Generating Pairwise Combinatorial Interaction Test Suites Using Single Objective Dragonfly Optimisation Algorithm

TL;DR

This paper introduces a new method for generating pairwise combinatorial test suites using a novel swarm intelligence algorithm called Dragonfly, demonstrating its efficiency and potential for software testing.

Contribution

It presents a new technique for pairwise test suite generation and adapts the Dragonfly optimization algorithm for this purpose, with extensive evaluation.

Findings

Efficient generation of pairwise test suites.

Dragonfly algorithm outperforms existing methods.

Effective in detecting software faults.

Abstract

Combinatorial interaction testing has been addressed as an effective software testing technique recently. It shows its ability to reduce the number of test cases that have to be considered for software-under-test by taking the combinations of parameters as an interaction of input. This combination could be considered as input-configuration of different software families. Pairwise combinatorial test suite takes the interaction of two input parameters into consideration instead of many parameter interactions. Evidence showed that this test suite could detect most of the faults in the software-under-test as compared to higher interactions. This paper presents a new technique to generate pairwise combinatorial test suites. Also, Dragon Fly (DF), a new swarm intelligent optimization algorithm, is assessed. The design and adaptation of the algorithm are addresses in the paper in detail. The algorithm is evaluated extensively through different experiments and benchmarks. The evaluation shows the efficiency of the proposed technique for test suite generation and the usefulness of DF optimization algorithm for future investigations.