Evaluation of software product line test case prioritization technique

Software product line (SPL) engineering paradigm is commonly used to handle commonalities and variabilities of business applications to satisfy the specific needs or goal of a particular market. However, due to time and space complexities, testing all products is not feasible, and SPL testing is pro...

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Bibliographic Details
Main Authors: Sahak, M., Halim, S. A., Jawawi, D. N. A., Isa, M. A.
Format: Article
Published: Insight Society 2017
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Online Access:http://eprints.utm.my/id/eprint/76364/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033337404&partnerID=40&md5=acd780fa05e80041eec79ec7306e8973
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Summary:Software product line (SPL) engineering paradigm is commonly used to handle commonalities and variabilities of business applications to satisfy the specific needs or goal of a particular market. However, due to time and space complexities, testing all products is not feasible, and SPL testing is proven to be difficult due to a combinatorial explosion of the number of products to be considered. Combinatorial interaction testing (CIT) is suggested to reduce the size of test suites to overcome budget limitations and deadlines. CIT is conducted to fulfill certain quality attributes. This method can be further improvised through the prioritization of list configuration generated from CIT to gain better results in terms of efficiency and scalability, However, to the best of our knowledge, not much research has been done to evaluate existing Test Case Prioritization (TCP) techniques in SPL. This paper provides a survey of existing works on test case prioritization technique. This study provides classification and compares the best technique, trends, gaps and proposed frameworks based on the literature. The evaluation and discussion are using Normative Information Model-based Systems Analysis and Design (NIMSAD) on aspects that include context, content, and validation. The discussion highlights the lack of technique for scalability issue in SPL with most of the work is on academia setting but not on industrial practices.