CS-FuzGA-PTS: Maximizing fault detection through optimizing t-way test suite prioritization based on boundary value analysis - Abdullah, Nasser; Kader, Md Abdul; Alsewari, Abdulrahman A.; Suliman, Mohamed Fati; Abdullah, Nibras; Diaba, Sayawu Yakubu; Jabbar, Waheb A. (IEEE, 2024)
In the realm of software testing, resource limitations pose a significant challenge to ensuring comprehensive testing coverage. While there are numerous attempts to systematically generate test cases that maximize input coverage and fault detection, there remains an essential need for prioritizing test cases to ensure efficient utilization of resources. Given the important role of each individual test case in the overall testing process, a Prioritized Test Suite (PTS) plays a vital role in optimizing testing resources, achieving maximum fault detection, and providing comprehensive test coverage. This research addresses this need by proposing and implementing a new testing strategy called Cuckoo Search with Adaptive Fuzzy Logic-Controlled Genetic Algorithm Operators for Generating PTS (CS-FuzGA-PTS). CS-FuzGA-PTS aims to systematically generate PTS by utilizing t-way testing, boundary value analysis (BVA), and optimization techniques. CS-FuzGA-PTS employs T-way testing for test case reduction and ensures maximum input coverage. CS-FuzGA-PTS incorporates BVA to prioritize test cases based on their boundary values to identify potential defects that occur at the boundaries of input ranges, thereby optimizing the test execution efforts by focusing on high-priority cases. The core of CS-FuzGA-PTS lies in a new optimization algorithm called CS-FuzGA as a search algorithm. The algorithm integrates adaptive fuzzy logic-controlled Genetic Algorithm (GA) operators with Cuckoo Search (CS). By dynamically adjusting search behavior based on solutions diversity, CS-FuzGA enhances both exploration and exploitation, achieving an optimal balance between them through integrating GA operators into CS according to search requirements. The results obtained from the experiments provide insights into the effectiveness of CS-FuzGA-PTS in generating a PTS that can identify potential defects occurring at input boundaries. Moreover, CS-FuzGA-PTS outperforms existing strategies in terms of test reduction.