DEV Community: Shubham Joshi

How Armtec Streamlined Technical Translation for the Infrastructure Industry with Pairaphrase

Shubham Joshi — Thu, 26 Mar 2026 07:24:12 +0000

As infrastructure companies expand across regions, accurate multilingual communication becomes critical for maintaining operational efficiency and meeting regulatory requirements.

Armtec — a national manufacturer of infrastructure products and engineered construction solutions — faced increasing translation complexity as its operations scaled. By implementing Pairaphrase, the company modernized its translation workflow, reduced costs, and improved collaboration across distributed teams.

About Armtec

Armtec serves multiple industrial sectors, including:

Transportation
Public works
Forestry
Oil and gas
Mining

The company develops steel and high-density polyethylene (HDPE) infrastructure solutions such as:

Drainage systems
Bridges
Retaining walls
Stormwater management products
Erosion control systems

After its acquisition by WGI Westman Group in 2018, Armtec expanded nationwide operations. This growth significantly increased demand for localized technical documentation, marketing materials, and internal communications — particularly for French-speaking markets.

The Challenge: Rising Costs and Workflow Complexity

As translation requirements increased, traditional workflows became difficult to sustain.

While external translation vendors delivered acceptable quality, they introduced several challenges:

High and escalating translation costs
Slow turnaround times
Workflow bottlenecks
Difficulty managing technical formatting
Limited scalability across departments

Armtec needed a solution that could:

Requirement	Goal
Multi-user access	Support teams across locations
Technical accuracy	Handle engineering documentation
File compatibility	Preserve formatting across formats
Faster delivery	Meet tight project timelines
Cost control	Reduce reliance on external vendors

Existing processes slowed communication and affected project efficiency.

The Solution: Implementing Pairaphrase

Armtec adopted Pairaphrase, an AI-powered translation management platform designed for secure, high-volume document translation.

The platform enabled seamless translation of DOCX and IDML files without breaking formatting — a critical requirement for technical documentation.

Key Capabilities

Support for 140+ languages
Translation across 25+ document formats
Automated translation workflows
Translation memory for consistency
Secure handling of proprietary content
Real-time collaboration across teams

With centralized workflows and automation, employees across departments could manage translation tasks efficiently using a lean internal team.

Measurable Results

After implementation, Armtec reported significant operational improvements:

Metric	Result
Annual savings	$39,072
Cost per word	Reduced from $0.16 → $0.012
Monthly translation volume	22,000 words
Active users	5-person internal team
Delivery speed	Faster turnaround without formatting issues

Teams were able to produce high-quality French translations quickly while minimizing manual intervention.

Business Impact and Operational Efficiency

Beyond cost savings, the updated workflow improved collaboration and internal communication.

Key operational benefits included:

Faster translation of technical documents
Preserved formatting and engineering accuracy
Reduced administrative overhead
Improved coordination between departments
Greater scalability for nationwide operations

In infrastructure and engineering environments, where documentation precision is essential, maintaining formatting consistency proved especially valuable.

Conclusion

Armtec’s experience demonstrates how AI-driven translation management can modernize communication workflows in technical industries.

By adopting Pairaphrase, the company achieved:

Scalable multilingual communication
Significant cost reductions
Faster project delivery
Improved collaboration across teams

As organizations expand into multilingual markets, intelligent translation platforms are becoming essential tools for operational efficiency, localization, and sustainable growth.

For more details, readers may refer to Pairaphrase

A Winning Test Automation Strategy

Shubham Joshi — Wed, 21 Jan 2026 19:50:25 +0000

You already know that automation in software testing is crucial. So the real question isn’t “Should we automate?” It’s actually “How do we do it right?”

Done well, automation promises efficiency, broader coverage, and fewer human errors. But when done poorly, it quickly becomes more of a burden, one that results in flaky tests and unmanageable maintenance that don’t align with actual software testing goals.

Bottom line: a well-thought-out automation strategy helps avoid common pitfalls, like deciding what to automate, when to automate, and how to integrate automation into the development processes in a way that drives tangible value.

In this blog post, we’ll discuss key elements of creating a winning test automation strategy.

But first, let’s discuss the basics.

What is a Test Automation Strategy?

It’s a structured plan that defines what, when, and how to automate testing within a Software Development Life Cycle (SDLC). At its core, a test automation strategy covers:

Defining automation scope and objectives
Choosing the right toolkit based on app architecture and team expertise
Setting up test environments and managing test data
Establishing processes for updating and analyzing tests over time

Why is a Test Automation Strategy Important?

Software testing can quickly become unpredictable and inconsistent without a clear automation testing strategy.

For example:

You may constantly switch tools or rewrite tests, wasting time and effort
You won’t have a clear understanding of what’s being tested, how often, or why
Without documentation, test automation can be abandoned altogether, as only a few people understand it, but they leave
Different teams may use different tools, that too in an ad hoc way, making it difficult to standardize testing across the organization

Therefore, when you have a test data automation strategy in place, you’re in a better position to be:

1. Consistent

You can apply the same testing standards, tools, and practices across projects. This means test results are reliable and comparable—and don’t cause unnecessary overheads.

2. Efficient

Time and effort are focused on high-value automation, rather than unnecessary duplication. You can simply leverage the existing test scripts instead of writing new ones from scratch.

3. Adaptable

If you plan to bring new test automation tools and practices into the mix, a strategy ensures this transition happens smoothly. It also enables tests to remain scalable over time.

Components of a Test Automation Strategy

What are the core building blocks of an automated testing strategy?

Let’s find out.

1. Knowing what to automate and what not to

Not everything needs to be automated. And trying to automate everything is a common mistake. Think about it this way: if a test is highly repetitive, time-consuming, and expensive, automation makes sense.

But if the success and accuracy of a test rely on human intuition or involve exploratory work, manual testing will be a better fit.

Let’s review some great candidates for automation:

Regression tests that run every release
Load and performance tests that simulate real-world usage
Tests that require multiple data sets (e.g., form validations)
API and integration tests that check how systems talk to each other

2. Build a test environment you can trust

Even the best-written scripts can fail for the wrong reasons if the test environment isn’t stable or inconsistent. A dependency can go missing, the browser version can change, or the test data can get corrupted; anything is possible.

You don’t want your tests to pass one day and fail the next, especially when nothing has changed, right? Imagine spending hours debugging “false positives!” Here’s how to build a test environment that stands the test of time:

Keeping test data stable to prevent false failures
Standardizing browsers, devices, OS versions, and configurations
Deciding if you’ll run tests on-premise, in the cloud, or as a hybrid setup
Running tests in a CI/CD pipeline so they trigger automatically with every code change

3. Choose the right test automation framework
Such frameworks provide a set of guidelines, tools, and libraries that help create, execute, and manage automated tests for software apps, essentially acting as a foundation for building automated test scripts.

These testing frameworks define rules for test organization, coding standards, data handling, and execution mechanisms. Choose the wrong framework and you can risk spending more time fixing flaky tests than actually writing reusable, scalable, and maintainable tests.

So how do you pick the right test automation framework? Here are key factors to watch out for:

Integrates smoothly into CI/CD pipelines
Works well with your existing tech stack
Supports parallel execution (faster test runs)
Generates clear reports so failures are easy to debug

Test automation tool examples:

Unit testing: JUnit, TestNG, NUnit
API testing: Postman, REST Assured
GUI testing: Selenium, Cypress, Playwright
Behavior-Driven Development (BDD) testing: Cucumber, SpecFlow, Robot Framework

4. Think about your test data seriously
Ever seen tests fail because someone accidentally deleted or changed a piece of test data? Or worse, tests that pass even though the data isn’t right? Your test automation planning can’t be reliable if your data isn’t. This is a fact.

Automate test data setup and cleanup so you’re never working with stale or missing data sets
Use data-driven testing to cover multiple scenarios without writing duplicate tests
Store test data in a version-controlled system to prevent inconsistencies
Mask or anonymize data to meet compliance and security requirements

Top Challenges in Test Automation and How to Avoid Them

Let’s explore the key reasons that can make automation unsuccessful:

1. Trying to automate everything

It sounds ideal in theory. However, in reality, some tests don’t provide enough value to justify being automated. For instance, some tests demand frequent updates or depend on a constantly changing UI. Maintaining them can become cumbersome.

