users in navigating the data. However, for large tables, users may find it challenging to retain all the column information, potentially diminishing their experience and causing them to overlook valuable table data.
The

tag is sometimes misused to structure elements that do not contain tabular data, such as graphical elements or layouts mimicking CSS Grid. This misuse can confuse screen reader users, as these elements are not intended to be read sequentially like traditional tables. It’s best practice to reserve the

tag strictly for presenting tabular data in a textual format that is easier for people with impaired vision to interpret and navigate.
This revision clarifies the implications of using

tags in both scenarios, emphasizing the importance of proper usage for enhancing accessibility.
Do Not Ignore Media Elements

When discussing website accessibility, the focus often leans towards textual content, but media elements such as audio, video, and images are equally crucial, if not more so. Media accessibility not only addresses disabilities and motor control issues but also temporary impairments, such as those recovering from injuries like broken bones. Therefore, it’s essential to prioritize media elements in website accessibility design to ensure easier accessibility for all users.

Two significant issues with media accessibility include the lack of keyboard-friendly native controls on video players, where not all browsers seamlessly switch between controls using the “tab” key. Additionally, differences in how browsers interpret native controls due to various browser engines lead to cross-browser compatibility issues in web accessibility.

To address these challenges, consider moving away from native APIs and focusing on strict JavaScript and HTML coding practices. Browsers universally understand these technologies, ensuring consistent results to achieve easier accessibility across different platforms and assistive technologies.

Make the Website Keyboard-Friendly

Assuming that most users use a mouse to navigate, the website often overlooks those relying solely on a keyboard. For example, blind users often use braille keyboards, and people with limb impairments may rely on keyboards instead of mice. Navigating a website with just a keyboard can be tricky, especially when tabbing through options and making selections.

Developing and testing websites for keyboard friendliness enhances accessibility, benefiting both typical users and those who require or prefer using a keyboard due to accessibility needs. This approach ensures easier accessibility for all users, regardless of their input method.

Incorporate Assistive Technology in Testing

Assistive technology refers to devices that help people with disabilities understand web pages. The specific type of assistive technology used depends on the individual’s disability; for example, those with visual impairments may use screen readers, while individuals with hearing issues may rely on text-to-speech software.

Leaving out assistive technology during testing poses risks for users who depend on these tools to navigate websites effectively. This oversight can lead to negative feedback and the eventual adoption of assistive technologies, underscoring the importance of integrating them from the outset for easier website accessibility.

Do Not Completely Rely on Automated Tests

Automation tests are a preferred method for verifying the correctness of new code and its impact on existing stable code. Once written, these tests can be used repeatedly until there are changes to the core functionality. However, automated tests should not be the only testing methodology used in certain domains. For instance, UI testing should be done manually because automated tests cannot identify all UI anomalies as efficiently as manual testers.

Website accessibility testing requires both manual inspection and automation testing. Testers should use automation testing for scenarios that are compatible with it. For example, contrast can be checked through automation since colors are embedded in the CSS styling code or by using a separate sheet of colors for quick analysis. Checking the alt text of images is also suitable for automation.

However, it is not recommended to use automation to test keyboard navigation or captions on videos. Writing automation scripts for these tests is challenging and can lead to false positives or negatives.

Therefore, do not rely solely on automation tests. Instead, segregate scenarios into two categories: those suitable for automation and those requiring manual testing. Keep the manual testing category robust, as web accessibility is more reliable when verified manually.

Perform Accessibility Testing or Install an Accessibility Browser Extensions

Often, developers may struggle to identify elements on their web pages that don’t comply with WCAG guidelines, which encompass numerous parameters, making full compliance challenging. Conducting accessibility testing is crucial to pinpointing these issues efficiently, allowing developers to address them in line with WCAG standards.

Accessibility testing tools ensure web pages meet WCAG guidelines by detecting and resolving accessibility issues. Additionally, utilizing accessibility browser extensions, such as those offered by platforms like LambdaTest, can significantly help in making websites and web applications accessible to all users. It is an AI-powered test execution platform that allows you to run manual and automated accessibility tests at scale with over 3000+ browsers and OS combinations.

As an accessibility browser extension, you can make use of LambdaTest Accessibility DevTools Chrome extension that allows you to easily test, manage, and report accessibility issues with features like partial scans, full scans, multi-page scans, and workflow scans that focus on continuous accessibility scanning by capturing dynamic interactions and page changes.

The most interesting part of this extension is that it can classify the issues and suggest solutions for each issue, making web accessibility easier for manifolds.

Beta Test or Usability Test With Impaired People

Once developers and testers have followed all the guidelines and methods to create an accessible website, it is beneficial to have it tested by impaired people. This helps prevent negative feedback and the need to rebuild certain parts of the application after release.

Creating a team of diverse individuals representing various impairments is advisable to get comprehensive feedback before the application reaches millions of users. The team can choose either beta testing or usability testing for this step, as both approaches will yield similar results in terms of outputs and efficiency.

