Deep learning-based software engineering: progress, challenges, and opportunities
Researchers have recently achieved significant advances in deep learning techniques,
which in turn has substantially advanced other research disciplines, such as natural …
which in turn has substantially advanced other research disciplines, such as natural …
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …
large amount of data to achieve exceptional performance. Unfortunately, many applications …
Deep learning approaches for bad smell detection: a systematic literature review
Context Bad smells negatively impact software quality metrics such as understandability,
reusability, and maintainability. Reduced costs and enhanced software quality can be …
reusability, and maintainability. Reduced costs and enhanced software quality can be …
Neural transfer learning for repairing security vulnerabilities in c code
Z Chen, S Kommrusch… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In this paper, we address the problem of automatic repair of software vulnerabilities with
deep learning. The major problem with data-driven vulnerability repair is that the few …
deep learning. The major problem with data-driven vulnerability repair is that the few …
A survey on machine learning techniques for source code analysis
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …
these techniques to a myriad of software engineering tasks that use source code analysis …
DeleSmell: Code smell detection based on deep learning and latent semantic analysis
Y Zhang, C Ge, S Hong, R Tian, C Dong… - Knowledge-Based Systems, 2022 - Elsevier
The presence of code smells will increase the risk of failure, make software difficult to
maintain, and introduce potential technique debt in the future. Although many deep-learning …
maintain, and introduce potential technique debt in the future. Although many deep-learning …
Code smell detection using ensemble machine learning algorithms
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. To …
development, especially in the design and coding phase. It leads to low maintainability. To …
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 …
[HTML][HTML] A survey on machine learning techniques applied to source code
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …
these techniques to a myriad of software engineering tasks that use source code analysis …
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 …