Publication in conference proceedings
Code Review with Large Language Models
Rajdev Kumar (Kumar, R.); Carlos Coutinho (Coutinho, C.);
Proceedings of the International Conference on Electrical and Computer Engineering Researches (ICECER2025)
Year (definitive publication)
2026
Language
English
Country
Madagascar
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Times Cited: 0

(Last checked: 2026-03-15 11:06)

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Abstract
With the recent rise of conversational AI (Artificial Intelligence) models, such as ChatGPT, it is essential to understand how these models can be used to complete tasks faster and more efficiently. Large Language Models (LLMs) can assist software developers to solve a variety of problems such as completing missing portions of code, finding vulnerabilities in the code, styling the code. Therefore, these tools can be useful to accelerate the learning curve. This paper studies how LLMs can be used for code review by junior software developers. A code review aims to identify mistakes that a junior developer may pass and improve code’s readability. In this study a tool was built that uses the ChatGPT API to review code. The same pieces of code were reviewed using different prompts and different versions of ChatGPT model. The results indicate that, to use LLMs effectively for code review, the prompt alone is not enough, there should also be used the model with the higher number of parameters to obtain better reviews.
Acknowledgements
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Keywords
LLM,AI,Junior,Developer,Software,Development,ChatGPT,API,Review
  • Computer and Information Sciences - Natural Sciences
  • Electrical Engineering, Electronic Engineering, Information Engineering - Engineering and Technology
Funding Records
Funding Reference Funding Entity
UIDB/04466/2023 FCT
UIDP/04466/2023 FCT

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