28 citations · 43 across the 5 of their papers we have counts for
5 papers
AI-Powered, But Power-Hungry? Energy Efficiency of LLM-Generated Code
Lola Solovyeva, Sophie Weidmann, Fernando Castor
Large language models (LLMs) are used in software development to assist in various tasks, e.g., code generation and code completion, but empirical evaluations of the quality of the…
Language Models in Software Development Tasks: An Experimental Analysis of Energy and Accuracy
Negar Alizadeh, Boris Belchev, Nishant Saurabh +2
The use of generative AI-based coding assistants like ChatGPT and Github Copilot is a reality in contemporary software development. Many of these tools are provided as remote APIs.…
Understanding Code Understandability Improvements in Code Reviews
Delano Oliveira, Reydne Santos, Benedito de Oliveira +3
Motivation: Code understandability is crucial in software development, as developers spend 58% to 70% of their time reading source code. Improving it can improve productivity and r…
Estimating the Energy Footprint of Software Systems: a Primer
Fernando Castor
In Green Software Development, quantifying the energy footprint of a software system is one of the most basic activities. This documents provides a high-level overview of how the e…
Green AI: A Preliminary Empirical Study on Energy Consumption in DL Models Across Different Runtime Infrastructures
Negar Alizadeh, Fernando Castor
Deep Learning (DL) frameworks such as PyTorch and TensorFlow include runtime infrastructures responsible for executing trained models on target hardware, managing memory, data tran…