Optimization of Mutation Testing Challenges to Fixing Faults

One of the challenges mutation testing is fixing faults. In debugging phase, all live mutants were repaired. Programs need high scores to be declared reliable program codes. Each test can allow identification multiple mutants. This what confuses faults process. The objective this research get shortest route so that it help in sorting mutant types during application improvement after testing. optimization needed considering number each problems related are very complex. It takes a suitable method find path by paying attention point. There 30 projects chosen randomly. operator mutations often killed when AOIU and COI. proposed for repair sequence ant colony system (ACS). selection using Ant Colony System algorithm resulted 1.528254. Meanwhile, if genetic used, score 1.767643. Optimization results helpful developers improving code Research states best order handling ACS. further developed with addition class-level cases which produced class operators. Class operators have different characteristics from traditional particular, requires changes structure, such as definition variables.