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access icon free DIV-TBAT algorithm for test suite reduction in software testing

© The Institution of Engineering and Technology
Received 01/07/2017, Accepted 09/03/2018, Revised 25/01/2018, Published 13/03/2018

Researchers have investigated different approaches to maintain the minimum cost and effort in regression testing. Here, test suite reduction is a common technique to decrease the cost of regression testing by removing the redundant test cases from the test suite and then, obtaining a representative set of test cases that still yield a high level of code coverage. Accordingly, here, the authors have developed two various techniques for test suite reduction. In the first technique, ATAP measure is newly developed to find the reduced test suite with the help of greedy search algorithm. In the second technique, DIV-TBAT (DIVersity-based BAT) algorithm is newly devised based on the mechanisms of Boolean logic within BAT algorithm which improve diversity during the search process. The proposed techniques are experimented using eight programs from SIR subject programs and the performance study is conducted using nine different evaluation metrics based on different research questions. The comparative analysis is performed with the existing algorithms like GreedyRatio, GreedyEIrreplaceability, diversity-based genetic algorithm, TBAT, and TAP, to prove the performance improvement over the eight software programs considered.

Inspec keywords: mathematics computing; search problems; greedy algorithms; program testing; software maintenance; genetic algorithms; Boolean functions

Other keywords: test suite reduction; software testing; greedy search algorithm; Boolean logic; reduced test suite; regression testing; DIV-TBAT algorithm; redundant test cases; ATAP measure

Subjects: Software engineering techniques; Mathematics computing; Optimisation techniques; Diagnostic, testing, debugging and evaluating systems

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