Genetic Algorithm Approach to Optimize Test Cases
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2020 by IJETT Journal|
|Year of Publication : 2020|
|Authors : Baswaraju Swathi, Dr.Harshvardhan Tiwari
|DOI : 10.14445/22315381/IJETT-V68I10P219|
MLA Style: Baswaraju Swathi, Dr.Harshvardhan Tiwari "Genetic Algorithm Approach to Optimize Test Cases" International Journal of Engineering Trends and Technology 68.10(2020):112-116.
APA Style:Baswaraju Swathi, Dr.Harshvardhan Tiwari. Genetic Algorithm Approach to Optimize Test Cases International Journal of Engineering Trends and Technology, 68(10),112-116.
Test case generation is considered a significant and complex aspect in software testing, ensuring the quality of a software product. In a highly competitive environment, web applications have become crucial to most enterprises, demanding the application`s quality. The characteristics of such applications include client-server, distributed, and dynamic. Hence meticulous testing of a web-based application becomes necessary. Many strategies have been proposed to address the issues w.r.t test case generation for web applications. One such strategy is a Genetic Algorithm (GA), which is an evolutionary technique. In this paper, we analyze the test suit generation as a complex problem and derive the test cases with traditional test case generation approaches where the common generation problems are addressed with a case study. Further Genetic Algorithm approach, the parameters which can enhance the test case generation is proposed. The various encoding and selection techniques of GA are considered. The parameter of fitness function which determines the success of GA is analyzed. Finally the evaluation criteria code coverage is examined to assess the test effectiveness.
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code coverage, evolutionary technique, fitness function, Genetic Algorithm, test case generation