DEV Community: Joshua Jackson

10 Leading Regression Testing Tools of 2022

Joshua Jackson — Thu, 13 Oct 2022 20:26:04 +0000

When it comes to software products, code changes are inevitable. Customer requirements are highly dynamic, which requires the software to evolve according to the trend. Regression testing ensures that an application's functionality works as expected despite a change or a new build. But its effectiveness highly depends on using the right tools for regression testing.

The best set of regression testing tools prevents modifications from causing a diversion from the expected usage and functionality of the application. Regression testing validates and verifies changes in code.

Manual regression testing hogs up a lot of time and turns out to be costly. But when you automate the regression test suite, it reduces the time required to complete tests and facilitates the parallel running of multiple tests. Choosing the right tools for regression testing can be daunting, considering the available options.

In this post, we will look at the leading regression tools that facilitate the quick execution of tests and save a lot of time. Let's check them out.

1. Selenium

Selenium has always been an all-time favorite automation Testing tool. It is known to perform flawless regression testing over various platforms and browsers. Selenium has a category of tools that cover different aspects of testing.

Features:

Selenium is highly compatible with other software testing frameworks and different programming languages.
It offers web page navigation, proper usage of web elements, and high flexibility.
Selenium enables easy debugging, thanks to features such as hitting pause on exceptions and setting breakpoints.

2. HeadSpin

Headspin is one of the leading regression testing tools that facilitate testing of both web and mobile applications using intelligent test automation. It offers product monitoring and enhancement insights and accelerates product development.

Features:

The AI-powered regression intelligence offers build-over-build regression and seamless integration with your CI / CD processes.
It enables the comparison of UX KPIs 100 + locations across various real devices.
It offers a user-friendly interface that allows users to compare different aggregate metrics across devices, locations smoothly, and builds.

3. Testimony

The brainchild of Basis Technologies, Testimony has been specifically engineered for SAP software. It eliminates the requirement for managing test data and creating and maintaining test scripts, thus, re-inventing SAP regression testing. After configuration is complete, its high-end robotic automation testing technology makes and updates the regression testing library. This helps testers complete month-long streaks of tasks.

Features:

Testimony enables faster running of regression tests.
Thanks to the left shifting of regression testing, Testimony enhances development efficiency.
It carries out automatic creation, execution, and update of the test library.

4. TestComplete

TestComplete is one of the leading names in the automated regression testing arena. It allows users to quickly create and easily maintain regression tests across different desktop, mobile, and web applications.

Features:

TestComplete offers support for database testing and object name mapping.
It easily integrates with other toolsets.
Test complete enables keyword-driven, data-driven, and object-driven testing.
You can record tests and review them later.

5. Ranorex

If you are looking for one of the most robust automated regression tools, Ranorex has been a popular choice for a long time. It has C# and VB.NET as its programming languages and supports multiple applications, including Flex, Winforms, SAP, JAVA, WPF, Flash, HTML5, and iOS.

Features:

Ranorex edits user actions and replaces users with the help of features like replay editor and object-based capture.
Its test recorder promotes the reusability of steps across different test cases.
Testers get highly customizable test reports, and they can enhance a test run with video reporting.

6. Watir

Watir is an abbreviation for Web Application Testing in Ruby. As the name suggests, Ruby is the primary programming language with this tool. Watir has been the leading choice of big names, including Facebook and Oracle, with its main intention to test web applications.

Features:

Watir boasts exceptional browser interaction capabilities.
It promotes the designing of maintainable, readable, compliant, and simple automated tests.
This technology-independent tool also offers cross-platform operating system support.

7. Katalon Studio

Katalon Studio is a lightweight regression testing tool that offers support for end-to-end testing of desktop, mobile, API, and web applications. Built on Appium and Selenium, this automated testing tool features full recording and spying functionalities.

Features:

Katalon Studio seamlessly integrates with CI/CD tools such as Jenkins, Jira, CircleCI, Selenium Grid, Bamboo, etc.
The support community spreads worldwide.
It offers support for data-driven, keyword-driven, TDD, and BDD testing.

8. TestingWhiz

If you’re looking for a codeless regression testing tool, Testing Whiz is quite the buzz in the testing world. It features more than 290 inbuilt commands, thus, enabling quick automation of test cases.

Features:

TestingWhiz offers seamless integration with plenty of popular tools for tracking bugs as well as test management tools.
It offers support for multiple browsers and mobile testing.
TestingWhiz features distributed test execution.

9. Experitest

Experitest is one of the leading regression testing tools known for performing tests on different web apps across 1000+ devices. For better results, most testers integrate it with Selenium or Appium.

