What is Regression Testing? All You Need To Know

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Have you ever thought about how your phone’s apps and software stay perfect even after countless updates? Imagine this: developers are coding furiously, testers are putting in their efforts, and new features are added to the apps. But some new changes come with great responsibility – make sure that everything works smoothly and no sneaky bugs have crept in! This is where regression testing comes in. Here, we will explain what regression testing is, its types, how to conduct regression testing, and many more. Keep reading to know!

What is Regression Testing?

It is a type of testing where you can check the changes made in the codebase that do not affect the existing software functionality. For instance, such code changes might involve adding new features, bug fixes, updating current features, etc.

In simple words, regression testing means re-executing previously passed test cases on the updated version of the apps to confirm that all features are still functioning properly. Moreover, regression testing is a series of tests that are conducted each time a new version is added to the codebase.

Is It Possible To Perform Regression Testing Manually?

Yes, such type of testing can be performed manually. Generally, it includes retesting the changed parts of the software application to ensure that the changes haven’t impacted the current functionalities. 

Though manual software regression testing is possible, it can be time-consuming and error-prone, especially for big and complex systems. This is why automated regression testing tools are advisable to enhance efficiency and accuracy.

Examples of Regression Testing

Let’s take a web-based e-commerce platform as an example. Suppose the development team adds an enhancement to the search functionality, enabling users to filter the product by its color.  Here’s how regression testing may be applied in such case:

  • Product Browsing: Apart from the changes made to the search functionality, users should still be able to browse through product categories, and check our product details and items in their cart without having any issues.
  • Cart management: After adding a new search filter feature, regression testing ensures that people can still easily add, remove, or update items in the shopping carts.
  • Checkout process: Confirmed that consumers can proceed via the checkout process smoothly, from entering shipping and billing information to completing the payment is pivotal. Regression testing ensures that this important functionality remains intact.
  • User accounts: We need to test the user’s account management system to verify that they can still log in, update their profile, and check order history without having any issues with changes made.
  • Mobile responsiveness: This testing may also involve checking the responsiveness of the platform across several devices and screen sizes to ensure the new search filter has not caused layout or usability problems on mobile devices.

When to Perform Regression Testing?

This testing in software testing is performed when the changes are made or the code is modified including adding new features, fixing bugs, and updating the current software. It is suitable in below cases:

A New Feature Or Functionality Is Introduced To The Application

For example, you have made a website with login functionality enabling users to first login only via email. And now you want to add login via Facebook or Instagram.

There is a Requirement to Change

For instance, you delete the remember password functionality on the login page which was applicable easily. Regression testing is conducted after every such change.

When Defects Or Patches Are Fixed In The Codebase

For example, when the tester finds a broken login button. Once the developers fix the bug, they test the login button for expected results, while simultaneously performing tests for other functionalities related to the login button.

When Performance Issues Are Fixed

For instance, when a page takes 5-7 seconds to load, the loading time is reduced to 2 seconds.

When There Are Environment Or Configuration Changes

For example, update the database from MySQL to Oracle.

Advantages and Disadvantages of Regression Testing

Advantages:

  • Regression testing makes sure that any change in code does not negatively impact other functionality.
  • It ensures that already solved issues don’t occur again.
  • This software regression testing serves as a risk mitigation strategy during testing.
  • Easy to learn, understand, and determine.

Disadvantages:

  • Without automation, this type of testing takes more time.
  • Testing is required for all small changes of code.
  • A repetitive process of testing can affect agile sprint.
  • Needs you to create complex test cases.

How to Conduct Regression Testing?

Normally, there are no fixed patterns to perform this testing. But, there are several methods that quality analysts should use while conducting testing:

Step 1: Regression Test Selection

First, you need to choose the test cases requiring re-testing. Keep in mind that you would not be able to test the entire test suite, and the selection of test cases relies on the module where there is a change in the source code.

Then, you divide the test cases into:

(i) Reusable Test Cases

(ii) Obsolete Test Cases. 

Reusable test cases will be used for future regression cycles, while you won’t consider Obsolete ones for the upcoming testing cycles.

Step 2: Know the Time for Executing Test Cases

The next thing you need to do is determine the time it will take to execute the chosen test cases. 

Several factors that impact the execution time are test data creation, regression test planning by the quality analyst team, and checking of all the test cases.

Step 3: Identify the Test Cases that can be Automated

Here, as per the results of exploring testing, the QA team can decide the test cases that they can automate. Automated test cases are faster as compared to manual testing and enable you to reuse the same script again. So, divide the test cases into two groups – 

(i) manual test cases

(ii) automated test cases

Step 4: Test Cases Prioritization

Now, you collect all the test cases and prioritize them such as high, medium, and low. By this evaluation, you will execute the high-priority cases first, followed by medium and low-priority test cases. The priority will depend on the product’s functionality and user involvement.

Step 5: Executing Test Cases

Finally, it’s time to execute all the test cases and test whether the product is working as it should or not. You can go for manual testing or automation as per the requirement. For automated regression testing, using functional tools like Selenium, QTP, Watir, etc., allows you to execute the test cases faster.

Conclusion

Regression testing is a crucial aspect of software development that ensures code changes do not impact existing functionality. By re-executing previously passed test cases, developers can maintain software quality and reliability. While it can be time-consuming, especially when done manually, the benefits of catching potential issues early far outweigh the costs. With proper test case selection, prioritization, and execution strategies—including automation where appropriate—regression testing helps deliver stable, high-quality software products that meet user expectations and business needs.

