Metaheuristic Algorithm for State-Based Software Testing

Abstract

This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. We formulate the testing problem as an optimization problem and use a simulated annealing (SA) metaheuristic algorithm to generate test cases as sequences of events while keeping the test suite size reasonable. SA evolves a solution by minimizing an energy function that is based on testing objectives such as coverage, diversity, and continuity of events. The suggested method includes a “significance weight” assigned to events, which leads to important web pages and ensures coverage of relevant features by test cases. The experimental results demonstrate the effectiveness of simulated annealing and show that SA yields good results for testing web applications in comparison with other heuristics.