Results 11 to 20 of about 18,914 (252)

A study of dealing class imbalance problem with machine learning methods for code smell severity detection using PCA-based feature selection technique. [PDF]

Sci Rep, 2023
Detecting code smells may be highly helpful for reducing maintenance costs and raising source code quality. Code smells facilitate developers or researchers to understand several types of design flaws. Code smells with high severity can cause significant
Rao RS, Dewangan S, Mishra A, Gupta M.
europepmc   +2 more sources

Software Code Smell Prediction Model Using Shannon, Rényi and Tsallis Entropies. [PDF]

Entropy (Basel), 2018
The current era demands high quality software in a limited time period to achieve new goals and heights. To meet user requirements, the source codes undergo frequent modifications which can generate the bad smells in software that deteriorate the quality
Gupta A, Suri B, Kumar V, Misra S, Blažauskas T, Damaševičius R.   +5 more
europepmc   +2 more sources

Assessment of Code Smell for Predicting Class Change Proneness Using Machine Learning

IEEE Access, 2019
Assessment of code smell for predicting software change proneness is essential to ensure its significance in the area of software quality. While multiple studies have been conducted in this regard, the number of systems studied and the methods used in ...
Manju Khari, Le Hoang Son, Raghvendra Kumar   +2 more
exaly   +3 more sources

Dynamic stacking ensemble for cross-language code smell detection. [PDF]

PeerJ Comput Sci
Code smells refer to poor design and implementation choices by software engineers that might affect the overall software quality. Code smells detection using machine learning models has become a popular area to build effective models that are capable of ...
Aljamaan H.
europepmc   +3 more sources

SmellyCode++: Multi-Label Dataset for Code Smell Detection. [PDF]

Sci Data
Context: Code smells indicate poor software design, affecting maintainability. Accurate detection is vital for refactoring and quality improvement.
Alomari N, Alazba A, Aljamaan H, Alshayeb M.   +3 more
europepmc   +2 more sources

A Unified Multi-Label Code Smell Dataset for Code Smell Detection at Different Granularities

IEEE Access
Code smell detection is critical for maintaining software quality and enabling effective refactoring, yet much prior work identifies only one smell at a time.
Haneen M. Alhadeaf, Mubarak Alrashoud
openaire   +3 more sources

Code Smell Detection Using Ensemble Machine Learning Algorithms

Applied Sciences (Switzerland), 2022
Code smells are the result of not following software engineering principles during software development, especially in the design and coding phase. It leads to low maintainability.
Seema Dewangan, Alok Mishra, Manjari Gupta   +2 more
exaly   +3 more sources

Machine Learning-Based Methods for Code Smell Detection: A Survey

Applied Sciences (Switzerland)
Code smells are early warning signs of potential issues in software quality. Various techniques are used in code smell detection, including the Bayesian approach, rule-based automatic antipattern detection, antipattern identification utilizing B-splines,
Pravin Singh Yadav, Rajwant Singh Rao, Alok Mishra   +2 more
exaly   +3 more sources

Python code smells detection using conventional machine learning models [PDF]

PeerJ Computer Science, 2023
Code smells are poor code design or implementation that affect the code maintenance process and reduce the software quality. Therefore, code smell detection is important in software building.
Rana Sandouka, Hamoud Aljamaan
doaj   +2 more sources

Code Smell Detection Driven by Hybrid Feature Selection and Ensemble Learning [PDF]

Jisuanji gongcheng, 2022
Code smell is a software feature that violates basic design principles or coding standards.When introduced into a source code, code smell increases the cost and difficulty of its maintenance.Machine learning can outperform other code smell detection ...
AI Chenghao, GAO Jianhua, HUANG Zijie
doaj   +1 more source