A large empirical assessment of the role of data balancing in machine-learning-based code smell detection
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 …
For this reason, many approaches aimed at identifying these design flaws have been …
On the role of data balancing for machine learning-based code smell detection
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 …
For this reason, many approaches aimed at identifying these design flaws have been …
Machine learning techniques for code smell detection: A systematic literature review and meta-analysis
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 …
source code that often lead it to be more change-and fault-prone. Researchers defined …
A review on machine-learning based code smell detection techniques in object-oriented software system (s)
Background: Code smells are symptoms that something may be wrong in software systems
that can cause complications in maintaining software quality. In literature, there exist many …
that can cause complications in maintaining software quality. In literature, there exist many …
On the relative value of imbalanced learning for code smell detection
Machine learning‐based code smell detection (CSD) has been demonstrated to be a
valuable approach for improving software quality and enabling developers to identify …
valuable approach for improving software quality and enabling developers to identify …
Detecting code smells using machine learning techniques: Are we there yet?
Code smells are symptoms of poor design and implementation choices weighing heavily on
the quality of produced source code. During the last decades several code smell detection …
the quality of produced source code. During the last decades several code smell detection …
Code smell detection based on supervised learning models: A survey
Y Zhang, C Ge, H Liu, K Zheng - Neurocomputing, 2024 - Elsevier
Supervised learning-based code smell detection has become one of the dominant
approaches to identify code smell. Existing works optimize the process of code smell …
approaches to identify code smell. Existing works optimize the process of code smell …
Comparing and experimenting machine learning techniques for code smell detection
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 …
because smells can be subjectively interpreted, and hence detected, in different ways. In this …
Code smell detection by deep direct-learning and transfer-learning
T Sharma, V Efstathiou, P Louridas… - Journal of Systems and …, 2021 - Elsevier
Context: An excessive number of code smells make a software system hard to evolve and
maintain. Machine learning methods, in addition to metric-based and heuristic-based …
maintain. Machine learning methods, in addition to metric-based and heuristic-based …
Are you smelling it? Investigating how similar developers detect code smells
Context A code smell indicates a poor implementation choice that often worsens software
quality. Thus, code smell detection is an elementary technique to identify refactoring …
quality. Thus, code smell detection is an elementary technique to identify refactoring …