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.
Index Terms—Genetic Algorithms, optimization,specification based software testing, soft computation
Kulvinder Singh is with Department of Computer Science and Engineering, University Institute of Engineering & Technology (U.I.E.T),Kurukshetra University, Kurukshetra (K.U.K), India- 136 119 (Phone:+91-94162-24353, E-mail: email@example.com).
Rakesh Kumar is with the Department of Computer Science and Applications (D.C.S.A), Kurukshetra University, Kurukshetra (K.U.K),India- 136 119(Phone: +91-98963-36145; e-mail: firstname.lastname@example.org)
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.