Conclusion

Integrating accessibility is crucial for creating an inclusive and user-friendly website. Conducting surveys and research to gather insights from diverse users ensures your website meets real-world needs. Incorporating accessibility into the planning phase makes it an integral part of the development process, promoting easier accessibility rather than treating it as an afterthought. Feedback options are vital for identifying and addressing accessibility gaps and should be easily accessible to users.

Combining automated testing with manual inspection thoroughly evaluates easier accessibility. Tools like LambdaTest Accessibility DevTools are valuable for ongoing monitoring and issue resolution.

These best practices underscore the importance of considering all users, regardless of their abilities, to achieve easier accessibility and create a more inclusive digital environment.

16 Tips To Use Chrome DevTools For Cross Browser Testing [2024]

Harish Rajora — Thu, 08 Aug 2024 10:06:57 +0000

Google Chrome is the most used browser as of 2024. Google seems to continue to hold its position 1 for at least a couple of years, if not more! Holding the most dominant browser market share makes it an inevitable part of the cross browser testing checklist of every QA manager. One of the most valuable features that have become an indispensable part of every web developer’s and web tester’s daily routing is Chrome Dev Tools.

Being of this importance, it is absolutely necessary for the testers to know how they can leverage Chrome Dev Tools to their full extent and perform better testing. Although developer tools are available in all the major browsers to help their fellow developers debug any cross browser compatibility issues, Google Chrome is always striving to add more features to help professionals get the hang of Chrome Dev Tools more conveniently.

In this post, we will highlight the top 16 tips to use Chrome Dev Tools for cross browser testing. However, if you are just starting out as a web developer or web tester then we will start off with a basic section to help you open the developer tools in your browser.

How To Open The Chrome Dev Tools?

Before working with the different tips for developer tools on Google Chrome, a tester should know beforehand about how to open Chrome Dev Tools. Developer tools in Google Chrome can be accessed by the following methods:

Open your Google Chrome browser. Go to the website on which you want to debug. Perform a right-click on the screen and go to Inspect.
Another way to access Chrome Dev Tools is by using the keyboard shortcuts. You can either press Ctrl + Shift + C (Cmd + Option + C) or Ctrl + Shift + J(Cmd + Option + J).

Similarly, you can also leverage Developer tools in other browsers. Here is how you may open developer tools in Mozilla Firefox and Safari.

To open Developer tools in Mozilla Firefox, go to the website and right-click on the element you wish to debug. Then select Inspect Element.

Similarly, to open Developer tools in Safari, go to the website and right-click on the element you wish to debug. Then select Inspect Element.

For this post, as I mentioned, we will stick to Google Chrome. Let’s us look into the 16 tips to use Chrome Dev Tools for better cross browser testing.

Tip #1: Finding an Element

This feature helps the tester/developer find any element on a webpage in the source code. Open your Chrome Dev Tools & visit the “Elements” tab. Once you are in the Elements section, press Ctrl + F (Cmd + F). This will open an input box where you can enter the element you desire to find and the tool will highlight it for you.

Tip #2: Add and Edit CSS Elements Directly

Chrome Dev Tools let you add the CSS elements into the code. You can even edit these CSS elements directly from the console.

That way, you can make changes to the styling of your web page instantly. These changes would only be applicable on your browser for a particular session. So once you reload the page the changes would be reverted.

Tip #3: Change Position Of Elements

In the Elements tab of the developer tool, you can change the position of the elements by simply dragging and dropping to the required position. This will show you the updated code’s rendered output on the screen.

Thay way, you can restructure and experiment with the current webpage to evaluate where your content fits best.

Tip #4: Locate CSS Property In Sources

Many times a tester needs to find a property in Sources which is defined in the Elements to make some changes to it. They can achieve this quickly with Ctrl + Click (Cmd + Click). You can then visit Sources to find the property highlighted.

Tip #5: Screenshot An Element

The developer and tester can take a screenshot of an element. To capture a screenshot of an element through Chrome Dev Tools, select the element and then press Ctrl + Shift + P (Cmd + Shift + P). This will open up the command console which accepts various commands. Enter CAPTURE SCREENSHOT as the command to take a screenshot of the element.

Tip #6: Continue Console Operation

While working on the console, you might have noticed that every new line gives a certain output which depends on the expression you defined in the previous line. With Google Chrome Dev Tools, you can use this output on your next expressions by referring to it as “$_”.

Tip #7: Multi-Lines Scripting Feature in the Console

The console in any software or operating system normally gives an output of the previous expression on every new line. The developer console also works similarly. However, in Chrome Dev Tools Console, a tester can choose to go for multi-line scripting in the console. To enable the multi-line scripting feature, press Shift + Enter.

The console tab is bound to get clustered with various logs. To clear the console, you need to press Ctrl + L (Cmd + K).

Tip #8: Locators For Selenium Automation Testing

For automation testers, Chrome developer tools have become imperative. While you are performing Selenium automation testing, location elements are crucial to help direct your WebDriver to the correct element. Locators in Selenium helps you to accomplish that. Using Locators, you can locate a specific web element over a web page. Below are the types of locators in Selenium.

