Programa de Pós-Graduação em Sistemas de Informação e Gestão do Conhecimento | Universidade FUMEC


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Test case prioritization approaches in regression testing: A systematic literature review

Publication date: Available online 1 September 2017
Source:Information and Software Technology
Author(s): Muhammad Khatibsyarbini, Mohd Adham Isa, Dayang N.A. Jawawi, Rooster Tumeng
ContextSoftware quality can be assured by going through software testing process. However, software testing phase is an expensive process as it consumes a longer time. By scheduling test cases execution order through a prioritization approach, software testing efficiency can be improved especially during regression testing.ObjectiveIt is a notable step to be taken in constructing important software testing environment so that a system’s commercial value can increase. The main idea of this review is to examine and classify the current test case prioritization approaches based on the articulated research questions.MethodSet of search keywords with appropriate repositories were utilized to extract most important studies that fulfill all the criteria defined and classified under journal, conference paper, symposiums and workshops categories. 69 primary studies were nominated from the review strategy.ResultsThere were 40 journal articles, 21 conference papers, three workshop articles, and five symposium articles collected from the primary studies. As for the result, it can be said that TCP approaches are still broadly open for improvements. Each approach in TCP has specified potential values, advantages, and limitation. Additionally, we found that variations in the starting point of TCP process among the approaches provide a different timeline and benefit to project manager to choose which approaches suite with the project schedule and available resources.ConclusionTest case prioritization has already been considerably discussed in the software testing domain. However, it is commonly learned that there are quite a number of existing prioritization techniques that can still be improved especially in data used and execution process for each approach.