Building Ant System for Multi-Faceted Test Case Prioritization

Author:

Pachariya Manoj Kumar1

Affiliation:

1. MCNUJC, Bhopal, Madhya Pradesh, India

Abstract

This article presents the empirical study of multi-criteria test case prioritization. In this article, a test case prioritization problem with time constraints is being solved by using the ant colony optimization (ACO) approach. The ACO is a meta-heuristic and nature-inspired approach that has been applied for the statement of a coverage-based test case prioritization problem. The proposed approach ranks test cases using statement coverage as a fitness criteria and the execution time as a constraint. The proposed approach is implemented in MatLab and validated on widely used benchmark dataset, freely available on the Software Infrastructure Repository (SIR). The results of experimental study show that the proposed ACO based approach provides near optimal solution to test case prioritization problem.

Publisher

IGI Global

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Networks and Communications,Computer Science Applications,Software

Reference29 articles.

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4. Dorigo, M., & Socha, K. (2007). An Introduction to Ant Colony Optimization. CRC Press.

5. Empirical evaluation of pareto efficient multi-objective regression test case prioritisation.;M. G.Epitropakis;Proceedings of the 2015 International Symposium on Software Testing and Analysis,2015

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1. Exploring Better Black-Box Test Case Prioritization via Log Analysis;ACM Transactions on Software Engineering and Methodology;2023-04-26

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