A prioritization approach for software test cases based on bayesian networks

Abstract

An important aspect of regression testing is to prioritize the test cases which need to be ordered to execute based on specific criteria. This research work presents a novel approach to prioritizing test cases in order to enhance the rate of fault detection. Our approach is based on probability theory and utilizes Bayesian Networks (BN) to incorporate source code changes, software fault-proneness, and test coverage data into a unified model. As a proof of concept, the proposed approach is applied to eight consecutive versions of a large-size software system. The obtained results indicate a significant increase in the rate of fault detection when a reasonable number of faults are available. © Springer-Verlag Berlin Heidelberg 2007.