Features:

Experitest can parallelly run 100+ tests at once.
You can perform visual testing to find out how the UI fares on varying screen resolutions.

10. Test IQ

The core aim of Test IQ is to help run your application as smoothly as possible on varying combinations of operating systems, devices, and browsers. It tests apps in real-world conditions that immediately expose loose ends to fix.

Features:

It gathers honest user feedback to improve the quality of the product.
The release time is faster with Test IQ as compared to other tools.

Summing It Up

The best way to choose a regression testing tool is to analyze your company's requirements carefully. There isn't a one-size-fits-all approach in this case. You need to take your team's comfort, programming languages, the type of software product, and frameworks into account before choosing a regression testing tool.

Once you have chosen the right tool, identifying discrepancies between original code and new changes becomes a cakewalk. It's advisable to select an all-in-one scalable solution appropriate for small and large testing teams.

The Advantages And Shortcomings Of Mobile-Based Testing

Joshua Jackson — Wed, 21 Sep 2022 15:59:42 +0000

Current technology and its frequent innovations have rapidly altered the digital landscape. Most of our everyday tasks are dependent on our devices, specifically the applications. Apps are software designed for use on various gadgets. Compared to integrated software systems on PC, mobile applications often provide different functions. Chat applications and social networking apps were the most popular app categories globally in the third quarter of 2020, with 91% and 88% usage reach, respectively. You need to be aware of the updates for which real-device testing is essential. Different devices have different utilities- making it slow. Model-based testing tools and techniques help to ensure the functionalities within the minimum run time.

Model-based testing is a software testing approach that compares the run-time behavior of the software under test to predictions generated by a model. A model is a description of the behavior of a system. Input sequences, actions, conditions, output, and data flow from input to output can represent behavior. It should be practical to grasp and reusable; sharing must provide a detailed description of the system under test.

Most popular applications globally by the 3rd quarter of 2020

Types Of Mobile-Based Testing

Model-based testing frameworks can be classified into two categories.

Offline / a priori: Create test suites, a grouping of test cases, before running them.

Online / on-the-fly: Test suite generation during test execution

Different Models In N Testing

There are multiple models available that describe various elements of system behavior. The following are some examples of the model:

Control Flow
Dependency of Graphs
Data Flow
Decision Tables and
State Transition machines

Finite State Machines

This model assists testers in determining the outcome based on the input chosen. Several input combinations can result in a corresponding system state.

The system will have a specific and present state that will be regulated by a set of inputs provided by the testers.

Consider the following example:

A mechanism in place allows the staff to access the application. The employee’s present status is “out”; it will change to “in” once they sign into the system. An employee in the “in” status can read, print, and scan documents in the system.

State Charts

Statecharts are finite state machine extensions utilized for sophisticated and real-time systems. These have a predetermined number of states. The system’s activity is studied and represented as events for each state.

As an example —

Defects are marked as new in the defect management tool. The status is set to fix once developers have corrected it. The quality is changed to re-open unless it is rectified. The statechart has a structure to ensure each state has its event.

Unified Modeling Language (UML) is a general-purpose modeling language standardized. UML contains graphic notation tools for creating visual models that may represent exceedingly complex system behavior.

Notations in UML include:

Activities
Actors
Components of the Business Process
Language of programming

Every model that enhances efficiency has its cons.

Challenges Of Mobile-Based Testing

The deployment of model-based testing in any company necessitates significant expenditure and work. Testers must have the relevant skills.

The learning curve duration will be longer due to difficulty comprehending the model itself.

As an application grows in size in terms of lines of code or complexity, mobile-based testing tools become more efficient. If tests are not conducted in-house as additional lines of code are added to the source code, this will be worrisome. As more lines of code are added, the likelihood of bugs or possible security problems entering the program increases, hampering your mobile-based testing techniques.

Below we have listed some disadvantages of model-based testing:

It facilitates the formation of teams of trained testers.
The overall testing cost for the project will rise, but this expense is mitigated as the product grows.
When adopting model-based testing techniques, there is a steep learning curve.
Model-based testing can be rather complicated to comprehend at first.
Teams who are just getting started may wish to work with testing professionals who can explain the model-based testing tools to developers and assist in the implementation that will work best for you.
While hiring these specialists may cost a little more money upfront, it will save you money in the long run.
High coverage and minimal maintenance costs exhibit an excellent option for enterprises seeking the highest degree of testing coverage available. Model-based testing will necessitate the presence of qualified testers within the company.

However, you cannot overlook the progress made by model-based testing.

Benefits Of Mobile-Based Testing

Despite the challenges, mobile-based testing has its share of advantages. It provides easy test case maintenance at low cost and early defect detection.

