APPLICATION OF CLONAL SELECTION ALGORITHM IN SOFTWARE TEST DATA GENERATION

This paper presents an artificial immune system (AIS) based optimized test data generation technique. Software test data generation is a critical activity in software testing. Redundant test data impose an extra cost in form of more testing and increase in efforts. So the generation of effective test data can save time and efforts spent on extra testing of the software. Optimized test data is generated for critical paths of the program. Paths criticality is defined based on the presence of loops and decision. The clonal selection algorithm is an immune system based machine learning algorithm and generates optimized test data by the maturation of the affinity. Generated results indicate the effective application of clonal selection technique in software test data generation