1 citations · 2 across the 4 of their papers we have counts for
4 papers
Designing Empirical Studies on LLM-Based Code Generation: Towards a Reference Framework
Nathalia Nascimento, Everton Guimaraes, Paulo Alencar
The rise of large language models (LLMs) has introduced transformative potential in automated code generation, addressing a wide range of software engineering challenges. However,…
Large Language Models in the Data Science Lifecycle: A Systematic Mapping Study
Sai Sanjna Chintakunta, Nathalia Nascimento, Everton Guimaraes
In recent years, Large Language Models (LLMs) have emerged as transformative tools across numerous domains, impacting how professionals approach complex analytical tasks. This syst…
Analyzing Prominent LLMs: An Empirical Study of Performance and Complexity in Solving LeetCode Problems
Everton Guimaraes, Nathalia Nascimento, Chandan Shivalingaiah +1
Large Language Models (LLMs) like ChatGPT, Copilot, Gemini, and DeepSeek are transforming software engineering by automating key tasks, including code generation, testing, and debu…
LLM4DS: Evaluating Large Language Models for Data Science Code Generation
Nathalia Nascimento, Everton Guimaraes, Sai Sanjna Chintakunta +1
The adoption of Large Language Models (LLMs) for code generation in data science offers substantial potential for enhancing tasks such as data manipulation, statistical analysis, a…