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A Hybrid Artificial Bee Colony and Harmony Search Algorithm to Generate Covering Arrays for Pair-wise Testing
Author(s) -
Priti Bansal,
Sangeeta Sabharwal,
Nitish Mittal
Publication year - 2017
Publication title -
international journal of intelligent systems and applications
Language(s) - English
Resource type - Journals
eISSN - 2074-9058
pISSN - 2074-904X
DOI - 10.5815/ijisa.2017.08.07
Subject(s) - harmony search , computer science , benchmark (surveying) , algorithm , artificial bee colony algorithm , set (abstract data type) , cover (algebra) , software , heuristic , artificial intelligence , programming language , mechanical engineering , geodesy , engineering , geography
Combinatorial Interaction Testing (CIT) is a cost effective testing technique that aims to detect interaction faults generated as a result of interaction between components or parameters in a software system. CIT requires the generation of effective test sets that cover all possible t-way (t denotes the strength of testing) interactions between parameters. Covering array (CA) and mixed covering array (MCA) are often used to represent test sets. This paper presents a hybrid algorithm that integrates artificial bee colony algorithm (ABC) and harmony search algorithm (HS) to construct CAs for testing all 2-way interactions (pair-wise testing) in software systems. The performance of the proposed hybrid algorithm ABCHS-CAG is compared and analyzed by performing experiments on a set of benchmark problems on pair-wise testing. The results show that ABCHS-CAG generates smaller CAs than its greedy counterparts whereas its performance is comparable to the existing state-of-the-art meta-heuristic algorithms.

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