ID
Name
Linktext
Partial Linktext
Tag Name
Class Name
CSS Selector
Xpath

Using Google Chrome developer tools, you can find the necessary input for these locators. For example, if you wish to leverage the XPath of a web element, you can copy it using the developer tools and feed it to your Selenium automation scripts.

Tip #9: Clear Cookies

Testing any third party applications creates a lot of cookies while debugging. Since debugging requires executing the script multiple times, cookies can interfere with the actual result. So, these need to be cleared. Although Google Chrome provides an option in the Settings to do this, the tester can save time and quickly clear all the cookies from the developer tool only for that specific website or webpage.

To clear the cookies, go to Applications -> Cookies and clear all the cookies or only specific ones.

Tip #10: Reach Specific Line and Column Directly

You can reach a specific line and column directly in the Chrome Dev Tools through the panel. You can open the panel to enter the line and column name by pressing Ctrl + O (Cmd + O).

Tip #11: Switch Files Within Project

A web-based project contains many files within. As a web tester or web developer, you may need to switch between these files many times during the integration testing or even unit testing phase. Developer tools provide quick file switching within the project by just typing the name of the file in the panel.

The panel can be opened by pressing Ctrl + P (Cmd + P).

Tip #12: Watch Expression

Chrome Developer Console provides a feature called watch expression. This feature is located in the “Sources” tab in the right column. A tester needs to keep an eye on a variable or expression a lot of times during the debugging phase. Finding, again and again, takes a lot of time. By watch expression feature, the Chrome Dev Tools do that for you. The tester needs to enter the expression or variable in the section and it gets updated every time there is any change.

Tip #13: JavaScript Breakpoints

For a typical website, JavaScript codes are long. With so many values changing on a single request, the tester needs to locate and observe them for better testing. For example, an API request using AJAX might run 4 times and provide different status codes. This needs to be checked at every point to test efficiently. For this, developer tools provide a feature called JavaScript Breakpoints. Using JavaScript Breakpoints, you can define the particular line of code where you wish to halt the execution. To apply a JavaScript breakpoint, simply click on the line where you need your JavaScript code execution to stop.

Tip #14: XHR/Fetch Breakpoints

The “Sources” tab contains the XHR/Fetch Breakpoint section below Watch Expression. With this, you can set a breakpoint in the script any time an XHR/Fetch request is sent. The tester is also free to use this feature only on specific XHR/Fetch requests with specific URLs.

Tip #15: Initialize Multiple Cursors

Wouldn’t it be cool to write on different lines simultaneously? Well, Google Chrome Developer Tools allow a tester to achieve that by initializing multiple cursors. Multiple cursors can be initialized by pressing Ctrl + Click (Cmd + Click). Once the cursors are initialized, whatever you write, will be written in all the places.

Tip #16: Monitor Performance

Google Developer tool allows the tester to monitor the performance of the website directly from the tool. This helps the tester validate the resources that are being used such as time, activity and source. For monitoring the performance of a webpage, you would need to visit the performance tab in the Chrome Dev Tools and press Ctrl + E (Cmd + E) and then press Ctrl + R (Cmd + R) to reload the page. Hit the stop button to halt the performance monitoring.

How to Access Chrome Dev Tools On LambdaTest?

LambdaTest is an AI-powered test orchestration and execution platform that provides an easy and quick way to access the developer tools in Google Chrome, as well as other browsers such as Mozilla Firefox, Opera, Safari, Internet Explorer, Edge, Yandex. You can even open developer tools over Android and iOS browsers while cross browser testing.

For desktop browsers, you can access Developer Tools using the same way as we saw above. Just right-click and inspect. For mobile browsers, you will find an option inside the controller buttons on the left.

Make sure to incorporate Developer Tools a part of your cross browser testing checklist to ensure cross browser compatibility with LambdaTest.

10 Top Frustrating Browser Compatibility Issues Devs Face In 2024

Harish Rajora — Wed, 07 Aug 2024 05:50:34 +0000

Developers are dealing with cross browser compatibility issues for some time now. The question that always looms in their minds is how we can give the best user experience to everyone despite the differences in the underlying mechanism of the browsers and the features they support?

With many people connected to the internet on different devices using their choice of web browser, web developers don’t see a single browser as their target. Instead, everyone wants to gain a competitive edge by providing the best user experience. Hence, bridging the gap between legacy and modern browsers is an essential task for developers globally.

In this post, we will deep dive into some major pain points that cause browser compatibility issues for developers. Let’s go!

Internet Explorer: What went wrong?

In the survey conducted by MDN, Internet Explorer was found to be the most troublesome browser by 70% of the respondents.

Once dominating the browser market, Internet Explorer has become a pain point for developers in 2021. Rapid growth in technology and many other reasons led to the death of internet explorers in recent times. However, there is a substantial audience using Internet Explorer for web browsing that cannot be ignored.

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Internet Explorer was a great browser, but as time passed and technologies started evolving, it became obsolete. More browsers started coming into the market, having versatility and being feature-rich. Internet Explorer was just dated!

