Please use this identifier to cite or link to this item:
Title: Avaluació dels LLM per la generació de codi
Author: Gallel, Carles  
Baró, Xavier  
Clarisó, Robert  
Abstract: Code generation using LLM is a burgeoning field following the popularity of tools such as ChatGPT or GitHub Copilot. With these tools, a programmer can significantly reduce the time it takes to develop code. However, there is no certainty that the generated code is correct. In this context, the objective of this study is to conduct an assessment that allows the evaluation of the quality of the generated code when applying different methodologies. To achieve this, a plan has been defined with several specific tasks. Specifically, this tasks are: 1. A study of the state of the art, contextualizing the current situation of the field of code generation using LLM. 2. The design and development of a prototype, which allows the execution of all the necessary tests by sending queries to the LLM API. 3. Analysis of the results obtained, conducting a comparative study on all the results obtained by applying the different methodologies. As a result, some conclusions will be reached that will allow to determine of the viability of the use of these methodologies in code generation with LLM and, additionally, will allow the identification of current shortcomings and potential improvements to be developed in the future.
Keywords: Intel·ligència artificial
generació de codi
Type: info:eu-repo/semantics/bachelorThesis
Issue Date: 20-Jun-2023
Publication license:
Appears in Collections:Bachelor thesis, research projects, etc.

Files in This Item:
File Description SizeFormat 
thesis.pdfMemòria del TFG2,03 MBAdobe PDFThumbnail
View statistics

This item is licensed under aCreative Commons License Creative Commons