RefactorScore: Evaluating Refactor Prone Code

K Jesse, C Kuhmuench… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
We propose RefactorScore, an automatic evaluation metric for code. RefactorScore
computes the number of refactor prone locations on each token in a candidate file and maps …

[PDF][PDF] Code smells: A synthetic narrative review

P Kokol, M Kokol, S Zagoranski - arXiv preprint arXiv:2103.01088, 2021 - core.ac.uk
Code smells are symptoms of poor design and implementation choices, which might hinder
comprehension, increase code complexity and fault-proneness and decrease …

[HTML][HTML] A novel metric based detection of temporary field code smell and its empirical analysis

R Gupta, SK Singh - Journal of King Saud University-Computer and …, 2022 - Elsevier
Code smell causes side effects in the source code and impact the code quality. It is
beneficial to recognize code smells to improve software quality. Despite 22 classical code …

Identifying the severity of technical debt issues based on semantic and structural information

D Yu, S Li, X Chen, T Sun - Software Quality Journal, 2023 - Springer
Technical debt (TD) refers to the phenomenon that developers choose a compromise
solution from a short-term benefit perspective during design or architecture selection. TD …

Code smells in pull requests: An exploratory study

MI Azeem, S Shafiq, A Mashkoor… - Software: Practice and …, 2024 - Wiley Online Library
The quality of a pull request is the primary factor integrators consider for its acceptance or
rejection. Code smells indicate sub‐optimal design or implementation choices in the source …

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 …

Exploring architecture blueprints for prioritizing critical code anomalies: Experiences and tool support

E Guimaraes, S Vidal, A Garcia… - Software: Practice …, 2018 - Wiley Online Library
The manifestation of code anomalies in software systems often indicates symptoms of
architecture degradation. Several approaches have been proposed to detect such …

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 …

Towards a systematic approach to manual annotation of code smells

N Luburić, S Prokić, KG Grujić, J Slivka… - Authorea …, 2023 - techrxiv.org
This is a preprint of an article published in the Science of Computer Programming. The final
peer-reviewed publication is available online at: https://doi. org/10.1016/j. scico …

Application of Deep Learning for Code Smell Detection: Challenges and Opportunities

M Hadj-Kacem, N Bouassida - SN Computer Science, 2024 - Springer
Code smells are indicators of deeper problems in source code that affect the system
maintainability and evolution. Detecting code smells is crucial as a software maintenance …