Today in 2024, the problem with Internet Explorer is that it does not support multiple features compared to other browsers. For example, multi-class support (JavaScript) is not available, Form layout designing is a nightmare, and most of the new properties that came in were never updated. CSS Flexbox is supported on Internet Explorer but with multiple issues.

There are a lot more features, properties, and functionalities that are not supported. As a developer, your priority is to test on Internet Explorer for cross browser compatibility issues.

Microsoft retired support for Internet Explorer 11 on June 15, 2022, for certain versions of Windows 10, including desktop applications.

Microsoft Edge will come with an “IE mode” through which you can access and test websites on Internet Explorer.

Why can’t we just leave Internet Explorer and move ahead?

I am sure you must be thinking, why don’t we just drop it from our target browsers and move ahead with the concept of “Change is constant?”

As per netmarketshare, the browser market share of Internet Explorer is still 0.09% worldwide on desktops and laptops.

0.09% is a small percentage, but it still highlights the importance for developers to ensure their websites or web applications are consistent with Internet Explorer. Despite its declining usage, Internet Explorer remains woven deep into many systems.

During its peak, Internet Explorer was the foundation for numerous applications across finance, inventory, accounting, and even critical systems like MRI or CT scan machines. While many have transitioned to modern browsers, the cost of overhauling these systems is significant, leading to Internet Explorer still being used by millions globally.

The message here is that as developers, skipping Internet Explorer is not yet an option. It’s crucial to develop and test websites for cross-browser compatibility issues, including Internet Explorer, to ensure a smooth experience for all users.

CSS: An important factor causing browser compatibility issues

The next browser compatibility issue developers mentioned in the survey is CSS, and it’s not a surprise. CSS is messy and unpredictable!

Web developers are often found criticizing the CSS and supporting their backend development on the web. I have seen developers not preferring CSS because they think that logic is more important than styling during product development.

Bottom line — CSS is messy and unorganized! Several of its sub-branches, such as CSS flexbox and CSS position sticky, are a problem in themselves. They raise browser compatibility issues and have no turnaround. However, they are being fixed by Google, Igelia, Microsoft, and Mozilla combined with the project name Compat21.

To learn more about the browser compatibility issue in CSS follow this guide top browser compatibility issues in CSS and get valuable insights.

Browser Compatibility Issues With Old Browsers

The “old browser” pain point can be seen as a larger umbrella that covers Internet Explorer under it. Old browsers also constitute an older version of the current browsers (which are still actively developed). These may include Google Chrome, Firefox, etc.

The reasons here are still the same. Old browsers often do not come with 100% support of the latest technologies. CSS is changing and adapting for good, but we cannot implement it completely because 0.09% of people still use Internet Explorer (even if I just exclude every older version).

As per the statcounter report the Google Chrome is on version 122, equipped with the latest features and currently it is the most widely used browser with 65.31%.

Chrome 120 was released in the previous year on November 29th, and we would certainly hope that people no longer use it. However, it’s not uncommon for users to work with older browser versions for various reasons. This is why it’s essential to test for browser compatibility issues across all browsers and versions when developing a website.

Improve and resolve browser compatibility issue by preforming cross browser testing seamlessly over the cloud Try LambdaTest Now!

Explore the best Chrome extensions for developers and streamline your coding process. Start now!

JavaScript Cross Browser Compatibility Issues

JavaScript is among the top four pain points in terms of browser compatibility issues for developers. As per the survey, around 5% of the people find JavaScript hard to work with.

The main browser compatibility issues in JavaScript are:

Different ECMAscript versions need to be aligned with different browser versions.
ES6 features are supported on old browsers but with Polyfills.
Native support in JavaScript is missing.
Bloated code due to running code through transpilers.

Another reason is JavaScript also survives on modules and packages. A small application can therefore contain many modules, which affects the speed and makes it slower.

This reminds me that JavaScript is also blamed for being a slow language on the web. For instance, view this graph that shows the time taken by different languages for calculating the value of pie:

JavaScript is below C, C++ (expected), and even Python and PHP!

However, many survey participants mentioned that fixing JavaScript cross browser compatibility issues isn’t very problematic to deal with. Thanks to transpilers and babel that proved helpful in recent years.

Do you want to perform end-to-end cross browser compatibility testing of your website? Watch how to perform cross browser testing in the demo video given below and get your browser inconsistence fixed in no time.

To learn more about various automation tutorial you can Subscribe to the LambdaTest YouTube channel for details guidance on Selenium testing, Cypress testing, and more.

Rendering Issues in Browsers

Rendering issues are more of browser compatibility issues where you have some element working on a single browser but miss it out completely on another one.

The point is, they work on browser engines which are responsible for everything you see on a browser. Unfortunately, browser engines are different in different browsers and render the page differently. This leads to inconsistent font sizes or abrupt image ratios.

Let’s take an example of CSS writing modes. It helps us define the direction of writing with few options. For example, the support for writing-mode “sideways-lr” and “sideways-rl” is as follows:

When I say “does not support,” it means the browser engine is yet not ready to understand what that means and will bypass the property with default values.

