- author = "Thaina Mariani and Silvia Regina Vergilio",
- title = "A systematic review on search-based refactoring",
- journal = "Information and Software Technology",
- year = "2017",
- volume = "83",
- pages = "14--34",
- month = mar,
- keywords = "genetic algorithms, genetic programming, SBSE, Search-based software engineering, Refactoring, Evolutionary algorithms",
- ISSN = "0950-5849",
-
DOI = "
doi:10.1016/j.infsof.2016.11.009",
-
URL = "
http://www.sciencedirect.com/science/article/pii/S0950584916303779",
- size = "21 pages",
-
abstract = "To find the best sequence of refactorings to be
applied in a software artefact is an optimization
problem that can be solved using search techniques, in
the field called Search-Based Refactoring (SBR). Over
the last years, the field has gained importance, and
many SBR approaches have appeared, arousing research
interest.
Objective: The objective of this paper is to provide an overview of existing SBR approaches, by presenting their common characteristics, and to identify trends and research opportunities. Method: A systematic review was conducted following a plan that includes the definition of research questions, selection criteria, a search string, and selection of search engines. 71 primary studies were selected, published in the last sixteen years. They were classified considering dimensions related to the main SBR elements, such as addressed artefacts, encoding, search technique, used metrics, available tools, and conducted evaluation.
Results: Some results show that code is the most addressed artifact, and evolutionary algorithms are the most employed search technique. Furthermore, most times, the generated solution is a sequence of refactorings. In this respect, the refactorings considered are usually the ones of the Fowler's Catalogue. Some trends and opportunities for future research include the use of models as artefacts, the use of many objectives, the study of the bad smells effect, and the use of hyper-heuristics.
Conclusions: We have found many SBR approaches, most of them published recently. The approaches are presented, analysed, and grouped following a classification scheme. The paper contributes to the SBR field as we identify a range of possibilities that serve as a basis to motivate future researches.",
- notes = "Brief mention of GP. Cites \cite{Jensen:2010:gecco}, \cite{langdon:2009:gecco3}",
