Review of Evolutionary Optimization Algorithms for Test Case Minimization

Multi-objective test suite minimization problem is to select a set of test cases from the available test suite while optimizing the multi objectives like code coverage, cost and fault history.[1] Regression Test suite optimization is an effective technique to reduce time and cost of testing. Many researchers have used computational intelligence techniques to enhance the effectiveness of test suite. These approaches optimize test suite for a single objective. Introduction of nature inspired algorithms like GA, PSO and BFO may be used to optimize test suite for multi-objective selection criteria. Main focus of our approach is to find a test suite that is optimal for multi-objective regression testing.[2]