Following are the benefits of conducting model-based testing:

The initial implementation of many test cases is time-consuming but is much easier to maintain.
While testing automation, the expenses of conducting many tests reduce. The worldwide automation industry is forecast to expand significantly, notably in 3D printing, artificial intelligence, and drones, which are estimated to almost double in global revenue over this time frame. Most contemporary industries rely heavily on testing automation. By 2021, the automation industry will be worth more than 83 billion US dollars.
Tests can be conducted on several workstations or servers to see how the underlying system reacts to the various tests.
Defects in a system or a product find quick identification.
Projects are smoother and more efficient to carry out.
Customer service gets better due to less time consumption.
When model-based testing is used, developers testing multiple methodologies will discover that their job satisfaction is immense.

When adopting any testing procedure, it is critical to recognize that the initial resources invested in the testing might be enormous. These resources can be time-consuming, but the convenience of testing automation will considerably outweigh the effort invested in model-based testing.

Difficulties will be addressed immediately during the development cycle so that there is no risk of the product reaching the market with ongoing issues that degrade the user experience.

Conclusion

Software businesses have adopted various testing techniques around the globe. Microsoft has been employing model-based testing techniques for years. It finds ready usage in mobile applications and other sorts of development in the current world.

These tests are carried out in addition to the manual mobile app testing services that many teams utilize.

A model enables developers and their teams to understand system behavior during testing. It is a simple validation in both software and hardware testing. The company must understand the benefits of online mobile testing systems to avoid confusion during the process.

End-to-End testing: Everything you need to know!

Joshua Jackson — Mon, 19 Sep 2022 14:06:14 +0000

There are numerous approaches to software testing, and end-to-end testing is one of them. Although it requires the most time and resources, this process can be automated.

In this article, we explain what end-to-end test automation is and how it fits into a larger testing plan that may benefit any business.

We’ll start with the fundamentals, going over the “what” and “why” of end-to-end testing. After that, we’ll discuss the importance of end-to-end testing in a thorough testing approach.

You’ll see that the advantages of test automation extend far beyond time savings. We believe in test automation, even though manual testing has its place—and end-to-end testing can be done manually. As a result, you’ll also learn about the importance of automation in modern testing strategies.

Before we part ways, we speak about how to tell the difference between end-to-end testing and other types of testing.

What do you understand by end-to-end testing?

End-to-end testing (E2E testing) is an app testing method that examines an application’s workflow from start to finish. This method simulates real-world user scenarios to test the system’s integration and data integrity.

The test goes through every activity the application may perform to see how it interacts with hardware, network connectivity, external dependencies, databases, and other apps. End-to-end testing is often performed after functional and system testing.

Steps for End-to-End Testing:

To start and finish any E2E test, follow the procedures below:

Examine the needs. Have a good understanding of how the app should function in every way.
Create a test environment that meets all of the requirements.
Examine the hardware and software requirements.
Make a list of how each system should react.
Make a list of the testing methods you’ll need to evaluate these responses. Include precise details of the standards to be followed in each test (language and tools.).
Create test cases
Run tests, analyze the results, and save them.

Misconceptions related to End-to-End testing

End-to-end testing should not be confused with user interface testing. While they may have some similarities, UI testing can be considered a unit or integration testing because each UI piece can be tested separately. On the other hand, end-to-end test automation necessitates testing the complete flow. In addition, UI testing focuses on whether the user interface appears and behaves as intended, whereas end-to-end testing focuses on whether the underlying system functions effectively.

However, UI and end-to-end testing frequently overlap. For example, when testing an app’s login flow, you might check that the login fields display the relevant keyboard and the login works. Put another way- you can add UI tests to your end-to-end tests if you are very careful and explicit about it.

End-to-end tests are also ineffective for evaluating specific features. This is because they violated numerous testing fundamentals. Because they involve interaction with the entire system, they usually are pretty slow to run. They take a long time to get started because the whole system must be developed first, making it difficult to follow the adage “fail quickly.” They can’t isolate a bug; in most cases, all you’ll know is that something isn’t working. Once a bug is discovered, you’ll have to devote more time and effort to isolate it.

Finally, end-to-end tests are notoriously unreliable since they are susceptible to real-world difficulties that affect your final system, such as network concerns.

What is the need for end-to-end testing?

The software can and should be thoroughly tested. The unit test is the most basic level of testing. This is when programmers create a minor routine to try the one they’re working on. Your application will be made up of all of these minor procedures.

However, programmers will benefit from writing these simple test routines since they will receive immediate feedback on whether or not they are correctly implementing a feature.

While checking that all of the minor bits operate is insufficient. Integration tests are helpful in this situation. Integration tests combine two or more components in a trial and verify the outcome.

