Test Case Generation Using Adequacy-Based Genetic Algorithm

Abstract

Generating test cases is one of the most time- and effort-consuming problems in software testing. Many efforts have been made to automate this problem so as to make the procedure of software testing more efficient. The major part of these solutions involves the use of evolutionary techniques. Genetic algorithm is associated with automating the problem of test case generation since early 1990s. This paper presents an alternative way of using genetic algorithm for test case generation. It involves adequacy-based approach where the mutants are incorporated into the source code while generating the test cases. This approach will not only help in producing efficient results but also will reduce ample amount of time taken in the process. The results show that the intended approach undergoes an effective decline in the obtained number of test cases when compared to the path testing approach.