Generating Software Test Data by Particle Swarm Optimization
- Authors
- Jia, Ya-Hui; Chen, Wei-Neng; Zhang, Jun; Li, Jing-Jing
- Issue Date
- Dec-2014
- Publisher
- Springer Verlag
- Keywords
- Particle swarm optimization; Automatic software test case generation; Software testing; Code coverage
- Citation
- Simulated Evolution and Learning 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, Proceedings, pp 37 - 47
- Pages
- 11
- Indexed
- SCIE
SCOPUS
- Journal Title
- Simulated Evolution and Learning 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, Proceedings
- Start Page
- 37
- End Page
- 47
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/116139
- DOI
- 10.1007/978-3-319-13563-2_4
- Abstract
- Search-based method using meta-heuristic algorithms is a hot topic in automatic test data generation. In this paper, we develop an automatic test data generating tool named particle swarm optimization data generation tool (PSODGT). The PSODGT is characterized by the following two features. First, the PSODGT adopts the condition-decision coverage (C/DC) as the criterion of software testing, aiming to build an efficient test data set that covers all conditions. Second, the PSODGT uses a particle swarm optimization (PSO) approach to generate test data set. In addition, a new position initialization technique is developed for PSO. Instead of initializing the test data randomly, the proposed technique uses the previously-found test data that can reach the target condition as the initial positions so that the search speed of PSODGT can be further accelerated. The PSODGT is tested on four practical programs. Experimental results show that the proposed PSO approach is promising.
- Files in This Item
-
- Appears in
Collections - COLLEGE OF ENGINEERING SCIENCES > SCHOOL OF ELECTRICAL ENGINEERING > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.