A Hybrid Approach For Test Case Prioritization And Selection

Software testing consists in the dynamic verification of the behavior of a program on a set of test cases. When a program is modified, it must be tested to verify if the changes did not imply undesirable effects on its functionality. The rerunning of all test cases can be impossible, due to cost, time and resource constraints. So, it is required the creation of a test cases subset before the test execution. This is a hard problem and the use of standard Software Engineering techniques could not be suitable. This work presents an approach for test case prioritization and selection, based in relevant inputs obtained from a software development environment. The approach uses Software Quality Function Deployment (SQFD) to deploy the features relevance among the system components, Mamdani fuzzy inference systems to infer the criticality of each class and Ant Colony Optimization to select test cases. An evaluation of the approach is presented, using data from simulations with different number of tests.