Solution: Instead of automating every test case, identify ones that are stable, repetitive, and provide high ROI.

2. Neglecting test maintenance

Just like software, automated tests need to be regularly updated. If that doesn’t happen, they start failing for reasons unrelated to actual bugs. Fixing them can be a massive waste of time, not to forget, costly.

Solution: Build test maintenance in your workflow and make it a point to review and update test scripts as the app evolves.

3. Having a poor test data strategy

If your tests rely on hard-coded or inconsistent data, they’ll fail unpredictably, resulting in false positives and frustration.

Solution: Invest in dynamic test data management. Use parameterized tests, external data sources, and database screenshots to ensure your automated tests always have reliable and realistic inputs.

4. Ignoring integration with CI/CD pipelines

If your automated tests aren’t running as part of your deployment process, you miss out on one of the biggest USPs of automation: quick feedback.

Solution: When tests are integrated into your CI/CD pipelines, you can catch defects early, ensure smooth deployments, and prevent regressions before they reach production.

5. Overlooking test flakiness
If your tests fail intermittently due to unreliable locators, timing issues, or unstable environments, they can erode the confidence in your automation suite. You could perhaps start ignoring failures, thinking they’re false positives. This defeats the purpose of automation.

Solution: Treat all flaky tests as a priority. Identify and fix the root cause instead of re-running tests, hoping they’d pass.

Best Practices for an Effective Test Automation Strategy

Let’s break down what it takes to make test automation work in the real world and all the tips you need to remember:

1. Start automation early

Too many teams wait until the end of the development cycle to think about automation. By that time, it’s either too late to catch critical defects or there’s too much technical debt to automate efficiently. The best solution is to integrate automation from day one.

This involves:

Writing automated tests in parallel with development instead of treating them as a separate task
Planning automation alongside feature development no more accumulation of a backlog of untested code
Shifting left, which means automating unit and integration tests so defects are caught before they reach later stages
Make testing a natural, continuous feedback loop rather than a bottleneck.

2. Automate the right tests

We’ve discussed this before: you shouldn’t automate everything, especially the tests that are unstable and have fast-changing features.

The best test strategies are selective and focus on tests that bring the most value while leaving exploratory and frequently changing tests to manual execution.

Typically, a good automation candidate is:

Repetitive (something you run often)
Time-consuming (manual execution would slow you down)
Critical (a failure here would impact business users or customers)
Stable (frequent UI or functionality changes make tests harder to maintain)

3. Define clear goals and metrics for automation

Having a test automation strategy isn’t a box-checking exercise. It has to help your software testing initiatives and derive great value. Ask yourself: what does successful automation look like to you? To answer that, review your business goals.

If your objective is faster releases, your automation KPIs should focus on test execution time (are tests running fast enough to fit into your CI/CD pipeline?) and defect detection speed.

If it’s improving software quality, analyze test coverage (how much of your app is covered by automated tests?) and failure response rates.

4. Make automation a team effort

Automation isn’t one person or team’s responsibility. Developers, testers, product managers, and even end users need to a part of the process. Involving all stakeholders ensures the app’s overall performance is in sync with your automation efforts.

For example, in the case of a mobile banking app, developers can offer insights into the technical feasibility of automation approaches, while end users can provide feedback on usability aspects that should be automated for a better user experience.

Plus, when automation is baked into the development process, it scales better and doesn’t get abandoned when things get busy.

5. Follow the test pyramid

To create a balanced test strategy, follow the test pyramid principle, which emphasizes a higher proportion of unit tests at the base, followed by integration tests, and fewer UI and end-to-end tests at the top.

This structure optimizes test coverage while minimizing execution time and maintenance efforts.

Unit tests form the foundation, validating individual components in isolation and providing rapid feedback on code correctness
Integration tests ensure seamless interaction between different modules, verifying that components work together as expected
UI tests simulate real user interactions, assessing end-to-end functionality but requiring fewer tests due to their higher complexity and maintenance costs.

Source: For more details, refer to TestGrid.

Industry’s First AI Powered Test Automation

Shubham Joshi — Tue, 20 Jan 2026 18:30:46 +0000

Using TestGrid AI based testing, users can write test cases in English, BDD and CSV and perform scriptless automation.

Atlanta, United States, June 20, 2023. TestGrid, a leading end-to-end automation cloud and on-premise testing solution, is proud to unveil the industry’s first AI-powered test automation platform. With TestGrid’s breakthrough AI technology, users can effortlessly create test cases in English, BDD, and CSV formats, enabling scriptless automation on a combination of 1000+ real devices, browsers & OS

In today’s dynamic digital landscape, the success or failure of websites and mobile apps hinges on their user experience. This puts immense pressure on businesses to ensure thorough and effective testing. However, with the constant evolution of software, maintaining up-to-date test cases can be tedious, time-consuming, and often requires extensive manual intervention. This not only increases costs but also delays time to market. Moreover, current automated testing solutions often yield brittle tests that fail at the slightest change in the UI.

Introduction

At TestGrid, we recognize these challenges and have developed an innovative solution.

Our AI Powered Test Automation case creation streamlines end-to-end testing, significantly reducing the degree of manual involvement and the brittleness of tests. With TestGrid, organizations can save up to 60% of testing time, cut costs by 50%, and greatly accelerate their time to market.

TestGrid customers can now simply paste, click, and automate their test cases in English, BDD, or CSV formats through our intuitive AI portal. By leveraging this groundbreaking new technology, test scenarios are transformed into seamless automation steps that can be executed across a vast range of real devices, browsers, and operating systems on cloud or on-premise.

During the launch Harry Rao, CEO TestGrid said “To create this powerful tool, we’ve trained our AI model on a vast corpus of over 15 million test steps and scenarios. We’ve utilized state-of-the-art machine learning algorithms for training our AI model, including transformer-based architectures that are renowned for their efficiency and efficacy in natural language processing tasks.

The training process was carried out on a high-performance computing cluster equipped with high-speed GPUs. This extensive training data has equipped our AI with the ability to understand a wide array of programming constructs and testing scenarios, ensuring that it generates accurate and effective test cases.

This will simplify the testing process across the organization, help them become more efficient, and fast track their go-to market launch”

“Having had the privilege of early access to TestGrid’s AI-Powered Test Automation tool, I must say it’s genuinely transformative. The way it streamlines testing while enhancing precision is remarkable. It’s much more than a time-saving device; it’s about ensuring we’re providing the best possible experience for our users. TestGrid has truly revolutionized our approach to testing.” Said one of TestGrid’s large bank customers.

TestGrid AI Powered Test Automation promises to revolutionize testing processes across organizations, enhancing efficiency, and expediting time to market. By automating repetitive manual testing tasks, teams can save up to 80% of the time typically spent on test case generation and execution. This empowers talented professionals to focus on more intricate and intellectually stimulating challenges, fostering productivity and professional growth.

TestGrid AI Testing is an invite based initiative, people can join the waitlist to try the platform here.

About TestGrid: AI Powered Test Automation

TestGrid is a leading provider of end-to-end automation cloud and on-premise testing solutions. With a focus on simplifying the testing process, TestGrid’s innovative AI-powered technology allows organizations to achieve significant time and cost savings while accelerating their go-to-market strategies.

Endurance Testing: Ensuring Long-Term Stability Under Continuous Load

Shubham Joshi — Thu, 20 Nov 2025 07:21:09 +0000

Endurance Testing is a non-practical kind of programming testing where a product is tried with a high burden stretched out throughout a lot of time. This helps to assess the conduct of programming applications under-supported use. The fundamental reason for this testing is to guarantee that the application is sufficiently able to deal with the expanded burden with no crumbling of reaction time.

This sort of testing is performed at the last phase of the performance run cycle. Endurance testing is a long cycle and now and again goes on for as long as a year. This may incorporate applying outer loads, for example, Internet traffic or client activities. This makes endurance testing contrast from Load Testing, which normally finishes in a few hours or thereabouts.

Did you know endurance testing is also called soak testing?

Endurance implies a limit so as such, you can term Endurance Testing as Capacity Testing.

