Automatic Test Data Generation for Mutation Testing Using Genetic Algorithms


The KIPS Transactions:PartD, Vol. 8, No. 1, pp. 81-87, Feb. 2001
10.3745/KIPSTD.2001.8.1.81,   PDF Download:

Abstract

One key goal of software testing is to generate a 'good' test data set, which is considered as the most difficult and time-consuming task. This paper discusses how genetic algorithms can be used for automatic generation of test data set for software testing. We employ mutation testing to show the effectiveness of genetic algorithms (GAs) in automatic test data generation. The approach presented in this paper is different from others in that the test generation process requires no knowledge of implementation details of a program under test. In addition, we have conducted some experiments and compared our approach with random testing which is also regarded as a black-box test generation technique to show its effectiveness.


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Cite this article
[IEEE Style]
I. S. Jung and B. M. Chang, "Automatic Test Data Generation for Mutation Testing Using Genetic Algorithms," The KIPS Transactions:PartD, vol. 8, no. 1, pp. 81-87, 2001. DOI: 10.3745/KIPSTD.2001.8.1.81.

[ACM Style]
In Sang Jung and Byeong Mo Chang. 2001. Automatic Test Data Generation for Mutation Testing Using Genetic Algorithms. The KIPS Transactions:PartD, 8, 1, (2001), 81-87. DOI: 10.3745/KIPSTD.2001.8.1.81.