Comparative analysis of BBBC and GSA algorithms for automated test data generation Using symbolic execution method |
Author(s): |
| Gurbaksh Singh , Department of Computer Science & Engineering, MMEC, M.M. University, Mullana, India; R.P. Garg, Department of Computer Science & Engineering, MMEC, M.M. University, Mullana, India |
Keywords: |
| Gravitational search algorithm, Big Bang Big Crunch, Symbolic Execution, Software Testing. |
Abstract |
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In recent years various heuristic optimization methods have been developed. in this paper compares two new meta-heuristic techniques namely Gravitational Search Algorithm (GSA) and Big-Bang Big-Crunch (BBBC) algorithms for automatic test case generation using path testing criterion in symbolic execution environment. We have experimented on two real world and benchmarked programs Triangle Classifier (TC) and Line-Rectangle Classifier (LRC) showing the applicability of these techniques in genuine testing environment. Result show that both algorithms perform well in comparison to random testing but fail to generate test cases where input domain size is large. |
Other Details |
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Paper ID: IJSRDV2I4397 Published in: Volume : 2, Issue : 4 Publication Date: 01/07/2014 Page(s): 684-687 |
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