NDLI: Quality improvement and optimization of test cases:a hybrid genetic algorithm based approach

Content Provider	ACM Digital Library
Author	Mohan, V. Mala, D. Jeya
Abstract	Software development organizations spend considerable portion of their budget and time in testing related activities. The effectiveness of the verification and validation process depends upon the number of errors found and rectified before releasing the software to the customer side. This in turn depends upon the quality of test cases generated. The solution is to choose the most important and effective test cases and removing the redundant and unnecessary ones; which in turn leads to test case optimization. To achieve test case optimization, this paper proposed a heuristics guided population based search approach namely Hybrid Genetic Algorithm (HGA) which combines the features of Genetic Algorithm (GA) and Local Search (LS) techniques to reduce the number of test cases by improving the quality of test cases during the solution generation process. Also, to evaluate the performance of the proposed approach, a comparative study is conducted with Genetic Algorithm and Bacteriologic Algorithm (BA) and concluded that, the proposed HGA based approach produces better results.
Starting Page	1
Ending Page	14
Page Count	14
File Format	PDF
ISSN	01635948
DOI	10.1145/1764810.1764824
Journal	ACM SIGSOFT Software Engineering Notes (SOEN)
Volume Number	35
Issue Number	3
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1979-04-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Genetic algorithm (ga) Hybrid genetic algorithm (hga) Test case optimization Test case Quality Bacteriologic algorithm (ba)
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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