Detection approaches for android malware: Taxonomy and review analysis
HHR Manzil, SM Naik - Expert Systems with Applications, 2024 - Elsevier
The main objective of this review is to present an in-depth study of Android malware
detection approaches. This article provides a comprehensive survey of 150 studies on …
detection approaches. This article provides a comprehensive survey of 150 studies on …
Examining deep learning's capability to spot code smells: a systematic literature review
Code smells violate software development principles that make the software more prone to
errors and changes. Researchers have developed code smell detectors using manual and …
errors and changes. Researchers have developed code smell detectors using manual and …
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 …
Detecting refactoring type of software commit messages based on ensemble machine learning algorithms
Refactoring is a well-established topic in contemporary software engineering, focusing on
enhancing software's structural design without altering its external behavior. Commit …
enhancing software's structural design without altering its external behavior. Commit …
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 …
Fedcsd: A federated learning based approach for code-smell detection
Software quality is critical, as low quality, or “Code smell,” increases technical debt and
maintenance costs. There is a timely need for a collaborative model that detects and …
maintenance costs. There is a timely need for a collaborative model that detects and …
Analyzing various machine learning algorithms with smote and adasyn for image classification having imbalanced data
Oversampling is a strategy employed in machine learning to handle imbalanced datasets by
creating copies of the minority class instances to balance the dataset, thus reducing bias …
creating copies of the minority class instances to balance the dataset, thus reducing bias …
Revisiting" code smell severity classification using machine learning techniques"
In the context of limited maintenance resources, predicting the severity of code smells is
more practically useful than simply detecting them. Fontana et al. first empirically …
more practically useful than simply detecting them. Fontana et al. first empirically …
Exploring the role of project status information in effective code smell detection
Repairing code smells detected in the code or design of the system is one of the activities
contributing to increasing the software quality. In this study, we investigate the impact of non …
contributing to increasing the software quality. In this study, we investigate the impact of non …
Python code smell detection using machine learning
N Vatanapakorn, C Soomlek… - … Computer Science and …, 2022 - ieeexplore.ieee.org
Python is an increasingly popular programming language used in various software projects
and domains. Code smells in Python significantly influences the maintainability …
and domains. Code smells in Python significantly influences the maintainability …