Cost aware test suite reduction algorithm for regression testing

Abstract

Regression testing is the process that a recent code change has not adversely affect the existing features. The re-running of all the test cases during regression testing is very expensive as it requires huge time and resources. Test case prioritization techniques are to schedule the test cases in accordance with some criteria such that important test cases are executed with that given period. This study presents test case prioritization using genetic algorithm and their effectiveness is measured using APFD. Then the prioritized test cases are reduced. Test suite reduction techniques aim at identifying and eliminating redundant test cases from test suites in order to reduce the total number of test cases to execute, thereby improving the efficiency of the software testing activity. Our aim is to reduce the cost by reducing the number of test suite after prioritization. MFTS algorithm is used to reduce the given test suite with maximum coverage and it improves the rate of fault detection effectiveness.