Objectives of Endurance Testing

The primary objective of Endurance testing is to check for memory spills.
To find how the framework performs under supported use.
To guarantee that after an extensive stretch, the framework reaction time will continue as before or better than at the beginning of the test.
To decide the quantity of clients and additionally exchanges a given framework will support and meet performance objectives.
To deal with the future burdens, we need to see the number of extra assets (like processor limit, plate limit, memory utilization, or organization transmission capacity) are important to help use in future.
This testing is for the most part done by either over-burdening the framework or by diminishing certain framework assets and assessing the results.
It is performed to guarantee that imperfections or memory spills don’t happen after what is viewed as a moderately “typical” utilization period.

What to screen in this Testing

In this Testing following things are tried.

Test memory spillage Checks are done to confirm if there is any memory spillage in the application, which can cause smashing of the framework or O.S.
Test association conclusion between the layer of the framework – If the association between the layers of the framework isn’t shut effectively, it might slow down a few or all modules of the framework.
Test information base association close effectively. If the data set association isn’t shut effectively, may bring about framework crash
System is tried for the reaction season of the framework. This is because the application turns out to be less proficient because of the drawn out utilization of the framework.

Step-by-step instructions to perform this Endurance Testing

The following is the fundamental testing approach for the Endurance Test

Testing Environment – Identify the equipment, programming, working framework needed for the endurance testing, appointing jobs and obligations inside the group, and so on. Prepare the climate before the test execution. You likewise need to appraise normal information base creation size and yearly development. You will need this to test how your application will react following a year, two or five.
Creating the Test Plan, Scenarios based on nature of testing – manual or mechanization or mix of both. Later, test Case configuration, audits, and execution ought to be arranged. Testing to pressure the framework, break point testing, and so on ought to likewise be essential for the test plan. Testing to pressure the framework decides the break point in the application.
Test Estimation – Provide the assessment of what amount of time it will require to finish the testing stage. It ought to be broke down based on various analyzers included and the quantity of test cycles required.
Risk Analysis – Analyzing the danger and making a fitting move for the anticipation. Prioritization of experiments according to the Risk factor and distinguish the underneath hazard and issues analyzer may stage during the endurance test.
Will performance stay reliable after some time?
Are there other minor issues that have not yet been recognized?
Is there outside impedance that was not tended to?
Test Schedule – Determine the spending plan, expectations inside the time spans. As Endurance Testing applies a colossal yet characteristic burden game plan of exchanges to the framework/application for a persistent timeframe.

Example

While Stress testing takes the tried framework as far as possible, this takes the application as far as possible after some time.

For Example, the most intricate issues – memory spills, information base worker use, and inert framework – happen when programming runs for an all-encompassing timeframe. On the off chance that you skirt the endurance tests, your odds of identifying such imperfections preceding arrangement are very low.

Endurance Testing Tools

WebLOAD
LoadComplete
Apache JMeter
LoadRunner
Appvance
LoadUI
OpenSTA
Rational Performance Tester

Benefits of Soak Testing

It helps in deciding how workload the System Under Load can handle.
Provides exact information that client can use to approve or improve their foundation needs.
Identifies performance issues that may happen after a framework has been running at an undeniable level for longer timeframe
Distinguish typical issues in more modestly designated performance tests. This implies guarantees application to stay accessible in any event, when there is a tremendous burden in an exceptionally limited ability to focus.
This test is likewise used to check whether there is any performance corruption after a significant stretch of execution

Weaknesses of Soak Testing

It is regularly difficult to characterize how much pressure merits applying.
This Testing could cause application as well as organizational disappointments. Hence, bringing huge disturbance if the test climate is not disengaged.
Permanent Data misfortune or defilement can happen by over-focusing on the framework.
Resource use stays high after the pressure elimination.
Some application segments neglect to react.
Client can see the unhandled exceptions.

Rundown:

In Software Engineering, Endurance testing is a subset of burden testing.
This is a long interaction and at times keeps going for even as long as a year
Conduct checks to confirm.
Test memory leakage.
Test reaction time.
Test information base association, and so forth.

For more details, readers may also refer to TestGrid.

Concurrency Testing: Ensuring System Stability Under Parallel Use

Shubham Joshi — Tue, 18 Nov 2025 06:27:02 +0000

Concurrency testing (also known as concurrent testing) is a technique used to detect possible defects while multiple users or concurrent users in performance testing scenarios access an application simultaneously. In software quality assurance and concurrency in software engineering, this form of testing plays a crucial role in detecting synchronization issues

Let us understand concurrency testing through an example:

Many of us make use of eCommerce websites such as Amazon to do online shopping. There comes a situation when multiple users log in to the website simultaneously and end up ordering the same product.

This requires maintaining the order in separate accounts without any confusion. This is an example of concurrent testing, where multiple users act on the same resource in real time, requiring accurate synchronization and resource management.

Why is Concurrency Testing Important?

Concurrency testing is usually done for two reasons

1. How does multiple user access at the same time affect the running process of a database or an application?

2. Determines how deadlocking, locking, single-threaded code, and constraining affect the resources that are shared.

Advantages of Concurrency Testing:

Here is a list of advantages of the Concurrency testing of an application:

It significantly decreases the effort for testing an application or database as it restricts the scope of general concurrent communication lines.
One can review just a fragment of the code without disturbing the whole code with the help of a specific value named encapsulation value.

After checking the processes of a concurrent program, it is updated with the reliability and vigor of the application.

Both developers and testers rely on concurrent testing to ensure their applications can handle multiple users efficiently, especially in high-load scenarios such as performance testing. Identifying bottlenecks caused by concurrent users in performance testing helps improve scalability.

Disadvantages of Concurrency Testing:

Concurrency testing, while valuable, also comes with a few notable disadvantages or limitations.

There is no special platform since very few development steps are taken during concurrent testing. Due to this unoptimized situation, multiple outlets are required to perform that whenever simultaneous testing is done.
Since concurrent programs are challenging to test, the defects are hard to find without vigorous testing.
Concurrency testing is highly time-consuming. The results of the operating functions on any part of the code do not return the outcome immediately. Instead, the result is returned later through a sort of notification or a separately designed callback function.
Without proper information representation of the flow of the actual program in the call stack, it is difficult to detect the defects. Thus, defragmenting the testing process.
There is an interconnection of all the concurrent systems that merge and interact with themselves while the program execution process is on. Thus, controlling the contemporary process becomes difficult as the interaction of the systems produces multiple paths of execution.
Concurrent programs have a reputation for failing more often than regular sequential programs.
Due to the multiple paths of execution, debugging the program becomes very troublesome.

Despite these challenges, concurrency testing remains critical in software quality assurance. The following techniques help ensure systems behave as expected under real-world, simultaneous user activity.

Concurrency Testing Techniques:

Several proven concurrency testing techniques help uncover issues in systems with multiple threads or users.

Reviewing Code – This process is quite time-consuming. Because you need to review and check every block of embedded code and its subsequent structure thoroughly.
Static Analysis- This is a standard process to evaluate and check the code thoroughly evaluated and checked before the final execution process. This process aims to determine bugs and errors of any sort in the program.
Con Testing- This method eliminates unwanted synchronization errors from a particular program, hence reducing running deficiencies.
Reachability Testing- This type of testing requires a lot of subtests in its follow-up. Hence, you need to select some precisely verified codes for reachability testing.
Fuzz Testing- This is a random test where the user deliberately inserts wrong code to see how the program’s execution reacts.
Random Testing- This is a valuable method to test multiple threads mandatorily to improve the quality of the results. Hence, it has a vast coverage area.
Extending Concolic Testing- This type of testing is suitable for multiple concurrent programs and numerous sequential programs. It is easily expandable in size and helps a lot.

Types of Concurrency Defects:

Let’s explore the most common defects found during concurrency testing.

Deadlock: This is a specific failure condition where the code stops working due to the deficiency of a particular resource. Here, one of the components is locked by another one and vice versa. For example, a defect caused by two components does not move forward until the resource is free to use.
Livelock: A failure condition where a concurrent component never finishes its execution process due to the lack of necessary resources, termed as the high-priority component.
Starvation: In this particular failure condition where the concurrent component has to wait indefinitely for its execution to complete because some other component occupies the resource it needs.
Suspension: It is a failure condition where the concurrent component is forced to wait for so long that when the resource is available to share, the execution cannot happen properly due to the delay.
Race Condition: A Race condition is a failure condition where too many operations can lead to unexpected and inappropriate behavior of the system. This usually happens when you do not appropriately authorize the resources, and there is excessive access to them. The simultaneous errors can lead to the corruption of the whole system.
Priority Inversion: It is an unwanted failure condition that is first served for the low-priority concurrent component. Then, before executing a high-priority concurrent component, it leads to the disruption of the whole process.

