Optimized Test Coverage With Hybrid Particle Swarm Bee Colony And Firefly Cuckoo Search Algorithms In Model Based Software Testing

Abstract

Software testing process is a very vital process in the software industry to obtain high quality software. From last four decades, several techniques for software testing were recommended to guarantee high-quality software delivery by satisfying all the client requirements. Model-based testing is a great breakthrough in the field of software test automation and is based on the automatic test case generation through various models. Though we have several model based testing models available in the literature, in this research an optimized novel hybrid approach is proposed by using Particle swarm bee colony and Firefly cuckoo search algorithms. One of the best substantial advantages of the proposed model is that it optimizes time and cost involved in software testing process. By using this approach, we can ensure automatic test case creation and execution to make the overall testing process more efficient by reducing the errors. Another improvement of the proposed work is that it produces the required number of test cases to test and ensure the system that it works perfectly and never undergo undesirable performance. Obtaining required number of test cases is promoting the proposed model towards cost optimization in software testing.