An Evolutionary Regression Test Case Prioritization based on Dependence Graph and Genetic Algorithm for Object-Oriented Programs

 Abstract— Regression testing takes almost half of the cost of software maintenance, but it is very important process in software testing. Unfortunately, it may be costly to allow for the re-execution of all test cases during regression testing. The challenge in regression testing is the selection of best test cases from the existing test suite. This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model of the affected program using genetic algorithm. The approach is based on optimization of selected test case from dependency analysis of the source codes. The goal is to identify changes in a method's body due to data dependence, control dependence and dependent due to object relation such as inheritance and polymorphism, select the test cases based on affected statements and ordered them based on their fitness by using GA. The number of affected statements determined how fit a test case is good for regression testing. A case study will be reported to provide evidence of the feasibility of the approach and its benefits in increasing the rate of fault detection and reduction in regression testing effort.