doi: 10.7763/IJIMT.2010.V1.9
Optimization of Functional Testing using Genetic Algorithms
Kulvinder Singh1
,
Rakesh Kumar2
- 1Department of Computer Science and Engineering, University Institute of Engineering & Technology (U.I.E.T),Kurukshetra University, Kurukshetra (K.U.K), India- 136 119.
- 2Department of Computer Science and Applications (D.C.S.A), Kurukshetra University, Kurukshetra (K.U.K),India- 136 119
Abstract
Software system should be reliable and available failing which huge losses may incur. To achieve these objectives a thorough testing is required. Adequacy of test cases is the key to the success. This paper presents the study of optimization of software testing techniques by using Genetic Algorithms (GAs)and specification based testing. Some new categories of genetic codes are applied in some problem optimizations for the generation of reliable software test cases based on the specification of the software. These GAs have found their application in detecting errors in the software packages. Based on new genetic strategy and GAs symmetric code is developed. In the current paper, some key definitions of genetic transformation have been used viz. crossover, mutation and selection. Some of our research shows that genetic techniques have very important influence on the performance of software test cases.
Keywords
- Genetic Algorithms
- optimization
- specification based software testing
- soft computation
How to Cite
Kulvinder Singh and Rakesh Kumar, "Optimization of Functional Testing using Genetic Algorithms," International Journal of Innovation, Management and Technology, vol. 1, no. 1, pp. 43-46, 2010. https://doi.org/10.7763/IJIMT.2010.V1.9
Copyright & License
Copyright © 2010 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).