Value-based cost-cognizant test case prioritization for regression testing

by Farrukh Shahzad Ahmed, Awais Majeed, Tamim Ahmed Khan, Shahid Nazir Bhatti

Software Test Case Prioritization (TCP) is an effective approach for regression testing to tackle time and budget constraints. The major benefit of TCP is to save time through the prioritization of important test cases first. Existing TCP techniques can be categorized as value-neutral and value-based approaches. In a value-based fashion, the cost of test cases and severity of faults are considered whereas, in a value-neutral fashion these are not considered. The value-neutral fashion is dominant over value-based fashion, and it assumes that all test cases have equal cost and all software faults have equal severity. But this assumption rarely holds in practice. Therefore, value-neutral TCP techniques are prone to produce unsatisfactory results. To overcome this research gap, a paradigm shift is required from value-neutral to value-based TCP techniques. Currently, very limited work is done in a value-based fashion and to the best of the authors’ knowledge, no comprehensive review of value-based cost-cognizant TCP techniques is available in the literature. To address this problem, a systematic literature review (SLR) of value-based cost-cognizant TCP techniques is presented in this paper. The core objective of this study is to combine the overall knowledge related to value-based cost-cognizant TCP techniques and to highlight some open research problems of this domain. Initially, 165 papers were reviewed from the prominent research repositories. Among these 165 papers, 21 papers were selected by using defined inclusion/exclusion criteria and quality assessment procedures. The established questions are answered through a thorough analysis of the selected papers by comparing their research contributions in terms of the algorithm used, the performance evaluation metric, and the results validation method used. Total 12 papers used an algorithm for their technique but 9 papers didn’t use any algorithm. Particle Swarm Optimization (PSO) Algorithm is dominantly used. For results validation, 4 methods are used including, Empirical study, Experiment, Case study, and Industrial case study. The experiment method is dominantly used. Total 6 performance evaluation metrics are used and the APFDc metric is dominantly used. This SLR yields that value-orientation and cost cognition are vital in the TCP process to achieve its intended goals and there is great research potential in this research domain.