A code coverage-based test suite reduction and prioritization framework

Abstract

Software testing is extensively used to ensure the development of a quality software system. The test suite size tends to increase by including new test cases due to software evolution. Consequently, the entire test suite cannot be executed considering budget and time limitations. Researchers have examined test suite reduction and prioritization techniques to address the test suite size problem. However, combination of these techniques can be useful for various regression testing situations. In this paper, we present a new code coverage-based test suite reduction and prioritization framework called TestOptimizer. The framework performs a suitable combination of TestFilter and St-Total techniques to determine optimal test cases, keeping in view of time restrictions. The performance of the proposed framework has been assessed using a case study. Results show that TestOptimizer can be beneficial to solve the test suite size problem within time constraints and has a profound impact on the required cost and effort of regression testing.