Mirror Adaptive Random Testing by Static Partitioning
Kamelia Yousofi Barforoush1, Farhad Ramezani2, Homayun Motameni3
1Mrs. Kamelia Yousofi Barforoush Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari Iran.
2Mr. Farhad Ramezani Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari Iran.
3Dr. Homayun Motameni Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari Iran
Manuscript received on 9 May 2015 | Revised Manuscript received on 25 May 2015 | Manuscript Published on 30 May 2015 | PP: 12-16 | Volume-4 Issue-12, May 2015 | Retrieval Number: L20510541215/15©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Software’s are being used extensively and having a huge impact on humans life. Random testing as one of the simplest testing methods is being used to test software systems. Based on the rational that distributing test cases more evenly will result in having batter chance to reveal non-point pattern failure regions, various Adaptive Random Testing (ART) methods have been proposed. In this paper we propose mirror adaptive random testing by static partitioning which while having same computational overhead cost will have better performance compared with that of mirror adaptive random testing.
Keywords: Random Testing, Adaptive Random Testing, Mirror, Static Partitioning.
Scope of the Article: Approximation and Randomized Algorithms