Test Case Prioritization Based on Information Retrieval Concepts

In regression testing, running all a system´s test cases can require a great deal of time and resources. Test case prioritization (TCP) attempts to schedule test cases to achieve goals such as higher coverage or faster fault detection. While code coverage-based approaches are typical in TCP, recent work has explored the use of additional information to improve effectiveness. In this work, we explore the use of Information Retrieval (IR) techniques to improve the effectiveness of TCP, particularly for testing infrequently tested code. Our approach considers the frequency at which elements have been tested, in additional to traditional coverage information, balancing these factors using linear regression modeling. Our empirical study demonstrates that our approach is generally more effective than both random and traditional code coverage-based approaches, with improvements in rate of fault detection of up to 4.7%.