| Issue |
E3S Web Conf.
Volume 391, 2023
4th International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED-ICMPC 2023)
|
|
|---|---|---|
| Article Number | 01035 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/e3sconf/202339101035 | |
| Published online | 05 June 2023 | |
Information Retrieval Based Solutions for Software Engineering Tasks Using C Codebases
Information Technology, Gokaraju Rangaraju Institute of Engineering & Technology, Hyderabad
* Corresponding author: nishithadusa22@gmail.com
Comments are descriptions of laws that a human can understand fluently. It’s easier to identify important law blocks with comments. But, not everyone can write the comments duly. They aren’t streamlined along with the law. Having outdated comments in the law can affect confusion rather than explanation. This paper aims at removing comments which aren’t related to code and not useful using Natural Language Processing( NLP). NLP has come one of the most habituated ways in the analysis of textbooks. In NLP, comments are written from the surrounding code given, and Machine Learning algorithms are applied. A semantic analysis frame for comments using textual and structural features grounded on comment orders and code–comment correlation. A machine learning approach is used to determine whether comments are also consistent and not superfluous based on code and comment correlation.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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