Detecting code smells using industry-relevant data

L Madeyski, T Lewowski - Information and Software Technology, 2023 - Elsevier
Context Code smells are patterns in source code associated with an increased defect rate
and a higher maintenance effort than usual, but without a clear definition. Code smells are …

Machine learning techniques for code smells detection: a systematic mapping study

FL Caram, BRDO Rodrigues… - … Journal of Software …, 2019 - World Scientific
Code smells or bad smells are an accepted approach to identify design flaws in the source
code. Although it has been explored by researchers, the interpretation of programmers is …

Comparing and experimenting machine learning techniques for code smell detection

F Arcelli Fontana, MV Mäntylä, M Zanoni… - Empirical Software …, 2016 - Springer
Several code smell detection tools have been developed providing different results,
because smells can be subjectively interpreted, and hence detected, in different ways. In this …

Evaluating the accuracy of machine learning algorithms on detecting code smells for different developers

M Hozano, N Antunes, B Fonseca… - … Conference on Enterprise …, 2017 - scitepress.org
Code smells indicate poor implementation choices that may hinder the system maintenance.
Their detection is important for the software quality improvement, but studies suggest that it …

[HTML][HTML] How far are we from reproducible research on code smell detection? A systematic literature review

T Lewowski, L Madeyski - Information and Software Technology, 2022 - Elsevier
Context: Code smells are symptoms of wrong design decisions or coding shortcuts that may
increase defect rate and decrease maintainability. Research on code smells is accelerating …

On the role of data balancing for machine learning-based code smell detection

F Pecorelli, D Di Nucci, C De Roover… - Proceedings of the 3rd …, 2019 - dl.acm.org
Code smells can compromise software quality in the long term by inducing technical debt.
For this reason, many approaches aimed at identifying these design flaws have been …

A preliminary study on the adequacy of static analysis warnings with respect to code smell prediction

S Lujan, F Pecorelli, F Palomba, A De Lucia… - Proceedings of the 4th …, 2020 - dl.acm.org
Code smells are poor implementation choices applied during software evolution that can
affect source code maintainability. While several heuristic-based approaches have been …

Machine learning techniques for code smell detection: A systematic literature review and meta-analysis

MI Azeem, F Palomba, L Shi, Q Wang - Information and Software …, 2019 - Elsevier
Background: Code smells indicate suboptimal design or implementation choices in the
source code that often lead it to be more change-and fault-prone. Researchers defined …

Comparing within-and cross-project machine learning algorithms for code smell detection

M De Stefano, F Pecorelli, F Palomba… - Proceedings of the 5th …, 2021 - dl.acm.org
Code smells represent a well-known problem in software engineering, since they are a
notorious cause of loss of comprehensibility and maintainability. The most recent efforts in …

Machine learning techniques for code smells detection: An empirical experiment on a highly imbalanced setup

FC Luiz, BR de Oliveira Rodrigues… - Proceedings of the XV …, 2019 - dl.acm.org
Code smells, also known as code bad smells, are" a surface indication that usually
corresponds to a deeper problem in the system"[12]. Introduced by Fowler in 1999 [11] …