A survey on machine learning techniques for source code analysis

T Sharma, M Kechagia, S Georgiou, R Tiwari… - arXiv preprint arXiv …, 2021 - arxiv.org
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 …

[HTML][HTML] A survey on machine learning techniques applied to source code

T Sharma, M Kechagia, S Georgiou, R Tiwari… - Journal of Systems and …, 2024 - Elsevier
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 …

Machine learning-based exploration of the impact of move method refactoring on object-oriented software quality attributes

J Al Dallal, H Abdulsalam, M AlMarzouq… - Arabian Journal for …, 2024 - Springer
Refactoring is a maintenance task that aims at enhancing the quality of a software's source
code by restructuring it without affecting the external behavior. Move method refactoring …

Rmove: recommending move method refactoring opportunities using structural and semantic representations of code

D Cui, S Wang, Y Luo, X Li, J Dai… - … and Evolution (ICSME …, 2022 - ieeexplore.ieee.org
Incorrect placement of methods within classes is a typical code smell called Feature Envy,
which causes additional maintenance and cost during evolution. To remove this design flaw …

Automatic refactoring candidate identification leveraging effective code representation

I Palit, G Shetty, H Arif, T Sharma - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
The use of machine learning to automate the detection of refactoring candidates is a rapidly
evolving research area. The majority of work in this direction uses source code metrics and …

All you need is logs: Improving code completion by learning from anonymous ide usage logs

V Bibaev, A Kalina, V Lomshakov, Y Golubev… - Proceedings of the 30th …, 2022 - dl.acm.org
In this work, we propose an approach for collecting completion usage logs from the users in
an IDE and using them to train a machine learning based model for ranking completion …

Deep Learning Based Feature Envy Detection Boosted by Real-World Examples

B Liu, H Liu, G Li, N Niu, Z Xu, Y Wang, Y Xia… - Proceedings of the 31st …, 2023 - dl.acm.org
Feature envy is one of the well-recognized code smells that should be removed by software
refactoring. A major challenge in feature envy detection is that traditional approaches are …

A Survey of Deep Learning Based Software Refactoring

B Nyirongo, Y Jiang, H Jiang, H Liu - arXiv preprint arXiv:2404.19226, 2024 - arxiv.org
Refactoring is one of the most important activities in software engineering which is used to
improve the quality of a software system. With the advancement of deep learning …

Local and global feature based explainable feature envy detection

X Yin, C Shi, S Zhao - 2021 IEEE 45th Annual Computers …, 2021 - ieeexplore.ieee.org
Code smell detection can help developers identify position of code smell in projects and
enhance the quality of software system. Usually codes with similar semantic relationships …

[PDF][PDF] Detecting and resolving feature envy through automated machine learning and move method refactoring

D Al-Fraihat, Y Sharrab, AR Al-Ghuwairi… - International Journal of …, 2024 - academia.edu
Efficiently identifying and resolving code smells enhances software project quality. This
paper presents a novel solution, utilizing automated machine learning (AutoML) techniques …