International Journal of Mathematical Sciences and Computing(IJMSC)

ISSN: 2310-9025 (Print), ISSN: 2310-9033 (Online)

Published By: MECS Press

IJMSC Vol.1, No.3, Sep. 2015

The Application of Meta-Heuristic Algorithms in Automatic Software Test Case Generation

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Maryam Mirzapour Moshizi, Amid Khatibi Bardsiri

Index Terms

Test Case Generation;Meta-Heuristic Algorithms;Software Test Case


Nowadays, software test is one of the most important activities that software's quality will be certified by it. Test operation includes program's implement on test case set and comparison of results with expected one. Manual test case for operation test program and error detect is time consuming with insufficient precision and complicated coverage of program, so, the use of algorithms in automatic test case generation has been considered. Meta-heuristic algorithms are known tools which are optimized and used in test case generation. Most of complicated matters need a lot of possible states assessment in order to reach the valid answer. With the proper answer, test case optimization and meta-heuristic algorithms play a constructive role. In this paper we would compare methods and their traits, and the software test case generation methods based on meta-heuristic algorithms with their description. 

Cite This Paper

Maryam Mirzapour Moshizi, Amid Khatibi Bardsiri,"The Application of Meta-Heuristic Algorithms in Automatic Software Test Case Generation", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.1, No.3, pp.1-8, 2015.DOI: 10.5815/ijmsc.2015.03.01


[1]Collofello, J. , Vehathiri, K, "An environment for training computer science students on software testing", Frontiers in Education, 2005. FIE '05. Proceedings 35th Annual Conference, pp T3E 6-T3E 10

[2]McMinn, " Search-Based Software Testing: Past, Present and Future", Software Testing, Verification and Validation Workshops (ICSTW), Fourth International Conference, 2011, pp 153-163

[3]Phil McMinn, "Search-based software test data generation" Software Testing, Verification and Reliability, Volume 14, Issue 2, 2004 , PP 105–156 

[4]Wang Jun, Zhuang Yan, Jianyun Chen, "Test Case Prioritization Technique based on Genetic Algorithm", International Conference on Internet Computing and Information Services, 2011, pp 173-175

[5]Sheng Zhang, Ying Zhang, Hong Zhou, Qingquan He, "Automatic Path Test Data Generation Based on GA-PSO" Intelligent Computing and Intelligent Systems (ICIS) International Conference, 2010, pp 142-146

[6]Soma Sekhara Babu lam, "Automated Generation of Independent Path and Test Suite Optimization Using Artificial Bee Colony", Procedia Engineering, Volume 30, 2012, pp 191–200

[7]Wang Lijuan, Zhai Yue, Hou Hongfeng, "Genetic Algorithms and Its Application in Software Test Data Generation", International Conference on Computer Science and Electronics Engineering, 2012, pp 617-620

[8]J.Albert Mayan, T Ravi, "Test Case Optimization Using Hybrid Search Technique", International Conference on Interdisciplinary Advances in Applied Computing, 2014, pp 1-7

[9]Praveen Ranjan Srivatsava, B. Mallikarjun, "Optimal test sequence generation using firefly algorithm", Swarm and Evolutionary Computation, Volume 8, 2013, pp 44-53

[10]Navdeep Koundal, Ankur Shukla, Mohsin Rashid Mir, "Test Case Selection Using Bee Colony Optimization", International Journal of Science and Research (IJSR), Volume 3, Issue 5, 2014, pp 1432-1436 

[11]Weixiang Zhang, Bo Wei, Huisen Du, " Test Case Prioritization Based on Genetic Algorithm and Test-Points Coverage", Algorithms and Architectures for Parallel Processing, volume 8630, 2014, pp 644-654.