K-Step Crossover Method based on Genetic Algorithm for Test Suite Prioritization in Regression Testing

Software is an integration of numerous programming modules  (e.g., functions, procedures, legacy system, reusable components, etc.) tested and combined to build the entire module. However, some undesired faults may occur due a change in modules while performing validation verification. Retesting software costly affair terms money time. Therefore, avoid retesting of entire software, regression testing performed. In testing, earlier created test suite used retest system's modified Regression Testing works three manners; minimizing cases, selecting prioritizing cases. this paper, two-phase algorithm has been proposed that considers case selection prioritization technique for on several ranging from smaller line codes huge procedural language. A textual based differencing implemented selection. Program statements between two are utilized identify cases affect program statements. next step, by applying Genetic Algorithm code/condition coverage. operators: Crossover Mutation have applied over initial population (i.e. cases), taking coverage as fitness criterion provide prioritized suite. Prioritization can be both original reduced depending upon suite's size or need accuracy. obtained results, efficiency algorithms analyzed Average Percentage Code Coverage (APCC) with cost (APCCc). comparison approach also done previously methods it observed APCC & APCCc values achieve higher percentage faster contrast non-prioritized