How to test web rendering issues?

Installing every browser and its version to test websites for cross browser compatibility is practically not possible. However, cloud testing platforms like LambdaTest. LambdaTest is an AI-powered test orchestration and execution platform that lets you run manual and automated tests at scale with over 3000+ real devices, browsers and OS combinations.

This platform helps you conduct cross browser testing with ease, you can test your application on various browsers and OS combination without having to worry about infrastructure.

LambdaTest is an online platform equipped with all the combinations of browsers and platforms installed on their cloud infrastructure. As a user, you just need to choose the target platform (such as Chrome 122 on Windows 10) and enter the URL to launch it on that combination. Being a cloud platform, you can perform tests irrespective of the device you are using. For example, you can even test Internet Explorer on Mac using LambdaTest platfrom.

Layout and Styling Issues

From the MDN survey, it was found that the majority of developers are struggling specifically with layout and styling issues. For example, CSS Flexbox & CSS Grid are troublesome in achieving layout consistency across different browsers.

It was also observed that responsive design or responsive layouts have issues with supporting dynamic viewport sizes and scrolling issues. Thus making it one of the critical browser compatibility issues for developers.

To learn more about how to deal with responsiveness and how you can manage it better by ensuring that your website is responsive in any view point you can prefer trying out LT Browser offered by LambdaTest to resolve the responsive issue. With this detailed guide on responsive testing get started with resolving responsive issue and build a consistent application.

Slow Adoption of New Features

Many features are released by JavaScript and CSS developers but are delayed in adoption by browsers. As a developer, I would like to include some cool new things on my web page. However, slow adoption leads to delay in implementation and higher browser compatibility issues.

For instance, CSS subgrids is a cool feature where a grid can be implemented inside another grid. It solves a lot of problems for front-end developers and designers. But the current support for subgrid is as follows:

Which is not even “okay.” Only Mozilla Firefox currently supports subgrids. If an engine is lagging in terms of feature adoption, it can make the website less competitive. The below graph depicts how tests are failed, particularly on Safari and not on Chrome & Firefox. Even though Safari is very popular, it still supports lesser features as compared to its competitors.

Browser Compatibility Issues With PWAs

A small percentage of people on the survey (around 3%) hinted at PWAs as a pain point in their development journey. A progressive web app is an application that is not native and neither a web app. This is the strength of PWAs and probably the weakness too.

Since PWAs are not native applications, they cannot take advantage of the native properties of any device, such as a camera or file access, etc. For this, they need support from the browsers, which are currently evolving.

Google is however determined to make PWAs popular in the near future. Therefore, you always get a list of Web APIs being released for the PWA development. So if you hear someone say their browser is not supporting PWAs, they could mean that API support is still in the dark.

Also, PWAs need to have a fixed icon (dimension rules, etc.) and a manifest personal to the browser. So browser compatibility testing plays an important role when you develop PWA’s. This is not something that cannot be done, but repetitive tasks and fixing icon images does hurt a little bit.

To learn more various type of apps such as hybrid, native, progressive web apps and more follow this guide on different types of mobile apps and get valuable insights.

Discover the top JavaScript unit testing frameworks and ensure your code is bug-free. Click here to learn more!

CSS Flexbox Design Issues

Another important pain point for cross browser compatibility issues is CSS Flexbox. It comes with a long list of properties that determine how these items can be distributed and the role of the container in it. We have created a CSS Flexbox tutorial that can come in handy for those new to CSS flexbox or CSS if that matters.

Flexboxes are a part of the Compat21 project, which focuses on today’s five most important issues in browser compatibility. Although Flexbox is performing well currently, as long as the developers like you keep logging those issues, 2024 will see much better browsers. Some of these issues are vertical flexbox and images as flexbox items (which are resolved now).

Flexbox has also topped the survey’s layout issue part where Flexbox is considered to be the most troublesome layout issue currently:

So, yeah! Flexbox creates design issues and is infamous for it at the same time is extremely popular among developers. It is something that gives content structure on a web page. As per Google, 77% of pages contain CSS flexbox in the source code:

As far as the browser compatibility issues are concerned, developers see many inconsistencies in design in different browsers. Also, not all the flexbox properties are supported by all the browsers currently.

All this makes us think twice before writing display:flex on the web page. But the only other option we have is the CSS grid, which is not a smooth road either. CSS flexbox reminds me of the popular quote, “Love it or hate it, you cannot ignore it!”.

Polyfills Can Often Be Tedious

Polyfills are the code segment that is applied when an actual property fails to implement. For example, if a browser does not support vertical alignment, then I might have to write JavaScript code for aligning it manually.

In a way, they are the fallback option that works when everything fails. Polyfills are extremely important in web development because, as we discussed above, many things fail across browsers. Honestly, browser compatibility is a mess, and it becomes a developer’s job to maintain a consistent web application across all platforms.

Polyfills are often written in JavaScript because that is where all the manual work has to be done. But polyfills are in no way confined to JavaScript. They are part of a generic term, and the misconception lies in the community. Polyfills become the pain from their existence in the market. They are perceived as “extra code” or “extra work” that has to be done by the developers even though it would not have been required with consistent browsers.

