GAPSO: Optimal Test Set Generator for Pairwise Testing
M. Lakshmi Prasad1, A. Raja Sekhar Reddy2, J.K.R. Sastry3
1Dr. M. Lakshmi Prasad, Department of CSE, NBKRIST, Nellore, India.
2Dr. A. Rajasekhar Reddy, Department of CSE, NBKRIST, Nellore, India.
3Dr. JKR Sastry, Department of ECSE, KL University, Guntur, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 2346-2350 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8645088619/2019©BEIESP | DOI: 10.35940/ijeat.F8645.088619
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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: Exhaustive testing is impossible for all sorts of software systems, owing to the cost and time consumption. Combinatorial testing is the solution to this issue and aims at picking the necessary set of parameters which can ensure high degree of interaction between the parameters. This paper presents a new approach for generating unique test cases by exploiting Genetic and Particle Swarm Optimization (GAPSO) algorithm for achieving pairwise testing. The generated test cases are refined, so as to arrive at the optimal test set. The outcome of the proposed algorithm is the minimal count of high quality test cases.
Keywords: Exhaustive testing, combinatorial testing, pairwise testing, genetic algorithm, particle swarm optimization.