Automated software testing using a metaheuristic technique based on tabu search

• Published in: 18th IEEE International Conference on Automated Software Engineering, 2003. Proceedings pp. 310 - 313
• Main Authors: Díaz, Eugenia, Tuya, Javier, Blanco, Raquel
• Format: Conference Proceeding
• Language: English
• Published: Piscataway, NJ, USA IEEE Press 06.10.2003; IEEE
• Series: ACM Conferences
• Subjects: Automatic testing; Automation; Computer science; Computing methodologies; Computing methodologies > Artificial intelligence; Computing methodologies > Artificial intelligence > Search methodologies; Computing methodologies > Artificial intelligence > Search methodologies > Heuristic function construction; Costs; Genetic algorithms; Programming; Simulated annealing; Software and its engineering; Software and its engineering > Software creation and management; Software and its engineering > Software creation and management > Software verification and validation; Software and its engineering > Software creation and management > Software verification and validation > Software defect analysis; Software and its engineering > Software creation and management > Software verification and validation > Software defect analysis > Software testing and debugging; Software quality; Software testing; System testing; Theory of computation; Theory of computation > Design and analysis of algorithms; Theory of computation > Design and analysis of algorithms > Data structures design and analysis; Theory of computation > Design and analysis of algorithms > Data structures design and analysis > Sorting and searching
• ISBN: 0769520359; 9780769520353
• ISSN: 1938-4300
• DOI: 10.1109/ASE.2003.1240327

The use of techniques for automating the generation of software test cases is very important as it can reduce the time and cost of this process. The latest methods for automatic generation of tests use metaheuristic search techniques, i.e. Genetic Algorithms and Simulated Annealing. There is a great deal of research into the use of Genetic Algorithms to obtain a specific coverage in software testing but there is none using the metaheuristic Tabu Search technique. In this paper, we explain how we have created an efficient testing technique that combines Tabu Search with Korel's chaining approach. Our technique automatically generates test data in order to obtain branch coverage in software testing.