So, how would you approach writing polyfills? First, implement the property in the most straightforward way you think. Then check for browser compatibility issues and write polyfills. This extra work results in a larger user base, but no one wants to write the same thing with two methods at least 10–20 times a day. It’s a pain! Especially if older browsers are a part of your browser matrix.

You can download the template provided to create a browser matrix, which can help you determine the necessary steps to make your website compatible with various browsers.

This matrix can also assist in creating a comprehensive test strategy for your website.

Follow our best practices for microservices design patterns to streamline your development.

Conclusion

If something does not work in Chrome or Safari, you cannot do anything in it. You just have to deal with it by applying some polyfills, writing a unified code, or maybe changing the feature altogether. This dependence has resulted in a survey that explains a few loopholes in the system and its progress. I am sure browsers have their reasons, but cross-browser compatibility is one such thing that annoys a developer more than anything. But I guess a perfect world does not exist, and here we are complaining about its imperfections. I hope this post will make you feel great that millions of developers are frustrated with the same things as you.

By the way, I am quite sure that “Security” is the latest trend these days as every browser developer launches or deprecates a feature and writes the reason as “security”. But who suffers in the end by all this?

How To Use Xcode for Windows To Build iOS Apps

Harish Rajora — Tue, 06 Aug 2024 08:15:41 +0000

Xcode is an Integrated Development Environment (IDE) that runs exclusively on macOS. This means that Xcode cannot be used on Windows machines, posing a significant challenge for developers. The restriction that Apple’s software cannot be used on non-Apple machines becomes a barrier for many developers and organizations who cannot afford a Mac machine.

However, there are alternative solutions for developers who want to build iOS apps but lack access to Mac hardware. Developers can use Apple’s powerful development tools without expensive equipment by finding alternative ways to run Xcode for Windows.

Yet, several questions arise when attempting to overcome this restriction: Is it impossible to avoid solely relying on Apple for development? Or can we find solutions to set up a stable environment on our systems and run Xcode for Windows?

What Is Xcode?

Xcode is an IDE for developing software for Apple’s operating system, i.e., macOS, iOS, visionOS, etc. It is free to use and is recommended by Apple for its best experience in app development, debugging, and testing. This includes features facilitating Apple app development, such as code completion and integrating version control systems like Git to commit from within a single screen without leaving the code.

Not only the development but Xcode tries to provide a single solution for testing as well. Features like capturing the test results and diagnosing them with video and screenshots prove helpful for testers and save much of their time.

The benefits of Xcode surpass its popularity, and it is often the most recommended tool for app development for Apple operating systems. That doesn’t mean each developer and tester must buy an Apple machine when they have already worked on Windows OS systems for all other projects.

Want to boost your coding skills? Explore the top programming languages to learn in 2024. Start now!

How To Build iOS Apps With Xcode for Windows?

Xcode is officially available only for macOS, meaning developers typically need access to a Mac for iOS or macOS app development. While official support for Windows in Xcode is unlikely, developers and testers can explore alternative methods to develop applications without relying on an Apple machine.

This is possible with a few additional steps and some extra effort.

Selecting a Virtual Machine Software for macOS Installation.
Installing the virtual machine.
Installing macOS on the virtual machine.
Downloading Xcode.

Let’s start by selecting the virtual machine software essential for using Xcode for Windows.

Selecting a Virtual Machine Software for macOS Installation

Virtual machines are a concept that divides the resources of the primary operating system to install another operating system alongside them. This gives us a perception that the system has two operating systems, but in reality, one is primary while the other is virtual (also called a guest operating system), which means it just exists within a sandbox environment.

Without software assistance, developers cannot run two operating systems simultaneously on a single physical machine. They need virtualization software to create and manage virtual machines, enabling the simultaneous operation of multiple operating systems.

Learning about how various operating systems handle resources is important. For those wanting to learn more, looking at Operating System Interview Questions can give useful information on system virtualization and its uses.

Two popular virtualization software options are listed below:

VMWare
Virtual Box

VMWare

It is a well-known name in virtualization technology, having been around since 1998. It has evolved to meet changing requirements and is known for its efficient resource utilization in guest operating systems. VMware is scalable and highly secure.

A user can boot an operating system by two methods with VMWare:

With PXE (Preboot Execution Environment), which is server-based booting.
With a media device (such as a pen drive)

Both methods are effective, but using a media device is more popular. It is faster and easier to install the operating system. Users only need to assign the memory usage and specify the OS and platform ISO image locations, and the OS will be ready to install Xcode.

VirtualBox

VirtualBox is another popular virtualization software offered by Oracle Corporation. It is open-source and provides high performance for users wanting to install multiple operating systems on their PC or Linux machine. VirtualBox is known for its user-friendly interface and fast execution, from installation to booting up the OS. Like VMware, VirtualBox offers two installation methods: PXE and using a media device. Both methods follow similar installation steps.