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The 5 Game-Changing Roles of AI in Software Testing in 2024

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AI is game-changing in software texting, making it faster, smarter, and more effective. With the help of AI, testers can automate tasks easily, find potential issues faster than before, and look for vast amounts of data quickly. As we move into 2024, AI is becoming more important in testing. It’ll help you do even harder tasks, so they can release great software faster and with fewer problems. Below, we’ll talk about how AI improves software testing for everyone.

But first, let’s discuss what AI-based testing is!

AI-Based Testing

AI-based testing is a method of testing software that uses AI and Machine Learning (ML) algorithms to make the testing process more efficient and effective. Its main goal is to use logical reasoning and problem-solving methods to improve the overall testing process. In AI-based testing, AI-driven tools are used to execute tests without any human intervention. This means that data and algorithms are used to design and perform tests automatically.

5 Amazing Roles Of AI in Software Testing In 2024

The 5 Game-Changing Roles of AI in Software Testing in 2024

In the ever-evolving landscape of software testing, one revolutionary force is reshaping the way we ensure quality: Artificial Intelligence (AI).

AI-driven tools for software testing can easily check bugs, inconsistencies, and several issues that manual testing could require days or even months. Moreover, these tools can likewise mimic client conduct to guarantee the final result is of the greatest conceivable quality. Here, let’s find out how AI can help the testers to streamline their tasks:

Automated Test Case Generation

One of the key roles of AI in software testing is its ability to generate test cases automatically. Generally, most of the test cases were created by testers manually which was a time-consuming and error-prone process. 

Additionally, AI algorithms can analyze software’s requirements, designs, and also code to generate comprehensive test cases, covering various scenarios and edge cases.

Moreover, AI can prioritize and optimize test cases based on various factors like risk, code complexity, and previous test results. This enables testers to focus their efforts on the most critical parts, increasing the effectiveness of the testing process while minimizing redundant or low-impact tests.

Defect Prediction and Prevention

AI in software testing easily predicts and prevents defects before they can occur. By checking historical data, code changes, and other factors AI models can predict the defects in certain areas of the codebase. By getting this information testers can write cleaner and create strong code from the outset.

Self-Healing Test Automation

AI-powered test automation frameworks can automatically adjust test scripts based on the changes in the application’s user interface or functionality. Then, such frameworks use machine learning to determine and modify test scripts which lessens the need for manual updates and help, ensuring that automated testing is perfect and reliable.

Natural Language Processing (NLP) or Requirements Analysis

Typically, NLP algorithms assist computers in understanding and reviewing documents that are written in everyday language. They can easily address mistakes and unclear things in the requirements, ensuring everything makes sense. This way, it can make the perfect test for software so it works well and does not have any issues.

Performance Testing and Optimization

Performance is one of the critical aspects of any software application and AI is playing an important role in ensuring optimal performance. The AI-powered tools analyze app performance data, determine performance bottlenecks, and also provide several insights for optimization. Such tools can simulate real-world usage scenarios, stress test the application, and identify areas for improvement. Doing so ensures a smooth and responsive user experience.

Advantages of AI in Software Testing

AI offers numerous benefits in software testing below we will mention one by one:

Improves Test Coverage and Efficiency

Because of time conflicts and human limitations, traditional testing methods usually struggle to cover all possible things during the software development process. However, machine learning algorithms can automatically generate various test cases such as uncommon scenarios and edge cases, lowering the risk of undetected critical issues. Apart from this, AI in software testing can easily replicate test cases, so it can minimize false positives and negatives in defect identifications.

AI Can Decrease Manual Efforts And Faster Testing Cycles

AI-powered tools can automate time-consuming tasks. These are:

  • Creating test cases
  • Preparing test data
  • Updating test scripts

Well, this automation improves productivity and enables testers to focus on other complex tasks where human expertise is crucial. 

Moreover, AI in software testing can identify the most relevant tests based on code changes as per developer feedback. The result is a dramatic time reduction in your software development timeline, enabling software teams to rapidly release updates and new features.

AI Can Improve Efficiency in Defect Detection

Well, traditional testing methods may miss minor or complex defects in large and tough codebases. This is where AI can help, with large algorithms it can easily identify hard-to-detect issues.

AI analyzes historical data and current software metrics to find error-prone areas. This way, testers can focus on parts of the applications that mostly have defects.

Moreover, AI-driven tools can also learn from past testing cycles and improve them to detect defects. By doing so, it will easily adapt to evolving software complexities and maintain top-quality standards. 

AI Can Enhance User Experience

AI in software testing can improve the user experience. Generally, AI-driven tools can simulate real-life user scenarios and interactions which can help in gaining valuable insights into the experience that users have while using your software. It involves testing under several conditions and on multiple devices, ensuring the software performs the best in all expected user environments.

Apart from this, AI can determine usability issues like complex navigation, and unresponsive elements which are tough for testers to determine. By knowing these complex issues, AI helps you to create more user-friendly and intuitive software applications, offering a better user experience.

Conclusion

In the year 2024, the role of AI in software testing has changed significantly. It offers numerous benefits to agencies striving to deliver top-quality software in today’s competitive market. AI helps with making tests automatically, deciding which tests are most important, predicting issues, fixing test problems by itself, and checking if the software meets the requirements using natural language processing. By using AI in these ways, companies can make their testing work better, faster, and more reliable. This can lead to happier customers and more successful businesses.

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