Analyzing the Effectiveness of Mutation Testing in Real-World Software Development
Awais, Muhammad (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202504257648
https://urn.fi/URN:NBN:fi:amk-202504257648
Tiivistelmä
Software testing is an important part of the software development lifecycle, ensuring dependability and functionality in complex systems. Traditional testing metrics, such as line and branch coverage, have long been the standard for assessing test effectiveness. However, these methods repeatedly fall short in finding subtle errors that can substantially influence software quality. Mutation testing appears as a favorable alternative, introducing intentional faults (mutants/bugs) in the code to assess the robustness of test suites.
This thesis examines the effectiveness of mutation testing in contrast to traditional testing techniques, aiming on real-world software projects. Using tools like Pitest for Java, mutation testing is used to selected open- source projects to examine its fault detection abilities. The study focuses key insights into the correlation between traditional coverage metrics and mutation scores, detecting strengths and limitations of both methods.
The results determine that mutation testing gives a deeper understanding of test suite quality, revealing flaws often examined by conventional metrics. This research offers practical recommendations for integrating mutation testing into software development workflows and implies areas for future development in testing tools and methodologies.
This thesis examines the effectiveness of mutation testing in contrast to traditional testing techniques, aiming on real-world software projects. Using tools like Pitest for Java, mutation testing is used to selected open- source projects to examine its fault detection abilities. The study focuses key insights into the correlation between traditional coverage metrics and mutation scores, detecting strengths and limitations of both methods.
The results determine that mutation testing gives a deeper understanding of test suite quality, revealing flaws often examined by conventional metrics. This research offers practical recommendations for integrating mutation testing into software development workflows and implies areas for future development in testing tools and methodologies.