While other virtualization software options are available, VMWare and VirtualBox have stood the test of time and continue to evolve, providing the best user experience. It is recommended to use one of these two options. For further steps on installing virtualization software, we will be using a virtual box.

Installing the Virtual Machine

Let’s start by installing VirtualBox on the local machine for demonstration purposes. The installation steps are similar in VMWare as well.

Follow the steps below to install VirtualBox.

Download the VirtualBox by visiting the official website and download the binary for Windows hosts since we use a Windows machine.

After downloading the Windows binary, follow the installation steps. During the installation, allocate memory for macOS to run smoothly later and click on Next.

Once the installation is complete, you will be prompted to finish the installation by clicking on the Finish button.

Great! Now that you have successfully installed the virtualization software on your local machine, it’s time to install macOS in VirtualBox.

Installing macOS in VirtualBox

After successfully installing VirtualBox on your local system, the next step is to install macOS. To do this, you’ll need to download an ISO image of macOS from the Internet. However, Apple doesn’t provide ISO images of its operating system, so you must search for a download link.

For this demonstration, we’ll use the Internet Archive, which provides authentic images. Below are the steps to install Internet Archive to achieve ISO images.

Navigate to the website and select ISO IMAGE on the macOS ISO download page:

Select current available ISO images of different macOS versions from the dropdown option.

Open the VirtualBox and click New to initiate a new guest operating system installation process:

Configure the options by providing the path where VirtualBox is stored. In the ISO Image section, select the BigSur ISO image downloaded in the previous steps and “Type” as Microsoft Windows.

Select the hardware usage and click the Next button.

A minimum of 4GB RAM and 2 CPU cores are required for macOS. The user should allocate more memory for better performance from the guest OS.

Lastly, allocate the desired amount of hard drive space for running macOS and click the Next to proceed.

Finally, click Finish to install Big Sur on Windows using VirtualBox.

Great! Now that we’ve completed both the steps of installing virtualization software and macOS and an iOS image, let’s install Xcode on VirtualBox on macOS.

Downloading Xcode in Virtual macOS

Xcode is an IDE available on Apple’s official software marketplace, the App Store. You cannot download any software from this store without an official Apple ID. Hence, the first step is to create an Apple ID to access the store.

Below are the steps to be followed once you have created the Apple ID to access the store.

Access the App Store and search for Xcode in the search box. Click on GET beside Xcode to download the software:

Next, you need command-line tools to facilitate the development process and help create an environment for iOS app development. These tools will be used during development.

Run the following command on the Terminal to install command line tools:
xcode-select --install

This method allows for the development and testing of iOS applications using Xcode. To deploy applications, users need a developer account with Apple. Testers can access Apple’s simulators through this guest operating system, although latency can be expected.

This approach, one of the oldest for building and testing iOS apps on Windows using Xcode, highlights how virtualization has expanded beyond development to include activities like gaming. This expansion is supported by the increased primary and secondary memory capacity in modern systems.

However, the method for developing apps through virtualization has remained unchanged and hasn’t become more convenient or efficient over the past decade.

Even with these advancements, the effectiveness of iOS app development on a physical Mac cannot be matched. Therefore, a more effective solution may be transitioning from local systems to cloud platforms, reducing resource consumption and eliminating memory-sharing overheads.

Rent a Mac To Build an iOS Application

Renting a Mac to develop macOS or iOS apps has become more cost-effective with modern cloud computing. Services like MacStadium, MacinCloud, and XcodeClub offer Mac OS X virtual machines that can be rented by the hour. These virtual machines can be quickly set up and destroyed, ensuring no sensitive data is left behind. It’s important to sign up for an Apple account and ensure software like Xcode is installed on the virtual machine before starting development. Once rented, the Mac can be accessed using RDP or a VNC client, and users can log in to the Mac OS X desktop to begin development.

Hackintosh

A method that Windows users can use to build iOS applications using Xcode is called Hackintoshing. The term “Hackintosh” has been used by macOS enthusiasts aiming to run macOS on non-Apple hardware since the 1980s. However, earlier attempts involved complex technical tweaks and were often unsuccessful.

In 2005, Apple made a significant change by transitioning its OS system to Intel’s x86–64 architecture from PowerPC. This change made running macOS on a PC much easier, as the OS was now compatible with the same architecture used by other operating systems like Windows. This transition led to an increase in the number of ready-to-install macOS binaries available in the market, resulting in a surge in downloads. This process of running macOS on non-Apple hardware is commonly referred to as “Hackintosh,” essentially meaning “hacking the Macintosh.”

It is true that Xcode for Windows is not available and is exclusively for macOS. However, it is possible to install macOS on a laptop, effectively creating an unlicensed version of a Macintosh, which allows for continuing the development journey. The downside of this method is that the user loses their Windows operating system entirely, as macOS becomes the primary operating system. This approach is similar to virtualization, but instead of running a guest operating system, macOS becomes the primary OS.

Despite losing Windows, this method offers the advantage of being able to build iOS apps and Android apps using the same system by switching between operating systems. It is a cost-efficient solution, and the process is relatively straightforward.

