Automated Generation of Independent Paths and Test Suite Optimization Using Artificial Bee Colony

Abstract

Software test suite optimization is one of the most important problems in software engineering research. This paper deals with Automatic Generation of Feasible Independent Paths and Software Test Suite Optimization using Artificial Bee Colony (ABC) based novel search technique. In this approach, ABC combines both global search methods done by scout bees and local search method done by employed bees and onlooker bees. The parallel behavior of these three bees makes generation of feasible independent paths and software test suite optimization faster. Test Cases are generated using Test Path Sequence Comparison Method as the fitness value objective function. This paper also presents an approach for the automated generation of feasible independent test path based on the priority of all edge coverage criteria. Finally, this paper compares the efficiency of ABC based approach with various approaches.