Automatic Test Case Generation For Performance Enhancement Of Software Through Genetic Algorithm And Random Testing

Autor:	Bright Keswani 1, Vikash Yadav 2
Rok vydání:	2018
Předmět:	Automatic test case generation Equivalence Class Partitioning Random Testing etc
DOI:	10.5281/zenodo.1135956
Popis:	Software testing is most effort consuming phase in software development. One would like to minimize the efforts and maximize the number of faults detected. Hence test case generation may be treated as an optimization problem. One of the major difficulties in software testing is the automatic generation of test data that satisfy a given adequacy criterion. Generating test cases automatically will reduce cost and efforts significantly. In this paper, test case data is generated automatically using Genetic Algorithms and results are compared with Random Testing. It is observed that Genetic Algorithms outperforms Random Testing.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e91a34f506e95e825f8126875da89b80 Zobrazit plný text záznamu