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 …

On the adequacy of static analysis warnings with respect to code smell prediction

F Pecorelli, S Lujan, V Lenarduzzi, F Palomba… - Empirical Software …, 2022 - Springer
Code smells are poor implementation choices that developers apply while evolving source
code and that affect program maintainability. Multiple automated code smell detectors have …

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 …

Applying machine learning to customized smell detection: a multi-project study

D Oliveira, WKG Assunção, L Souza, W Oizumi… - Proceedings of the …, 2020 - dl.acm.org
Code smells are considered symptoms of poor implementation choices, which may hamper
the software maintainability. Hence, code smells should be detected as early as possible to …

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 …

Developer-driven code smell prioritization

F Pecorelli, F Palomba, F Khomh… - Proceedings of the 17th …, 2020 - dl.acm.org
Code smells are symptoms of poor implementation choices applied during software
evolution. While previous research has devoted effort in the definition of automated solutions …

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 …

[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 …

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 …