Conclusion:

To summarize, all the above points elucidate that concurrency testing needs development and optimization of the highest sort in itself to be better used in the future.

But at the same time, it is also one of the effective techniques used by businesses to streamline operations in a better manner.

For more details, readers may also refer to TestGrid.

Record and Playback vs Scriptless Testing: Who Wins in Test Reusability?

Shubham Joshi — Mon, 10 Nov 2025 04:55:48 +0000

Conventionally, testing specialists manually checked the developed software before its launch. The necessity to test mundane tasks and redundant scenarios demanded the need for automated testing tools. This helped in saving time, reducing errors, and also performing the same activities automatically.

A bonus of automated testing is that it takes less time to test legacy test cases, but the disadvantage is that it requires scripts. For automation testing, testers need to either learn the supported languages or employ new personnel who can code.

Scriptless Automation Testing

Scriptless Automated Testing is a technique for building automated test scripts without the need for coding or programming knowledge. Compared to test cases that need programming knowledge, automated test cases are easy to generate and set up.

In comparison to ‘Record and Playback Tools,’ Scriptless test automation is more structured and offers more customization choices.

The ease with which test cases may be developed and understood ensures that even members of the team who aren’t familiar with programming languages can examine and build test cases if the necessity arises.

Scriptless Automated Testing makes it easy to generate the test cases in a way that even the members of the team who do not have any prior coding experience and education can create them.

Benefits of Scriptless Automation Testing

Simple to make: Because these technologies have a minimal learning curve, anyone familiar with the project may build test scripts utilizing scriptless automated testing tools.
Simple to Maintain: Whenever there is a difference in the program or functionality, the scripts are simple to maintain
Reuse the Scripts as many times as you want: When necessary, you can reuse any collection of test steps. This helps you in conducting tests repeatedly without any challenge.
Better Customization options: If you need to improve the application flow under test, the changes can be readily incorporated.

Disadvantages of Scriptless Automation Testing

Some tools might be difficult to set up, but TestGrid is relatively simpler

Record Playback Testing

When users interact with the website using Record and Playback testing tools, the steps translate into scripts. They are then executed in the same way they were recorded. For tweaking the ‘Record and Playback’ testing, coding expertise is a mandate.

Benefits of Record Playback Testing

Automated quickly: First, the test case is conducted manually, which is then quickly recorded. Thus, the time required to automate is much shorter than using other testing tools.
Setup and execution are simple: Because no heavy setup is necessary for playback, the recorded test cases are simple to set up and run.
These tools make it simple to detect application locators: While recording test cases, the record and playback tools document the various locators of an object in an application; these locators can be reused for extensive automation.
Easy for Beginners: People who are learning automation will benefit from these tools. They can record and store the test case in the required language. Afterward, the tester works on improving the recorded scripts.

Disadvantages of Record and Playback Tools

The codes become useless if you have to make any changes to them
Customizing the tool is limited and challenging
They are highly dependent on screen size and resolution
There is no option of re-recording
Requires a lot of manual effort to run the same test again and again
Editing the test is a technical job and time-consuming

What are the different methods used by Scriptless Automation Testing and Record and Playback?

1. NLP

For the construction of test cases, specific tools are used. Because the automated tests are written in plain natural language, these technologies can be used by a non-techie as well.

Depending on the situation, the user only needs to understand the proper grammar for test creation and use it to automate complicated or straightforward test scenarios.

The tests are dependable in the event of UI locator changes, and they save time on manual maintenance. They’re great for regression testing, with suggestions for other tests that might be affected and dynamic test summary reports.

2. Image-based Scriptless Automation

These allow you to use Remote Desktop or VNC to access the UI of any application. Also, English is a simple scripting language that may be used to automate activities on the UI of a remote application.

3. Drag and Drop Based Object Mapping

Some tools allow scriptless test automation by enabling users to drag and drop objects directly from a website. The objects can then be reused to create test scripts wherever they are needed.

4. Keyword-driven testing

Keywords are used as actions on test items in these tools. This makes writing test scripts script-free and straightforward.

5. Object Driven Testing

These are capable of recognizing an object and performing actions on it. There is no need to write a script.

6. Testing Using Models
We are a well-known model-based testing tool. TestGrid can recognize all of the website’s objects automatically. The test script logic, test data, and test objects are saved separately and then integrated during the test case execution. If any change is detected in any piece of the program, then the core model that contains the objects updates itself.

7. Screenshots Recording

Some tools take screenshots and use AI to update the test cases anytime the UI of the application is under test changes.

Every time the user acts, they record a test case in the form of screenshots. If the test case does not match the screenshots captured, the test case fails. The program tries to keep test cases up to date by employing artificial intelligence to detect changes in website elements’ position, name, or appearance.

8. Coding Scripts

Selenium and other tools require coding of the test cases. First, a tester writes the script for the work. Thereafter, he conducts the test. This process is boring, mundane, time-consuming, and requires high technical expertise.

9. Bots for Testing Automation

Bots deploy Artificial Intelligence to automate the test results. The bots can perform the entire test based on the input fed. It is relatively simple and doesn’t involve any coding language.

By the way, did you notice the difference?

Thus, “Scriptless automated testing” and “Record and Playback testing” are two distinct testing approaches that try to solve different types of problems.

Do not take them as interchangeable. Thus, the time has come to explore beyond record and playback tools. Test out other solutions that strive to make automation as simple as possible while still providing additional benefits!

Regression vs Functional Testing: Ensuring Quality from Both Ends

Shubham Joshi — Wed, 05 Nov 2025 18:58:53 +0000

Understanding the key Functional vs Regression Testing differences helps QA teams choose the right testing approach for each development stage.

Testing is frequently overlooked or not given the same importance as development in the software development lifecycle.

However, it is just as crucial as development because a buggy application with multiple features can cost you money and a user base. Both Regression Testing and Functional Testing are an essential part of test automation in DevOps.

What Is Functional Testing?

Functional testing is a software testing approach that evaluates all of the software’s features/functions to ensure that each component meets the required specifications.

Each application function or piece is thoroughly tested to ensure that the output/result provided by each application function is as expected.

Function functions are tested by feeding input and verifying output to check what the system does. APIs, databases, security, user interfaces, client/server applications, and the functionality of the Application Under Test are all checked during the testing.

Functional testing does not usually consider internal structure, code, performance, or environmental factors.

The primary aim of functional testing is to ensure Usability, accessibility, and compliance with requirement specifications. In addition, it provides that a product or application will work correctly and efficiently for users.

What do you test in Functional Testing?

Mainline functions: Test an application’s primary functions.Basic Usability entails testing the system’s Usability on a fundamental level. For example, it determines whether a user can freely navigate the screens without difficulty.

Accessibility: Verifies that the system is accessible to the user. Testing Techniques to Check for Error Conditions: Using testing techniques to check for error conditions. It examines whether the appropriate error messages are displayed.

To ensure the validity of the functionality of an application program, functional testing employs a black box testing approach. Because the emphasis is on functionality, the design and user experience aspects are unaffected. The following are the main aspects of functional testing.

Analyze Needs of the Customer:

Validation of the input data
Getting the expected outcomes
Execution of the test case
Comparison of the actual and anticipated outcomes
Comparing the results of the test cases

Why Do You Need To Perform Functional Testing?

The importance of functional testing in validating the quality and functionality of the software cannot be overstated.

Quality assurance teams use this software testing technique to verify software functionality based on the Software Requirements Specification (SRS) and ensure the system functions according to user specifications.

This type of testing aids in determining whether the system is ready for release and error-free. This testing does not rely on assumptions about the system’s structure, but it ensures that a high-quality product is delivered.

Essentially, this testing method is used to test usability features, specific error conditions, accessibility features, and other essential software functions.

It is very easy to dismiss software testing as a waste of time and money. However, a minor bug spiraled out of control for so many organizations. Embarrassing software flaws in a product may cause a brand to go viral but in the wrong way.

