A mechanized method for risk-based test case generation and prioritization by an improved correlation system (R-TCGiCS)

With a combination of limited resources and a demanding schedule, software testing is sometimes done under great pressure to guarantee that the software requirements are met. In addition, testing should reveal any flaws in the software that could compromise its ability to perform its primary functions. The most time-consuming and important part of testing software is creating test cases. There are a lot of testing scenarios, and the testing efficacy is low; thus, the test data needs to be enhanced using a powerful optimization technique. Test priority becomes an absolute necessity when testing software products built in a production line with limited resources in terms of time and money. Therefore, this paper proposes risk-based test case generation and prioritization by an improved correlation system (R-TCGiCS), which has been introduced to perform regression testing. The suggested method uses data on changes to requirements, method complexity, and total project size as risk indicators. In this research, the authors present a risk-based test case prioritizing strategy that uses information about software changes and the invocation relationship between methods to determine which tests should run first. The goal of this research is to automate the procedure for risk evaluation to make the risk-based analysis simpler and more flexible and to detect high-risk faults earlier. It achieved an impressive fault detection rate of 80% when executing 150 test cases, outperforming other approaches such as GA-TCP and ARS, which recorded detection rates of 66.67% and 60%, respectively. Experimental results reveal that our suggested method enhances test efficiency by detecting faults earlier than existing state-of-the-art approaches, particularly in high-risk modules.

Text 123999.pdf - Published Version Restricted to Repository staff only Download (1MB) Official URL or Download Paper: https://link.springer.com/article/10.1007/s42979-0...

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