PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support

Alazzawi, A.K. and Rais, H.M. and Basri, S. and Alsariera, Y.A. (2019) PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support. In: UNSPECIFIED.

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Abstract

Software testing becoming significant part of our daily life due to a software-development process that led to increase the components number and the associated time. Due to the financial resources and time constraints, practically exhaustive testing is hopeless. For this reason, numerous researchers have adopted pairwise testing to decrease the exhaustive number of test cases. Pairwise testing is one of a powerful Combinatorial Testing Technique (CTT) that used widely for test data generation. Various existing research works were developed using a meta-heuristic algorithm as a basis for pairwise testing strategies. Supplementing to earlier research work, this paper proposed a new pairwise test suite generation called pairwise hybrid artificial bee colony (PhABC) strategy based on hybridize of an artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. The output of PhABC is a set of promising optimal test set combinations. The results of the experiments showed that PhABC outperformed and yielded better test sets than other existing other research strategies even with the existing constraints. © 2019 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 13; Conference of 17th IEEE Student Conference on Research and Development, SCOReD 2019 ; Conference Date: 15 October 2019 Through 17 October 2019; Conference Code:154444
Uncontrolled Keywords: Heuristic algorithms; Particle swarm optimization (PSO); Software design; Testing, Artificial bee colonies; Meta heuristics; Optimization problems; Pair-wise Testing; T-way testing, Software testing
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 10 Nov 2023 03:25
Last Modified: 10 Nov 2023 03:25
URI: https://khub.utp.edu.my/scholars/id/eprint/11252

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