Multi-label learning for identifying co-occurring class code smells

M Hadj-Kacem, N Bouassida - Computing, 2024 - Springer
Code smell identification is crucial in software maintenance. The existing literature mostly
focuses on single code smell identification. However, in practice, a software artefact typically …

Hybrid model with multi-level code representation for multi-label code smell detection (077)

Y Li, A Liu, L Zhao, X Zhang - International Journal of Software …, 2022 - World Scientific
Code smell is an indicator of potential problems in a software design that have a negative
impact on readability and maintainability. Hence, detecting code smells in a timely and …

Code smell detection using multi-label classification approach

T Guggulothu, SA Moiz - Software Quality Journal, 2020 - Springer
Code smells are characteristics of the software that indicates a code or design problem
which can make software hard to understand, evolve, and maintain. There are several code …

Prompt Learning for Multi-Label Code Smell Detection: A Promising Approach

H Liu, Y Zhang, V Saikrishna, Q Tian… - arXiv preprint arXiv …, 2024 - arxiv.org
Code smells indicate the potential problems of software quality so that developers can
identify refactoring opportunities by detecting code smells. State-of-the-art approaches …

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 …

Actionable code smell identification with fusion learning of metrics and semantics

D Yu, Q Yang, X Chen, J Chen, S Wang, Y Xu - Science of Computer …, 2024 - Elsevier
Code smell detection is one of the essential tasks in the field of software engineering.
Identifying whether a code snippet has a code smell is subjective and varies by …

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 …

Code smell severity classification using machine learning techniques

FA Fontana, M Zanoni - Knowledge-Based Systems, 2017 - Elsevier
Several code smells detection tools have been developed providing different results,
because smells can be subjectively interpreted and hence detected in different ways …

Tuning Code Smell Prediction Models: A Replication Study

HG Nunes, A Santana, E Figueiredo… - Proceedings of the 32nd …, 2024 - dl.acm.org
Identifying code smells in projects is a non-trivial task, and it is often a subjective activity
since developers have different understandings about them. The use of machine learning …

An Evaluation of Multi-Label Classification Approaches for Method-Level Code Smells Detection

PS Yadav, RS Rao, A Mishra - IEEE Access, 2024 - ieeexplore.ieee.org
(1) Background: Code smell is the most popular and reliable method for detecting potential
errors in code. In real-world circumstances, a single source code may have multiple code …