Combinatorial First Order Polynomial Coverage Based Test Suites Prioritization for Improving Software System Quality

Abstract

Combinatorial Testing (CT) is performed to ensure the development of a software system quality. In CT, many research works has been designed for test suite minimization. But, existing test suite minimization techniques does not covers the more number of test cases for detecting the maximum faults in software programs. Therefore, there is a requirement for new test suite minimization technique for improving software system quality with higher number of test cases. To optimize the order of interactions being tested and to reduce the number of test suites generated best in terms of coverage, Combinatorial First Order Polynomial Coverage Based Prioritization (CFOP-CP) technique is proposed. For monitoring the order of interactions at time interval ‘ t ’ and time interval ‘ t-1 ’, First Order Polynomial (FOP) function is used. Therefore, FOP function predicts the faults interactions in software program efficiently which resulting in higher fault interaction prediction accuracy. After that, Coverage-based Test Suites Prioritization is performed to prioritize test suites best in terms of coverage and therefore provides global coverage for finding faults in software programs. Finally, Similarity-based Test Suite Selection is performed to reduce the number of test suites for detecting maximum number of faults in software programs which in turn helps for improving the software system quality. The CFOP-CP technique conducts the experimental works on parameters such as fault interaction prediction accuracy, testing cost and coverage rate. The experimental result shows that the CFOP-CP technique is able to improve the coverage rate for software fault detection and also reduces the testing cost for improving the software system quality when compared to state-of-the-art-works.

Keywords: Combinatorial Testing, Test Suite, Fault Interaction, Coverage, Test Cases, Prioritization