However, even if all of these tests pass, you may still have problems or unfulfilled requirements.

First and foremost, unit and integration tests do not cover user interfaces. Is the user interface well designed? Is the experience enjoyable? Are all of the required components in place? Is it possible for the user to achieve their goals? Only an end-to-end test can answer these types of queries.

End-to-end test automation is also crucial since modern software has many moving parts: servers can cause applications to act. Differently, settings must be set up correctly, and other dependencies can influence our program. Separate component testing will not cover everything.

Does this rule out the value of unit and integration tests? Certainly not. Unit, integration and end-to-end tests are critical components of a comprehensive testing approach.

What are the relevant factors for measuring end-to-end testing?

To track the progress of end-to-end tests, consider the following elements:

Test case preparation: Are the appropriate test cases built to test each software function? The graph should depict the rate at which current and prospective test cases are being developed.
Weekly test: It is critical to have a weekly percentage-based test completion report. The relevant parameters here are the test cases that are now running, not running, and have failed. - Details on defects: It’s crucial to know what proportion of defects are detected, closed, or opened each week. It lets testers and management keep track of faults and supervise their resolution by prioritizing defects (for explanation). - Test environment availability: This shows how much time is scheduled for testing each day against how much time is spent.

Why is end-to-end testing necessary?

Every program is connected to and integrated with many systems and databases outside its environment. The app’s workflow is convoluted as a result.

E2E testing evaluates whether an application’s numerous dependencies are functioning correctly. It also examines if reliable data is being transmitted between various system components.

- Backend: End-to-end testing verifies an app’s database and backend layers. This is required because the app’s fundamental functions rely on backend capabilities.
- Multi-tier system:If an application has a complicated design with numerous tiers, E2E testing is necessary to ensure overall functionality and interaction between particular levels.
- Distributed Environment: E2E testing is required in a distributed setting, such as an SOA (service-oriented architecture) or cloud environment. It’s also necessary for apps with several components to interact together to function correctly.
- Consistent User Experience:E2E testing ensures that the software provides a consistent user experience across numerous devices, platforms, and environments because it involves the front end. E2E testing, for example, includes cross-browser compatibility testing.

What are the challenges in End-to-End Testing?

Detecting flaws in a complicated workflow is naturally difficult. The most important ones are listed below:

- Creating workflows:Test cases in an E2E test suite must be executed in a specific order to investigate an app’s workflow. This sequence must correspond to the end-journey user’s journey through the app. Creating test suites to meet this procedure can be time-consuming, especially when thousands of tests must be completed and executed.
- Accessing the Test Environment:Testing programs in development environments is simple. On the other hand, every application must be tested in client or production settings. Prod environments are unlikely to be available for testing at all times. Testers must install local agents and log into virtual computers even when they are. Testers must also anticipate and avoid difficulties such as system changes that could disrupt test execution. Testing on an actual device cloud is the best method to get a perfect test environment.
- Test environment availability:This shows how much time is scheduled for testing each day against how much time is spent.

End-to-end testing: Best Practices

1) Prioritize the result:

Test as if you were the user when generating test cases. Are the characteristics identified? Is it possible for people to achieve what they want? Acceptance test papers and user stories can assist in clarifying the user’s perspective. Create test cases that reflect this. Focus on end-to-end tests on app functionalities that will create the most problems if they fail. Begin with these features and build more complex test cases to validate them. For this, consider employing a risk assessment matrix. Read this to gain a better understanding of risk-based testing.

2) Exception testing should be avoided:

An end-to-end testing framework is best for testing frequent user scenarios. Platforms like HeadSpin use integration testing or low-level unit testing to test exceptional use cases.

3) Maintain Order:

Since end-to-end testing frameworks cover the entire application, test cases will inevitably be complicated. Each system component must be tested, increasing the number of potential failure spots and the difficulty of diagnosing each anomaly. In E2E testing, structure and organization are critical. Do unit and integration tests first to resolve the first level of issues.

4) Improve the setup and teardown processes:

Ensure that the test environment is prepared to begin testing. The setup process should be as minimal as feasible. When the tests are finished, it should take an equivalent amount of time to wipe the test data, restore the environment to its original condition, and make it available to rerun tests.

Takeaway

This article attempts to explain end-to-end testing and why it is required. Other tests, such as unit and integration tests, accompany end-to-end testing. It is part of a more comprehensive testing approach to help every company. This is particularly true if your end-to-end tests are automated.

To sum-up:

We learned about end-to-end testing.
We did burst some misconceptions related to end-to-end testing.
We understood the need for end-to-end testing.
We also learned about the main challenges faced in end-to-end testing.