What are the Benefits of Self Healing Test Automation?

5 mins read 1 Experts
Diksha Gupta
Senior Automation QA | Mondia Group | Dubai

Power of Self Healing Tests in Test Automation

Over the years, now we are moving towards quality engineering that combines test automation, DevOps, and Agile practices. However still we have challenges where Tests are fragile and break frequently. Now we will discuss how self healing will overcome the challenges of fragile Test Automation. Now let’s first understand what Self Healing Test Automation is.

 

What is Self Healing Test Automation

Self-healing test automation in an Agile world refers to the ability of automated tests to autonomously detect, diagnose, and recover from failures or changes in the application under test. This capability aligns with the principles of Agile methodologies, which prioritize continuous integration, rapid iterations, and quick feedback loops. The goal is to enhance the resilience, adaptability, and efficiency of automated testing processes within the Agile development lifecycle.

 

Why is Self Healing Test Automation required?

Traditionally, test automation used application components to define and write their tests. Whenever the application under test went through certain changes, manual intervention was required to update these application components and objects. If not, the test scripts broke down in response to any change in the object properties.

The self-healing test automation process reduces manual efforts by automatically updating the tests whenever there is any change to the application and freeing up resources for more strategic and value-added activities. For example, it updates the automated tests on adding a new application feature or improving existing functionality by leveraging AI(Artificial Intelligence) and ML(Machine Learning). Also this reduces the maintenance burden on test scripts.

 

How Does Self-healing Mechanism Work?

The self-healing process typically involves a set of intelligent algorithms and techniques designed to identify and address issues automatically. The self-healing mechanism continuously monitors the execution of automated tests. It keeps a watchful eye on various elements, such as user interface interactions, application responses, and data validations.

Step 1: The self-healing mechanism gets triggered whenever “NoSuchElement” or similar an error occurs for an element mentioned in the automation script.

Step 2: The algorithm analyzes the test script to identify the root cause of the error. When a failure occurs during test execution, the self-healing mechanism analyzes the nature of the failure. It identifies whether the failure is due to a legitimate defect or if it’s a result of changes in the application.

Step 3: The algorithm uses AI-powered data analytics to identify the exact object in the test script that has changed. An object can be any interface item like a webpage, navigation button, or text box.

Step 4: Once the root cause is identified, the self-healing mechanism automatically adjusts the affected part of the test script. This may involve updating object locators, modifying data input, or making changes to the verification points in the script. In some cases, self-healing mechanisms integrate with version control systems to understand the historical context of the application and its changes.

Step 5: The updated test case is re-executed to verify that the remediation has been successful. It ensures that the test script aligns with the current state of the application, allowing for continued and accurate test execution.

Step 6: Throughout the self-healing process, detailed logs are maintained. These logs include information about the detected issues, the root cause analysis, the modifications made to the test script, and the validation results. This logging is crucial for transparency and debugging.

Depending on the implementation, the self-healing mechanism may notify users or stakeholders about the detected issues and the actions taken to resolve them. This ensures that the team is aware of the changes made to the automated tests.

Note: It’s important to note that the specific implementation of self-healing mechanisms can vary based on the testing tools, frameworks, and programming languages used in a particular test automation environment and the initial implemented test scripts, the robustness of the application.

 

How self-healing test automation adds value to your Automation process?

Self-healing test automation brings several benefits to the software delivery process, enhancing efficiency, reliability, and adaptability. Here are key advantages:

Adaptability to Changes : As applications undergo changes or updates, self-healing tests automatically adapt to these modifications without requiring manual intervention. This ensures that tests remain effective and relevant in dynamic development environments.

Faster Feedback Loop: Self-healing automation reduces the time spent on diagnosing and fixing test failures, leading to a faster feedback loop. Teams can quickly identify issues, allowing for prompt corrective actions and iterations. With traditional test automation approaches, tests are often run manually or through a continuous integration pipeline, Which is time consuming. Self healing Automation enables teams to identify and fix issues faster, improving the overall quality and reliability of the application.

Saves Time and Effort: Self-healing test automation can save organizations a significant amount of time and effort in software testing. Traditional test automation approaches require manual intervention to fix errors or failures that occur during test execution. This can be a time-consuming and error-prone process, especially when dealing with large and complex test suites. Self-healing test automation eliminates the need for manual intervention, allowing tests to recover automatically from failures or errors. This leads to more efficient resource utilization and allows teams to focus on strategic and value-added activities.

Enhanced Confidence in Automated Testing: The ability of self-healing tests to automatically recover from failures builds confidence in the reliability of automated testing processes. Teams are more likely to rely on automated tests for regression testing, ensuring the stability of software releases. This also contributes to the overall robustness of automated tests. Tests that can autonomously recover from common issues become more stable, providing consistent and trustworthy results.

Fewer failed and flaky tests: Fragile tests fail as soon as they encounter an unrecognizable object. Flaky test designs are unreliable and contribute to the instability of the test automation framework. With self-healing, testers can create a limited set of tests, run them, identify the stable ones easily, and continue to work with them. This leads to a more stable testing framework. The self-healing mechanism ensures that automated tests remain stable even in the face of changes in the application. This stability is crucial for maintaining the effectiveness of the testing process.

 

Conclusion

Self-healing test automation plays a pivotal role in modern software delivery by improving efficiency, reliability, and adaptability. It contributes to a more agile and responsive testing process, aligning with the goals of continuous improvement and rapid software delivery.

Connect with Diksha Gupta : Topmate

 

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