There is no need to learn the importance of proper software testing techniques the hard way.

Best Practices For Functional Testing:

#01 Plan Of Testing And Test Cases

The goals and scope of testing, the number of people who will be involved in the testing, the hardware, and software tools that will be used in the testing, the testing schedule, and the number of test cases that will be written to perform the testing are all part of the planning process.

The input data for test cases are based on the functionality’s specification. These test cases should be organized and prioritized to reduce delay and risk. Finally, the development team should review these test plans.

#02 Execution Of Test Cases Should Be Well-Planned.

Testing specific workflows in your app is known as test execution. Functional testing depends heavily on this.

Your testers can use test execution to work their way through specific functions for your mobile or web app, ensuring that they work as they should within the pre-planned workflow.

Assume you’ve created a test case for your e-commerce app. You want users to be able to search for red trainers,’ click on a specific pair, add it to their shopping bag, and check out. Within each step, testers will test specific functions such as the search bar, card payment, and shopping bag to see if the expected results are obtained.

#03 Reporting Of Test Results

A test result report follows a specific format and includes a summary of all test cases completed, the time spent at each stage for each feature, and its status and progress.

It also contains information about any new defects discovered during testing.

Overall, the test result report should be presented clearly and simply so that the development team can understand it.

#04 Automating Functional Testing

Automated testing improves the product or software’s quality while also saving time. What should be automated is up to the tester to decide.

Automated testing is slightly more expensive in the short term, but it is more beneficial to the product in the long run. Avoid automating things that can be done more cheaply and effectively by manual testing.

#05 Manage Defects With Data Storage System

Many people working on the same functionality may result in duplicate defect reports, incorrect order of issue resolution, consideration of incorrect defects, and other issues. A centralized data storage system that everyone can access should be managed to prevent this.

The system includes standard templates for defect reporting and verification, a priority ranking of defects, and information about task assignments; this aids in the solution of problems one at a time.

Different Functional Testing techniques:

End-user-based tests: In this functional testing technique, the system is tested to determine whether or not all of the components work perfectly together.

Equivalence tests: The test data is divided into various partitions in this equivalence test technique, and the data in each partition must respond similarly. Thus, tests are run on a single condition; if any of the conditions in any partition fails, the others stop working.
Boundary value tests: This technique helps validate how the system performs when boundary data limits are used. In most cases, if the provided inputs are less than the boundary values, the test is considered harmful.
Decision-based tests: This decision-based testing technique aids in validating the possible outcomes that can be obtained when a specific condition is met.
Ad-hoc tests: This testing technique aids in identifying bugs that were missed in previous tests. Ad hoc testing is an effective method for identifying bugs that were not previously identified.

What is Regression Testing?

Regression testing is the type of testing which ensures that changes made to the codebase do not affect existing software functionality. These code changes could include, for example, adding new features, fixing bugs, or updating a current feature.

In other words, regression testing entails re-running previously cleared test cases against the new version to ensure that the app’s functionalities are working properly. Furthermore, regression testing is a series of tests, not a single test run whenever new code is added.

Coders create test scenarios and exercise to put newly written code to the test. These tests are included in the ‘test bucket.’

Before releasing a new product version, old test cases are run against the new version to ensure that the old functionality remains intact. This is because adding new code can sometimes introduce errors in the existing code.

Regression Testing frequently entails selecting a subset of all previously executed tests to run again.

Because of changing requirements, the code has been modified.
Software is updated with new features.
Following the correction of defects.
Patch to address a performance issue.
Significant modifications.
Configuration changes.

When To Perform Regression Testing?

It should be taken up when new functionality is introduced: It’s one of the most crucial steps in the regression testing procedure.

When developers submit new code, they don’t always pay attention to how it interacts with existing code, so software regression testing should be used to identify any potential problems.

Existing functionality has been altered based on the requirements, and developers may revise existing functionality and exclude/edit some features during the agile software development process.

In such cases, the functionality and regression testing process determines whether or not the new changes have harmed the rest of the functionality.

New Integration on Other Products: Regression testing ensures that the software product continues to perform flawlessly even after integration with another product.

Why Regression Testing Is Important?

#01 Makes sure that new coding does not interfere with existing coding features

Regression testing is also necessary to ensure that any new code or program updates to software do not interfere with the current features dictated by older code.

For example, when a program or application is updated, software developers typically use regression testing to assess the viability of new features and ensure that the new features do not distort the program’s existing features.

#02 The functionality of the new programming code is evaluated.

Regression testing is an essential tool for determining the success of incorporating new code into an existing program or application.

This is because regression testing is used to test a software program before implementing new coding and then retest the same software to ensure that the application retains its functionality even after new coding is introduced.

#03 Ensures that no defects or bugs remain after software updates have been implemented.

Regression testing can also be used in quality assurance assessments by developers to check for any adverse side effects in the software.

For example, a video game developer, for example, might use regression testing to evaluate any issues, bugs, or glitches that arise after introducing new gaming code into an application. So, for example, suppose there are any bugs or issues with the program.

In that case, the developer can make the necessary changes before retesting the application to ensure that the problems have been resolved.

#04 Allows for the retesting of existing software following application changes.

Regression testing is also vital for providing additional test executions to ensure the viability of program code changes. Retesting each case following a software update or modification enables developers to assess how the new changes affect the program.

For example, suppose a software developer tests a software program after initializing new program code and discovers that the new features disable existing features.

In that case, the developer may retest the update each time they make a repair or change to it. Retesting allows the developer to pinpoint the source of the problem and reconfigure the program to run at peak performance.

Regression Testing Tools:

Developers can choose which tools to use to successfully execute the process after selecting test cases to perform regression testing on. Common regression testing tools can include the following, depending on the project:

Functional regression testing tools: Enable developers to test individual software program elements for errors or defects and generate a report to aid future development.
API testing tools: API testing, also known as application programming interfaces, allows developers to set input criteria to ensure that the software’s output meets performance expectations.
Unit regression testing tools: Enable developers to evaluate specific code elements within a software program to ensure the highest quality and functionality of each code that is integrated into the application.

Challenges of Regression Testing:

When starting regression tests, several challenges may arise. For example, depending on the test case, it can be challenging to start regression testing every time a program changes while staying within the project scope and budget.

Furthermore, continuous regression testing can create large test suites that require more resources to complete on time.

A database is created during each test case to store all data related to that test case. In addition, consistent regression testing can necessitate the generation of large amounts of data, resulting in ever-expanding test suites.

This factor may challenge regression testing of entire test suites, depending on the project budget and scope. Outlining the frequency with which to perform regression testing can also be challenging.

For example, developers may choose to perform regression testing every time software modifications are integrated or only after errors or defects are repaired.

However, building large test suites can necessitate additional resources, and frequent regression testing can also require additional resources.

Difference Between Functional Testing And Regression Testing

Many teams often confuse functional testing vs regression testing, but both serve distinct purposes in maintaining software quality and performance stability.

#01 Feasibility of Automation

Functional testing is performed manually at first, and once a feature is stable, test cases are automated. However, only those test cases that are already stable are executed manually or automatically during regression testing, so this can be automated when needed.

#02 Maintenance/Modification Of Test Script

Because functional test cases are few and focused on a single feature, they do not require extensive modification.

Test scripts in the regression suite, on the other hand, require more maintenance because the test suite is designed to test overall functionality.

However, there is a possibility that it contains old test cases. In addition, functionalities that have changed, new features that have been added, or some features that have been removed may be included in test cases.

#03 The Goal Of Testing

Functional testing determines how closely the developed application matches the desired requirements.

The purpose of regression testing, on the other hand, is to ensure that any changes to the application or systems have not resulted in code breaks and that the system continues to function properly.

#04 Test Case Executed

The functional testing test suite includes a new set of cases and functionalities that have never been tested or executed before. The test cases are re-executed when a defect is raised against a requirement.

Following that, it is fixed and assigned for retesting. If the fault is closed during retesting, the previously failed linked test cases pass. Cases that have previously been tested and passed are included in the regression suite.

Regression testing entails re-running test cases to ensure that changes have not affected previously tested features.

#05 Scope of Testing

Because functional testing is feature-specific, it has a limited scope. For example, suppose a team creates a car with a specific navigation feature. In that case, testers will ensure that the quality can locate the vehicle on a map and guide the driver to any desired destination.

