26 citations · 29 across the 3 of their papers we have counts for
3 papers
cs.SE2021★ 26 cited
An Empirical Study on Predictability of Software Code Smell Using Deep Learning Models
Himanshu Gupta, Tanmay G. Kulkarni, Lov Kumar +2
Code Smell, similar to a bad smell, is a surface indication of something tainted but in terms of software writing practices. This metric is an indication of a deeper problem lies w…
cs.SE2021
Empirical Analysis on Effectiveness of NLP Methods for Predicting Code Smell
Himanshu Gupta, Abhiram Anand Gulanikar, Lov Kumar +1
A code smell is a surface indicator of an inherent problem in the system, most often due to deviation from standard coding practices on the developers part during the development p…
cs.SE2017★ 3 cited
A Comparative Study of Different Source Code Metrics and Machine Learning Algorithms for Predicting Change Proneness of Object Oriented Systems
Lov Kumar, Ashish Sureka
Change-prone classes or modules are defined as software components in the source code which are likely to change in the future. Change-proneness prediction is useful to the mainten…