Hybrid swarm intelligence-based software testing techniques for improving quality of component based software

Being a time-consuming and costly activity, software testing always demands optimization automation. Software is an important activity to achieve quality customer satisfaction. This paper presents comparative evaluation of different hybrid automated techniques using the concepts soft computing for overall enhancement. A comparison between three automation carried out i.e., ant colony optimization-genetic algorithms (ACO-GA), artificial bee (ABC)-Naïve Bayes, ABC-GA along with parent approaches. The made by applying these selection minimized test suites thus reducing effort eliminating useless or redundant cases. experimental results prove efficiency approaches in scenarios. impact enhancement assessed terms defect density detection percentage.