Regression testing, on the other hand, is not feature-specific. It is carried out after a bug has been fixed, changes to a feature have been made, or a new feature added to an existing software application. So let’s look at the same navigation feature we discussed earlier.

Regression testing will be carried out if the mechanic has resolved some issues. If, for example, the navigation feature was not turning on and the mechanic fixed the problem, testers will ensure that it works and that everything else in the car works properly.

Regression testing entails testing a product from beginning to end, whereas functional testing is concerned with determining whether or not a single feature works.

#06 Acceptance Criteria

Functional testing determines whether or not a feature works and whether or not it works as expected.

When a new feature is added to an application, it is supposed to work and is also supposed to work efficiently. This is known as a feature’s acceptance criteria, and functional testing is used to test that feature.

Regression testing has to consider the acceptance criteria for several features instead of just the single added, updated, or fixed element.

This happens because when a new feature is implemented, or a bug is fixed, the fix may affect another component of an application.

Thus, the acceptance criteria for that feature will no longer be fulfilled, and this can only be determined if a tester looks at the acceptance criteria for all features caused by the change.

Conclusion:

To ensure a product’s stability, QA teams use functional testing and regression testing.

When the regression testing cycle is run after a change is made to the code and new bugs are discovered, the test engineers learn how a code change in one component of a product affects the code in the other components.

It also aids engineers in developing new features because they are aware that certain parts of the code rely on others.

Not when bugs are fixed, but when new features are implemented, it is critical for teams that are still figuring out which features rely on each other to deliver a functioning product.

Previous test results assist teams in planning future testing cycles and highlighting areas that should be tested when a new feature is added. When compared to functional testing processes, regression testing has a broader scope.

However, if a product has gone through multiple cycles, teams can estimate the impact of change and plan further testing.

The Power of No Code Process Automation in Modern QA

Shubham Joshi — Thu, 02 Oct 2025 15:33:24 +0000

No-Code Process Automation is a novel approach to developing automation tests that enables you to test an application without writing a single line of code or script.

The goal is to make the setup so simple that automating a test scenario takes less time and almost no coding. For many tasks, especially in IT automation, the less code there is, the easier it is.
By using and reusing premade or preprogrammed blocks of activities, the user can achieve faster results and greater simplicity.

According to Forrester, low/no-code platforms are expected to be a $20 billion+ industry.

So in this article, let us understand How no-code automation in the different fields makes the job easy for the firms.

What Is No Code Process Automation Platforms?

No-code process automation platforms are software applications that require no coding knowledge and enable users to create enterprise-grade, high-fidelity bespoke applications that automate otherwise manual-intensive processes.

By bringing in a more significant number of people with diverse skill sets, such platforms enable organizations to be proactive rather than reactive.

For example, it expedites business processes and reduces errors while relieving employees of mundane and repetitive tasks.

No-code has the potential to take the place of the talent, time-consuming, inflexible, and labor-intensive hand-coded application development and process automation methods.

It has made it easier for employees who do not have coding skills to create simple and complex applications that transform business processes.

Historically, these platforms were considered primarily educational tools; however, the modern generation of no-code platforms will change the definition of who can be a software developer.

This also helps the firm hire a person with better skills in UI, the person with more creative attributes rather than coding attributes because good UI is one of the most crucial for attracting an audience to your app or website.

4 Benefits of No Code Process Automation:

#01 Not able to find the right talent

No-code automation solves this problem by filling in the gaps and compensating for these flaws.

Not only does this allow organizations to allocate their existing skilled workforce away from the mundane to tasks and projects where they can truly make an impact on the business, but it also allows limited IT teams to keep up with their demanding workload.

#02 It Goes Well With Edge Computing

Edge computing, which brings “computational” work as close to the data collection point as possible, is being hailed as one of the top technology trends for 2021 and beyond.

According to recent reports, more than half of new enterprise IT infrastructure will use edge computing as an alternative to massively centralized data centers, especially for proprietary data or in situations (such as transportation or defense) where real-time decisions are required, and multiple trips to the cloud are not feasible.

In addition, this year, 34% of global manufacturers plan to integrate IoT technology into their operations and products.

Edge computing and no-code platforms work well together. For example, no-code apps can extract actionable data and business intelligence from connected devices quickly and easily, allowing for better decision-making.

#03 Supplements Remote/Hybrid Working

No-code platforms will continue to dominate the business app development landscape, allowing business users across organizations to deliver high-quality apps quickly during the pandemic.

Such platforms will enable business continuity and inspire innovation in the post-pandemic future.

#04 Enhance Speed And Productivity

Non-development teams in large organizations benefit from no-code platforms because they have more autonomy. For example, business users can use such solutions to meet their business application needs without burdening IT with time-consuming and mundane tasks.

Without coding or development skills, business users can create functional enterprise apps with modern user interfaces that integrate with core business systems and automate business-critical processes using these capabilities.

This relieves a significant burden on IT and development teams while also speeding up the pace of innovation within an organization.
It also saves money by eliminating the need to hire specialized personnel or buy new enterprise products every time a need arises

What Is No Code Workflow Automation?

No-Code Development Platform – from the beginning, it will assist you in creating workflows in a matter of minutes. A visual UI builder makes everything easier.

Drag and drop functionality saves time, and you won’t be frustrated or lost because you don’t know how to ‘code.

Benefits of No code Workflow Automation:

#01 Easy to Use

Workflow automation software with no code is simple. Any employee in your company can be designated as an administrator, and they will be able to create workflows for various teams quickly.

#02 Cost-effective

Developing new software from the ground up is costly and can cost thousands of dollars. Furthermore, hiring experienced programmers or coders to assist you regularly is still more expensive than utilizing existing resources. The no-code application is the cheapest and provides the best return on investment by helping you streamline your work.

Using a drag-and-drop interface, creating new workflows has never been easier. To get started, drag and drop boxes wherever you need them.

#03 Easy to Implement

It’s much easier to implement multiple workflows in hours than days or weeks when you can create them in minutes. Immediately streamline different departments in your company to work more efficiently.

Workflow automation software uses no-code development, which is both efficient and enjoyable to use. For example, you can create attractive workflows that display all relevant data at a glance.

There is no need to hire programmers to help you maintain the application because it is self-contained. There are no costs or downtime, but your workflow processes will be more reliable and secure.

No Code Robotic Process Automation:

No code RPA solutions aim to eliminate the need for RPA coding. While most common RPA tools have long provided UX support, the UX of most common RPA tools is somewhat restrictive, and developers must rely on programming to automate processes.

In addition to no-code solutions, low code RPA solutions require limited/simple programming compared to traditional RPA software.

Benefits of No-Code Robotic Process Automation:

Programming takes a lot less time and becomes a lot easier.
Increasing the capacity of in-house resources allows them to take on more responsibilities.
Easy maintenance

No Code Business Process Automation:

No-code is a method of developing and using software that does not require coding or programming knowledge. This type of software is part of the self-service movement, allowing business users to create, manipulate, and use data-driven applications to help them do their jobs more efficiently.

Conclusion:

No-code platforms help non-development teams within large organizations gain more autonomy. For example, business users can use such solutions to meet their business application needs without burdening IT with tedious and time-consuming tasks.

With these capabilities, business users who lack development skills or coding expertise can create functional enterprise apps with modern user interfaces that integrate with core business systems and automate business-critical processes.

This relieves a significant burden on an organization’s busy IT and development teams while increasing the overall pace of innovation. It also saves costs by eliminating specialized hiring talent or regularly purchasing new enterprise products.

Source: For more details, refer to TestGrid.

Destructive Testing: A Brief Guide

Shubham Joshi — Thu, 18 Sep 2025 06:14:00 +0000

Destructive testing is a software testing approach aimed at identifying breaking points or potential failures within an application. Unlike traditional testing methods that primarily validate functionality, destructive testing deliberately pushes the system toward failure to evaluate its robustness and stability.

This method is relatively straightforward, requiring testers to intentionally perform invalid or unexpected actions to uncover weaknesses. When combined with strong Test Case Design, destructive testing ensures that scenarios covering both expected and unexpected behaviors are well-documented and systematically executed.

