Identifying refactoring opportunities in object-oriented code: A systematic literature review

• Published in: Information and software technology Vol. 58; pp. 231 - 249
• Main Author: Al Dallal, Jehad
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.02.2015; Elsevier Science Ltd
• Subjects: Codes; Criteria; Digital libraries; Empirical analysis; Literature reviews; Object oriented; Object oriented programming; Pilots; Refactoring activity; Refactoring opportunity; Searching; Software engineering; Studies; Systematic literature review; Systematic review; Refactoring opportunity; Refactoring activity; Systematic literature review
• ISSN: 0950-5849; 1873-6025
• DOI: 10.1016/j.infsof.2014.08.002

Identifying refactoring opportunities in object-oriented code is an important stage that precedes the actual refactoring process. Several techniques have been proposed in the literature to identify opportunities for various refactoring activities. This paper provides a systematic literature review of existing studies identifying opportunities for code refactoring activities. We performed an automatic search of the relevant digital libraries for potentially relevant studies published through the end of 2013, performed pilot and author-based searches, and selected 47 primary studies (PSs) based on inclusion and exclusion criteria. The PSs were analyzed based on a number of criteria, including the refactoring activities, the approaches to refactoring opportunity identification, the empirical evaluation approaches, and the data sets used. The results indicate that research in the area of identifying refactoring opportunities is highly active. Most of the studies have been performed by academic researchers using nonindustrial data sets. Extract Class and Move Method were found to be the most frequently considered refactoring activities. The results show that researchers use six primary existing approaches to identify refactoring opportunities and six approaches to empirically evaluate the identification techniques. Most of the systems used in the evaluation process were open-source, which helps to make the studies repeatable. However, a relatively high percentage of the data sets used in the empirical evaluations were small, which limits the generality of the results. It would be beneficial to perform further studies that consider more refactoring activities, involve researchers from industry, and use large-scale and industrial-based systems.