Mutated Specification-Based Test Data Generation with a Genetic Algorithm

Rong Wang, Yuji Sato and Shaoying Liu
Additional contact information
Rong Wang: Department of Computer Science, Hosei University, Tokyo 184-8584, Japan
Yuji Sato: Department of Computer Science, Hosei University, Tokyo 184-8584, Japan
Shaoying Liu: Graduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima 739-8511, Japan

Mathematics, 2021, vol. 9, issue 4, 1-19

Abstract: Specification-based testing methods generate test data without the knowledge of the structure of the program. However, the quality of these test data are not well ensured to detect bugs when non-functional changes are introduced to the program. To generate test data effectively, we propose a new method that combines formal specifications with the genetic algorithm (GA). In this method, formal specifications are reformed by GA in order to be used to generate input values that can kill as many mutants of the target program as possible. Two classic examples are presented to demonstrate how the method works. The result shows that the proposed method can help effectively generate test cases to kill the program mutants, which contributes to the further maintenance of software.

Keywords: test data generation; genetic algorithm; specification-based testing; regression testing; mutation testing (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/9/4/331/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/4/331/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:4:p:331-:d:495026

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().