By simulating unpredictable user behavior or edge cases, destructive testing helps ensure that potential errors are detected and addressed before reaching end users. In essence, while traditional testing verifies whether the application works as intended, destructive testing reveals how the application behaves under stress or in unforeseen conditions, offering deeper insights into its reliability.

9 Common Types of Destructive Testing:

Here are the main types of destructive testing:

1. Top-Down Testing

Top-down testing is a method where the programming modules are tested in a specific structural flow as the testing is down from the top going down to the bottom.

By differentiation of levels of the module, high-level ones are tested first, and eventually, the tests move down to low-level ones.

2. Black Box Testing

Black box testing is a specific type of software testing where the operations of an application are tested on the outer part.

The internal structure is not touched and not checked. Every medium of software testing is eligible to go through the black box testing method.

3. Acceptance Testing

Acceptance testing is solely done to check the compliance of particular software or application with the requirements of the business.

It is a thorough checking process where every part of the application is checked, and its acceptability of it is checked according to the conditions set by the clients.

4. Loop Testing

Control Structure Testing, loop testing, is a method specifically conducted to test the loops present in a particular program. Loop testing is a special category of white box testing and is explicitly done to check the correctness and favorable execution of the loops.

5. Boundary Value Testing

Boundary value testing is a type of software testing based on the concepts of vector and set. Here the boundary values are assigned with a specific range, and the subsequent testing is carried out extensively.

6. Stress Testing

Stress testing or torture testing is when a software infrastructure or module is made to go through intense tests.

It is done in a particular abnormal condition and beyond the limit or capacity of the specific module to check its resilience under pressurized conditions, and thus, the results are obtained.

7. Interface Testing

The connection medium between two components is called an interface testing. This medium of connection between two separate software is tested through interface testing, whereby the capacity or the breaking point of this connection is extensively tested.

8. Beta Testing

Beta testing is a particular type of software testing where the user tests the software or application in the original environment but through a sample application. It helps discover all sorts of bugs and errors in a particular program and helps to correct them.

9. Regression Testing

Regression testing is done on already existing software or applications to check whether they work and perform the same after subsequent updates are brought into it. The smoothness and versatility of the newer version are also limited.

If it does not work correctly, the process is termed regression.

Why do Destructive Testing?

It helps the developers to identify the weak points of the software when it is put under improper pressure and not used in the proper manner.
It helps to check the strength and resilience of the software if put under an unwanted condition.

What is Check-in Destructive Testing?

The following points are thoroughly checked while running a destructive test:

The expected behavior of the software.
Improper conduct is shown by the software.
Inappropriate and undesired method of use.
Improper input streams.
Accurate results or output from the software.

How to do Destructive Testing?

There are numerous ways in which destructive testing can be done. Some of those methods are discussed below.

1. Failure Point Analysis Method

This is a method of destructive testing where the tester conducts a thorough assessment of the software to identify the various failure points and correct them. Usually, a Business Analyst is asked for help in this method.

2. Tester Peer Review Method

This is a very effective method of reviewing the various test cases. In this method, a fellow tester with the minimum knowledge of the whole system is summoned who can easily detect the errors and help correct them since that person is unfamiliar with the system’s working.

3. Business Review for Test Cases

In this method, core testers’ features miss due to continuous attention to the testing process being included in the system. Most of the time, expert users detect these legitimate software scenarios that need to be added for better functioning.

Conclusion:

Thus destructive testing is an effective method to identify the faults in a software or application before it is available to end-users. Especially in the current cut-throat competition, businesses do not have room for error anyhow.

Before anything reaches the end-users, it is always a better option to do a thorough check and loop for loopholes. Hence, this is where the role of destructive testing comes into the picture.

Technology might not be 100% perfect, but it can be made perfect with the help of some alterations here and there. There is a significant role played by destructive.

Source: For more details, readers may refer to TestGrid.

Configuration Testing: A Brief Intro

Shubham Joshi — Fri, 05 Sep 2025 06:56:02 +0000

The testing of the application with multiple OSES, different software, or entirely different platforms, is called software configuration testing. It is a process that takes up a lot of time due to the installing and uninstalling of different software that has to be used for testing.

A popular way to test software configuration is to test on virtual machines. On software, there is an environment that will be downloaded that acts as physical hardware and users have the same feel as that of a physical machine, this is called a virtual machine. Real-time configurations are simulated by virtual machines.

The better way would be to install the application or software in the virtual machine and to continue testing rather than installing and uninstalling the software in various machines again and again which is very time-consuming. Having virtual multiple machines makes the job easier for the tester and this process becomes smoother.

The software configuration testing process can commence once the configure ability requirements that are to be tested are defined, the test environment is ready, The team performing the test is properly trained in configuration testing and The build being released has passed the unit and integration test.

The typical test strategy that is used to test the software configuration is to perform the functional test suite across various software configurations to confirm that the application being tested is working as wanted and is without any bugs or errors. Another way to make sure that the system is working efficiently is by manually filling the test cases and verifying them for efficiency. In practice, testers often automate these checks using tools like Selenium, where Selenium XPath plays a key role in locating and validating UI elements consistently across different environments.

Let’s say that there is a banking application that has to be tested to see if it is compatible across multiple browsers and when the application is in an environment where all the prerequisites are present does it pass the unit and integration testing in the test lab.
Although, the same applies if placed and installed in a client‘s place the machines are missing and some of the software updates of the versions on which the application is directly dependent or indirectly dependent, there may be situations that the application might fail to perform. This situation can be avoided by failing the tests manually to remove some of the configured ability requirements and then proceeding with the testing.

Hardware Configuration Testing

Places, where there are physical machines and different hardware attached to them, are where generally hardware configuration testing is performed.
The software has to be installed in all physical machines where the hardware is attached every time a new bid is released and the test suite has to be run on each machine to make sure that the application is working efficiently.

A lot of effort is required to install the software on every machine to attach the hardware and to manually run or to automate the above process also requires a huge amount of effort. Specification of which type of hardware has to be tested is to be done compulsorily because there are a lot of computer hardware and peripherals which make it extremely difficult to run all of them together. Hence, it is the responsibility of the tester to find out which hardware is going to be used by the users the most and try to make the most test based on that, making it a priority.

All in all, in the scope of software engineering, configuration testing must be provided the same amount of significance as other testing methods. If configuration testing is not performed it is very hard to understand the optimal system performance and the software might also have compatibility issues.

Source: For more details, readers may refer to TestGrid.

Load Testing – The Process, Tools, Best Practices

Shubham Joshi — Wed, 03 Sep 2025 06:10:41 +0000

What is Load Testing?

Load testing is also termed reliability testing or software performance testing. It is a software testing method where the software or an application is put through an abnormal load to see how it reacts and performs under that condition. It is thoroughly checked if the performance of the application decreases or increases in that situation. The main aim of running a load test is to detect the potholes of an application’s performance and smoothness. This ensures that stability is instilled into that software when multiple users access the same function simultaneously.

The biggest USP of Load Testing is that it helps in giving out a clearer picture of the limitations of the application. Then, enabling enables the tester to analyze the root cause of the problem and take corrective measures. Through load testing, the failures are limited during production, which in return reduces the expenses. Hence, load testing is very cost-effective in nature.

User Experience Under Load Testing

Users perform this test to describe how promptly the device under test (DUT) responds to a certain amount of production load. There are selected applications that go through this test where the performance of the targeted application is denoted as the User Experience Under Load. Finally, the users assess the results to find if the application is performing on point.

Load Testing Tools:

Some of the most popular testing tools are listed below:

Apache JMeter
BlazeMeter
Blitz
Flood
Gatling
Loader.io
LoadRunner
Load Test
LoadUI
Login VSI
NeoLoad
OpenSTA
Rational Performance Tester
Silk Performer
Siege
Test Studio
Visual Studio
WebLOAD

Why is Load Testing Important?

Load testing is a crucial part before an application or software leaves for production. Because there is a certain amount of load that an application is put through after the functional test. However, this doesn’t mean that the same application would go through the same amount of load when the user uses it. Hence, load testing is essential to check for any loopholes or error functions. This ensures correcting the loopholes.

In fact, many testers also combine functional automation (using Selenium XPath for UI element interaction) with load testing to validate both performance and correctness under stress. This dual approach ensures the application not only handles the load but also behaves as expected during peak usage.

