Title: Meta-heuristic algorithm to generate optimised test cases for aspect-oriented software systems

Authors: Abhishek Singhal; Abhay Bansal; Avadhesh Kumar

Addresses: Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University, Uttar Pradesh, Noida, India ' Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University, Uttar Pradesh, Noida, India ' School of Computing Science and Engineering, Galgotias University, Uttar Pradesh, Greater Noida, India

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.

Keywords: aspect-oriented; artificial bee colony algorithm; genetic algorithm; meta-heuristic; optimisation; test cases; test case generation.

DOI: 10.1504/IJAIP.2021.112901

International Journal of Advanced Intelligence Paradigms, 2021 Vol.18 No.2, pp.134 - 153

Received: 15 Mar 2017
Accepted: 28 Oct 2017
Published online: 09 Feb 2021 *

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