Cross-Platform Development

Cross-platform development allows developers to write code once and build applications for both Android and iOS from the same codebase. Flutter is a framework designed for efficient cross-platform development with low memory usage. However, it’s important to note that while cross-platform frameworks like Flutter can be used to build iOS applications, certain tasks still require Xcode. Currently, Xcode for Windows is unavailable.

React Native is another popular choice among developers for mobile app development. Choosing the right framework for building mobile apps is crucial, and developers often compare Flutter vs React Native to determine the best fit for their project.

To learn more about Flutter and how to perform testing using Flutter for both Android and iOS applications, follow a detailed guide on Flutter testing to validate the working of your apps.

While Xcode provides testing capabilities, using it on a Windows PC can be challenging, especially when sharing resources or using virtual machines. Some testing features, such as parallel testing, running automation code, and recording testing sessions, may not be available.
This limitation can frustrate projects with large, complex applications requiring thorough testing.

To address these challenges, developers can leverage cloud services to speed up testing without changing their operating system. By using cloud-based testing services, developers can access a wide range of testing capabilities and resources, improving efficiency and streamlining the testing process.

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How To Test iOS Apps Built Using Xcode for Windows?

Xcode has a few tools to test iOS applications within the macOS environment. However, these tools are designed to work best on a Mac machine. A reliable solution to use Xcode for Windows is to use a cloud-based testing platform, which offers speed, efficiency, and cost-effectiveness.

One such platform is LambdaTest; it is a great solution for cross-platform and cross-browser testing. It is an AI-powered test execution platform that lets you conduct manual and automated mobile testing on a virtual macOS online environment across a wide range of real devices, 3000+ browsers, and OS combinations, ensuring device and browser compatibility across different platforms.

With LambdaTest, you can perform Android automation and iOS app testing on a real device in the cloud. It also allows you to use emulators or simulators for mobile app testing.

Since LambdaTest is a cloud-based platform, users do not need to install anything on their local system. iOS apps developed using Xcode or other tools can be directly uploaded to the LambdaTest platform using the Real Device Testing feature.

Users can upload their .apk or .ipa files, and once uploaded, these apps will be installed and can be operated on the selected iOS or Android devices. This process eliminates the need to visit the App Store for testing purposes.

Apart from these, there are other benefits that LambdaTest offers that will help you perform iOS or Android testing thoroughly.

Device Support: It lets you conduct Android and iOS app testing using the more popular mobile automation testing tools such as Appium, Espresso, and XCUIT.
Network Throttling: It lets you simulate different network conditions, such as 3G, 4G, and WiFi, to test your app’s performance under varying network speeds.
Geo-location Testing: It lets you conduct geolocation testing to help you simulate different geographic locations to test your mobile app under various locations.
Multiple Installation Support: The users can install multiple applications in a single session on LambdaTest, providing convenience and saving the time to uninstall and reinstall the apps.
Intelligent UI Inspector: It offers an intelligent UI inspector that helps identify elements and provides device logs to aid in debugging the application, all with a single click. This feature is a frequent action in testing and saves a significant amount of time.

To learn how to perform app automation on a real device, watch the video tutorial below and get familiar with the features of LamdbaTest that will help you perform automation testing.

To get started with LambdaTest, you need to follow the steps.

Sign up for a LambdaTest.
Go to the Real Time > App Testing > Virtual Mobile from the menu on the left-hand side.

Select any operating system of your choice. For demonstration purposes, we will use iOS as the operating system and upload the .ipa file to the cloud.

Select your mobile device and model after uploading your .ipa file. We will select the iPhone as the device and the iPhone 15 Pro Max as the mobile device with this configuration for demonstration purposes and click the Start button.

A virtual device will be launched in a cloud environment based on your chosen configuration and the uploaded app.

Using the left menu options, you can perform manual testing on the mobile app, including changing keyboard language, adjusting device orientation, activating sleep mode, and adjusting volume levels via the Device Controls menu. You can record your testing sessions and share them by selecting Record Session. Additionally, you can test native mobile apps from different geographical locations using the IP Geolocation option.

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Conclusion

Xcode is one of the best tools available for iOS app development today. Apple has ensured that it works according to the developer, consumes fewer resources, and makes the work easier to execute. Unfortunately, Apple doesn’t want it shared with users working on a different operating system for several reasons discussed in this post. Due to this, a user with a Windows system is left only with the option to buy an Apple device or install macOS to use Xcode. This post on Xcode for Windows tries to explore these methods in simple steps with a demonstration.

From installing a virtual machine to deleting their Windows OS files, users can choose the method that suits them best and works for the team. All the methods are free to use and don’t require any purchase of physical or digital assets. Also, once you are done with development, the testing becomes much easier with cloud tools like LambdaTest, which are made specifically for this purpose. They provide additional testing tools, support for automation frameworks, third-party integrations, and real Apple devices to test on. Combining these methods with these testing tools results in a high-quality application that demands lower maintenance. Ultimately, this is the combination that all the organizations aspire for.