Software Test Case Reduction using Genetic Algorithm A Modified Approach
Software test cases play an important role in Software Testing. A lot of test cases are developed while designing test cases that are of no use or redundant in nature. These types of test cases increase the effort and cost involved in testing and results in decrease of software testing efficiency. In this paper, a Genetic Algorithm based methodology has been proposed which can significantly reduce the test suite and leads to optimization of the efficiency of software testing. The testing efficiency can be increased by identifying the most critical paths. The proposed Genetic Algorithm based approach select the software path clusters that are weighted in accordance with the criticality of the path. Proposed algorithm has been evaluated by applying simple Genetic Algorithm and Fitness Scaling on a case study. GA with Fitness scaling helps in improving the efficiency of software testing by effectively reducing software test cases.