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Software smell detection techniques: A systematic literature review
Author(s) -
AbuHassan Amjad,
Alshayeb Mohammad,
Ghouti Lahouari
Publication year - 2021
Publication title -
journal of software: evolution and process
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 29
eISSN - 2047-7481
pISSN - 2047-7473
DOI - 10.1002/smr.2320
Subject(s) - code smell , computer science , software , software engineering , abstraction , code (set theory) , software design , systematic review , software development , software quality , programming language , philosophy , set (abstract data type) , epistemology , medline , political science , law
Software smells indicate design or code issues that might degrade the evolution and maintenance of software systems. Detecting and identifying these issues are challenging tasks. This paper explores, identifies, and analyzes the existing software smell detection techniques at design and code levels. We carried out a systematic literature review (SLR) to identify and collect 145 primary studies related to smell detection in software design and code. Based on these studies, we address several questions related to the analysis of the existing smell detection techniques in terms of abstraction level (design or code), targeted smells, used metrics, implementation, and validation. Our analysis identified several detection techniques categories. We observed that 57% of the studies did not use any performance measures, 41% of them omitted details on the targeted programing language, and the detection techniques were not validated in 14% of these studies. With respect to the abstraction level, only 18% of the studies addressed bad smell detection at the design level. This low coverage urges for more focus on bad smell detection at the design level to handle them at early stages. Finally, our SLR brings to the attention of the research community several opportunities for future research.