[HTML][HTML] How far are we from reproducible research on code smell detection? A systematic literature review

T Lewowski, L Madeyski - Information and Software Technology, 2022 - Elsevier
Context: Code smells are symptoms of wrong design decisions or coding shortcuts that may
increase defect rate and decrease maintainability. Research on code smells is accelerating …

[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 …

Predictive analytics and software defect severity: A systematic review and future directions

TO Olaleye, OT Arogundade, S Misra… - Scientific …, 2023 - Wiley Online Library
Software testing identifies defects in software products with varying multiplying effects based
on their severity levels and sequel to instant rectifications, hence the rate of a research study …

A survey on machine learning techniques for source code analysis

T Sharma, M Kechagia, S Georgiou, R Tiwari… - ar** study
OA Bastías, J Díaz, J López Fenner - Applied Sciences, 2023 - mdpi.com
While some areas of software engineering knowledge present great advances with respect
to the automation of processes, tools, and practices, areas such as software maintenance …

On the assessment of interactive detection of code smells in practice: A controlled experiment

D Albuquerque, E Guimarāes, M Perkusich… - IEEE …, 2023 - ieeexplore.ieee.org
Code smells are structures in a program that often indicate the presence of deeper
maintainability problems. Code smells should be detected as soon as they are introduced …