How to Start This Testing?

The basic steps to start the process of this testing are:

First, gather all the requirements to begin the test. This includes all essential parts, along with all the experience and problems the application’s end-users face.
Second, follow how the end-users use the application and the amount of load they put on it regularly to analyze the actual journey of the application.
Third, establish a solid base on which you can specify the conditions and run tests. Whenever you see the specifications are not met, update the process for better test execution.
Finally, give the ample amount of importance test loading requires and integrate the whole test execution process with all the tools necessary.

Selecting a Load Testing Tool:

Keep in mind the following points before selecting the suitable load testing tools. Hence, check for the following:

Efficiency and accessibility of the tool before creating test cases.
Accuracy of the tool by tracking real-time test data.
Scalability of the tool by regulating the number of test cases or instances.
Integrity methods of the tool to bring down all tools together.

Benefits

Identifies the loopholes of an application before direct production.
Increases the scalable functions.
Optimizes performance to reduce the risks of system downtime.
Substantially reduces the costs of repairing after failure.
Increases satisfaction and provides a better end-user experience.

Best Practices

While carrying out a load test, it is essential to think like a user. This helps incorrectly develop test cases and put an appropriate load on the system for testing.
The more often you load test your systems, the better it works. On top of that, if you feel that an application or software is not reacting to load well, consider testing it in the early stages before a complete breakdown happens.
Before starting a full-blown load test, try to analyze all the real-time issues that a system is facing. Create a test case accordingly and then execute all of it. Keeping that in mind, never put on the complete load at once. Instead, consider putting it in installments and recording every stance of the system’s reaction.

Load Testing Guidelines:

Plan the test once the application is stable.
A vast number of data (Unique) should be readily available in the data pool.
One should avoid creating detailed logs to conserve the space of disk IO properly.
Avoid downloading images on the site.
Decide the number of users for every script and scenario.

Conclusion:

Hence, this testing ensures that your application runs smoothly and effectively, thereby satisfying the experience of an end-user. This ensures a reduction in functional errors and increases the application’s performance exponentially.

Source: For more details, readers may refer to TestGrid.

Implementing Robust Error Handling in Selenium Tests

Shubham Joshi — Mon, 25 Aug 2025 18:13:18 +0000

Anyone who's worked with Selenium for more than a day knows that automated UI tests can be unpredictable. One moment your test suite is passing flawlessly, and the next, it's riddled with failures—often due to things beyond your control, like slow page loads, dynamic elements, or timing issues. That's where robust error handling in Selenium tests becomes crucial.

One of the best tools to help manage errors proactively is TestNG Listeners. These are built-in interfaces in the TestNG framework that allow you to track and react to events during test execution. From capturing screenshots on failure to logging custom messages, TestNG Listeners are the kind of power tool you want in your back pocket when things go south.

Why Error Handling Deserves Your Attention

Let’s take a step back and ask a basic but important question: what is error handling, and why does it matter in Selenium testing?

At its core, error handling is about anticipating and managing potential failures gracefully. It’s not just about catching exceptions—it's about designing your tests to recover, report, and continue in a controlled way. Without it, you're not really automating intelligently; you're just automating blindly.

Error handling in Selenium tests is especially critical because of the nature of web applications. Elements move, servers slow down, network issues spike—your tests need to be smart enough to cope with these changes.

Where Test Failures Usually Come From

If you’re wondering what to look out for, here are a few common Selenium errors that most testers run into:

NoSuchElementException: The element wasn’t found in the DOM.
ElementNotInteractableException: Found it, but can’t interact with it.
TimeoutException: The wait period ended before the expected condition was met.
StaleElementReferenceException: The element reference is no longer valid due to DOM refresh.

These issues can be intermittent, which makes them even harder to debug. That’s why proactive error handling matters—it turns these random failures into known quantities that you can manage effectively.

Tip #1: Use Try-Catch Where It Makes Sense

The simplest form of selenium error handling is the good old try-catch block. You can use it to wrap specific lines of code where failure is likely or recoverable.

try {
    WebElement button = driver.findElement(By.id("submit"));
    button.click();
} catch (NoSuchElementException e) {
    System.out.println("Submit button not found. Skipping this test step.");
}

While this helps prevent a test from crashing entirely, overusing try-catch can mask problems. Use it sparingly and wisely—only when failure is non-critical or expected.

Tip #2: Centralize Your Error Logging

Instead of scattering logs across test files, consider building a utility class or method that handles all logging and screenshot capture. This makes your tests easier to maintain and debug. You can then plug this utility into your TestNG Listeners to automate it across the board.

A common pattern is to capture a screenshot automatically on test failure:

public void captureScreenshot(WebDriver driver, String testName) {
    File src = ((TakesScreenshot) driver).getScreenshotAs(OutputType.FILE);
    File dest = new File("./screenshots/" + testName + ".png");
    FileUtils.copyFile(src, dest);
}

And trigger this method from the onTestFailure listener event.

Tip #3: Don’t Ignore Your Test Runner

Understanding what is test runner in Selenium will make you more effective at handling test errors. The test runner (like TestNG or JUnit) is the tool responsible for executing your test scripts, managing lifecycle events (setup, teardown), and collecting results.

When integrated with listeners or hooks, your test runner becomes a powerful mechanism for error management. You can configure it to retry failed tests, log errors, or send alerts—all without cluttering your test code.

Tip #4: Add Retries for Flaky Tests

Sometimes, a test fails for a reason that won't repeat if run again immediately. That's where retry logic comes in. You can implement custom retry analyzers in TestNG that attempt to rerun failed tests before declaring them as failed.

This technique is often used to manage flakiness caused by slow page loads or transient UI changes—scenarios where error handling in Selenium tests can drastically reduce false negatives.

Tip #5: Use Assertions Thoughtfully

Assertions are often used to confirm that the application behaves as expected, but not every assertion failure should halt the entire test. You can use soft assertions (available in TestNG) to allow multiple assertions within a test to run before failing the test case. This helps gather more data on what went wrong.

Here’s a small example using TestNG’s SoftAssert:

SoftAssert softAssert = new SoftAssert();
softAssert.assertTrue(condition1);
softAssert.assertEquals(actualText, expectedText);
softAssert.assertAll(); // Triggers failure if any assertion fails

Again, this is not about ignoring errors—it's about handling them in a structured way.

Tip #6: Deal with Unpredictable Popups and Alerts

Unexpected modals, popups, or browser alerts can break even the best test script. Selenium provides ways to switch to and manage alerts, but many testers forget to add proper checks.
Here’s how to safely handle alerts:

try {
    Alert alert = driver.switchTo().alert();
    alert.accept();
} catch (NoAlertPresentException e) {
    System.out.println("No alert found. Continuing.");
}

These small guards are what make error handling in Selenium tests practical and production-ready.

Tip #7: Keep Tests Independent

One of the lesser-discussed strategies is to design tests that don’t depend on each other. If Test A fails, it shouldn’t affect whether Test B runs. This becomes even more critical when errors occur.

Using @BeforeMethod and @AfterMethod annotations in TestNG allows each test to have a clean setup and teardown, reducing shared state issues.

Bonus: Monitor and Alert

Once your tests are integrated into a CI/CD pipeline, error visibility becomes vital. It’s not just about catching the error—it's about letting the right people know it happened. Tools like Jenkins or GitHub Actions can be configured to send Slack messages, emails, or even webhook notifications when a test fails.

These monitoring solutions enhance the effectiveness of your error handling in Selenium tests, ensuring issues don’t go unnoticed.

Wrapping Up

There’s no silver bullet when it comes to error management in test automation. But by applying a few smart strategies—like using TestNG Listeners, logging failures, retrying flaky tests, and managing assertions—you can make your error handling in Selenium tests significantly more robust.

Think of it this way: you wouldn’t ship production code without handling exceptions, so why treat your tests any differently?

As your testing stack evolves, so should your error management strategy. Combine functional techniques like try-catch and soft assertions with structural tools like test runners and listeners, and you’ll find yourself spending less time on debugging—and more time building quality software.

To learn more about advanced listener customization, you can explore TestNG’s listener documentation, which breaks down implementation and event types in depth.

By mastering error handling in Selenium tests, you're not just creating automation—you’re building a safety net for your application and your team.