Understanding Beyond Smoke Testing: Critical Functional Testing in Software Development

When discussing software testing, phrases like 'smoke testing,' 'sanity testing,' and 'regression testing' often come up. These terms, though fundamental, can be deeply misunderstood. This article aims to unravel the confusion and provide a clear understanding of these concepts.

Software Build: The Foundation of Software Development

Beyond the basic understanding that software development involves writing code, it is essential to comprehend the process of creating executable software through a 'build.' A build is the process of combining multiple source code files into a single executable file that can be deployed by the release team.

Before reaching the client, a software undergoes various changes, including fixing defects, leading to multiple 'builds.' This iterative process ensures that the software is resilient and free from critical issues. Understanding the concept of 'build' is crucial to comprehend the importance of various testing phases.

Smoke Testing: The Basic Check-Up

Imagine a situation where the most basic feature, like user login, doesn't work. Smoke testing is the preliminary test designed to reveal simple failures that are severe enough to reject a given build. This test acts as a 'confidence test' or 'verification test' of critical functionalities.

The goal of smoke testing is to identify and reject key defects before full functional testing begins. This practice ensures that the build is stable enough to proceed with detailed testing, thereby saving time and resources. Best practices in the industry advocate for daily smoke testing.

Sanity Testing: A Specialized Check-Up

Sanity testing extends the concept of smoke testing. It is a more specialized form of testing performed after each change or update in a build. Its primary objective is to verify if the changes are working as expected, thereby enabling other detailed tests.

Sanity testing is a rational, health check-up to ensure that the software is working as intended after a recent change. Just as a person not being considered sane if they display irrational behavior, a software build must behave rationally post-update.

Key Concepts

Sanity Testing vs. Smoke Testing: Although both are preliminary tests, sanity testing is more focused on specific changes, whereas smoke testing is a broader initial test.

Automated vs. Manual Testing: Both sanity and regression testing can be performed manually or through automation, with regression being better suited for automation tools like Selenium or HPE UFT.

Regression Testing: Ensuring No Side Effects

After performing smoke and sanity tests, the job is not entirely finished. The code is developed, the build is deployed, tests are performed, and defects are fixed and retested. However, changes can affect multiple areas of the software, leading to new defects.

Regression testing ensures that while fixing defects and implementing changes, no new defects are introduced. Impact analysis is crucial in identifying affected areas, making regression testing an indispensable part of the testing cycle.

Impact Analysis in Regression Testing

Impact analysis is the process of understanding the effects of a change on the software. It includes identifying which parts of the software may have been impacted by a change and ensuring they are still functioning correctly.

A thorough regression testing cycle is essential, especially when changes are made, to maintain the quality and integrity of the software.

Conclusion and Best Practices

To be a great tester, it's essential to understand these concepts and their nuances. The testing community often uses the same terms to refer to different processes, leading to further confusion. However, by understanding the sequence and purpose of these tests, testers can perform their role more effectively.

Smoke, sanity, and regression testing are all crucial steps in ensuring a stable, defect-free software build. By integrating these practices, organizations can maintain the highest standards of software quality.

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