DocumentCode :
2459633
Title :
Comparison study of optimized test suite generation using Genetic and Memetic algorithm
Author :
Mundade, Ankita A. ; Pattewar, Tareek M.
Author_Institution :
Dept. of Comput. Eng., SES´s R. C. Patel Inst. of Technol., Shirpur, India
fYear :
2015
fDate :
8-10 Jan. 2015
Firstpage :
1
Lastpage :
5
Abstract :
Testing is one of the important phase of software engineering field, which checks the correctness of software. A common part in software testing is that test data are generated. For this test data, tester manually adds different test cases. But adding test cases manually is very difficult task. So we generate set of test cases called as test suite. Test case is nothing but a condition which we want to check. Code coverage is important factor in test suite. While generating a test suite, consider a inheritance tree a of class and generate test cases by considering all branches of that tree. Test case may have more than one goal, check feasibility for this particular goal. For generating optimized test suite, apply Genetic and Memetic algorithm. The aim of this test suite generation is covering all branches for maximum code coverage while keeping the minimum size. Applying both algorithms for code coverage. Code coverage of Memetic algorithm is maximum than code coverage of Genetic algorithm. We have implemented this system and for checking result use open source project such as Roops and net.
Keywords :
genetic algorithms; program testing; public domain software; code coverage; genetic algorithm; inheritance tree; memetic algorithm; open source project; optimized test suite generation; software correctness; software engineering field; software testing; test data generation; Genetic algorithms; Genetics; Memetics; Software; Software algorithms; Software testing; Genetic algorithm; Memetic algorithm; Software testing; code coverage; test suite;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Computing (ICPC), 2015 International Conference on
Conference_Location :
Pune
Type :
conf
DOI :
10.1109/PERVASIVE.2015.7087175
Filename :
7087175
Link To Document :
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