Simulated Annealing: An Experimental Application on Pairwise Testing
M.V.Prudhvi Raj1, Subhrakanta Panda2
1M.V. Prudhvi Raj, Birla Institute of Technology & Science, Pilani, Hyderabad Campus Hyderabad, Telengana.
2Subhrakanta Panda, Birla Institute of Technology & Science, Pilani, Hyderabad Campus Hyderabad, Telengana.
Manuscript received on 04 April 2019 | Revised Manuscript received on 11 April 2019 | Manuscript Published on 26 April 2019 | PP: 377-381| Volume-8 Issue-6S April 2019 | Retrieval Number: F61350486S19/19©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: Testing plays a vital role in Software industries. Of all the methods, Combinational Testing is most preferred due to its robust approach in testing each and every possible pair, triple or n-way of a configuration at least once. Most of the faults occurred through these interactions between components can be captured using pairwise Testing. Many of the existing research proposes novel methods which aims to find a test set of configurations to cover all the possible different pairs. The difficulty of solving this problem is demonstrated to be NP-Complete. In this paper we propose to deeply explore the usage of Simulated Annealing, a meta heuristic algorithm to pairwise testing that generates the least number of test configurations with the aim to cover all distinct pairs possible. Furthermore, we proposed a fitness function which is dynamic in nature. This provides us the flexibility of choice between the runtime of this algorithm and the different pairs coverage of the test configurations generated. An ideal scenario would be a combination of both (runtime and coverage), but the results show that they are inversely related.
Keywords: Meta-Heuristic Algorithms, Simulated Annealing, Combinatorial Testing, Pairwise Testing.
Scope of the Article: Recent Trends & Developments in Computer Networks