Automated Software Testing Using Metahurestic Technique Based on an Ant Colony Optimization

Abstract

Software testing is an important and valuable part of the software development life cycle. Due to time, cost and other circumstances, exhaustive testing is not feasible that's why there is a need to automate the testing process. Testing effectiveness can be achieved by the State Transition Testing (STT) which is commonly used in real time, embedded and web-based kinds of software systems. The tester's main job to test all the possible transitions in the system. This paper proposed an Ant Colony Optimization (ACO) technique for the automated and full coverage of all state-transitions in the system. Present paper approach generates test sequence in order to obtain the complete software coverage. This paper also discusses the comparison between two metaheuristic techniques (Genetic Algorithm and Ant Colony optimization) for transition based testing.