This research introduces resource-efficient approaches to code summarization that address sustainability concerns in large Language Models for software engineering.

• Demonstrates effective code documentation with reduced computational resources
• Addresses growing sustainability concerns in scaling AI models
• Proposes GreenAI techniques that maintain performance while lowering environmental impact
• Provides practical solutions for developers seeking efficient code documentation tools

For engineering teams, this offers a pathway to implement AI-assisted code documentation without prohibitive computational costs, enabling more widespread adoption of these productivity-enhancing tools.

Resource-Efficient & Effective Code Summarization