Energy Impact of Class-Level Code Smells in AI-based Applications

• Grant number: 25/04369-6
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: June 01, 2025
• End date: May 31, 2026
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Markus Endler
• Grantee: Izadora de Paula Santos Lima
• Host Institution: Centro Técnico Científico (CTC). Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio)
• Associated research grant: 23/00811-0 - EcoSustain: computer and data science for the environment, AP.TEM

Abstract

The widespread adoption of cloud computing has significantly increased energy consumption in data centers, raising concerns about sustainability and efficiency. While hardware optimizations and resource management strategies have been explored to reduce energy usage, the impact of software quality on energy efficiency remains an underexplored area. This project investigates how code smells affect the energy consumption of applications running in cloud environments. By analyzing the relationship between code structure and power usage, we aim to identify energy-inefficient code patterns and propose refactoring strategies to reduce environmental impact. The findings will contribute to the development of more sustainable cloud-based applications, promoting energy-aware software engineering practices.