Meta-heuristic algorithm to generate optimised test cases for aspect-oriented software systems. (25th January 2021)

• Record Type: Journal Article
• Authors: Singhal, Abhishek; Bansal, Abhay; Kumar, Avadhesh
• Is Part Of: International journal of advanced intelligence paradigms. Volume 18:Number 2(2021)
• Page Start: 134
• Page End: 153
• Publication Date: 2021-01-25
• Subjects: aspect-oriented -- artificial bee colony algorithm -- genetic algorithm -- meta-heuristic -- optimisation -- test cases -- test case generation; Artificial intelligence -- Periodicals; Machine theory -- Periodicals; Fuzzy logic -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-0386

Abstract

Optimised test case generation is challenging for software industry. Test all approach is commonly used in software industry but it is not an effective approach in terms of computational cost. There exist literature available that show the applicability of meta-heuristic algorithm to address the issues, but the results received are not as perfect as it was expected, so scope of more optimised approaches still persists. In this paper, we propose an artificial bee colony based test case optimisation approach for aspect oriented software systems. Experiments are conducted using six benchmark problems, which validates the effectiveness of proposed approach. The results state the reduction of 20-40% number of test cases and more than 90% of code coverage in the optimised test suite, which shows the superiority of proposed approach. This clearly indicates that the computational time and complexity of the approach adopted shows remarkable improvement over GA.