A Pairwise T-Way Test Suite Generation Strategy Using Gravitational Search Algorithm
This work addresses software testing efficiency for developers, but it is incremental as it builds on existing t-way strategies with a new optimization method.
The paper tackles the problem of generating efficient test suites for software testing by proposing a new pairwise t-way strategy called PGSAS, which uses the Gravitational Search Algorithm to reduce test suite size, with results showing it is competitive or outperforms existing strategies in some cases.
Software faults are commonly occurred due to interactions between one or more input parameters in complex software systems. Software test design techniques can be implemented to ensure the quality of the developed software. Exhaustive testing tests all possible test configurations; however, it is infeasible considering time and resource constraints. Pairwise t-way testing is a sampling strategy that focuses on testing every pair of parameter combination, effectively reducing the generated test size as opposed to testing exhaustively. In this paper, we propose a new pairwise t-way strategy called Pairwise Gravitational Search Algorithm Strategy (PGSAS). PGSAS utilizes Gravitational Search Algorithm (GSA) for generating optimal pairwise test suites. The performance of PGSAS is benchmarked against existing t-way strategies in terms of test suite size. Preliminary results showcase that PGSAS provides competitive results in most configurations and outshines other strategies in some cases.