Regression Test Case Prioritization Frameworks: Challenges and Future Directions

Abstract

Regression testing is a necessary maintenance activity in the software industry where modified software programs are revalidated to make sure that changes do not adversely affect their behavior. Test case prioritization (TCP) is one of the most effective methods in regression testing whereby test cases are rescheduled in an appropriate order for execution to increase test effectiveness in meeting some performance goals such as increasing the rate of fault detection. This paper explores efforts that have been carried out in relation to TCP frameworks. Through the review of related literature, ten existing frameworks were identified, classified and reviewed whereby two are Bayesian network-based, five are multi-objective, while the rest are varied in terms of aspects and purposes. Accordingly, this study analyzes those frameworks based on their proposed year, TCP factors, number of test cases used, evaluations metric and criteria as well as experimental subjects. The results showed that the stated frameworks are not integrated with nature-inspired algorithms as enhancing optimization techniques while several others were insufficiently evaluated according to stated evaluation criteria and metrics for the effective and practical testing process. There is also a scarcity of frameworks that focus on regression test efficiency. This study indicates the need for further research into the topic to enhance TCP frameworks that focus on several directions for practical considerations in this field such as evaluation issues, specific knowledge dependency, and objective deviation. At the end of this study, several future directions such as nature-inspired algorithms assistance are proposed, and a number of limitations are identified and highlighted.