CLARA: A Developer's Companion for Code Comprehension and Analysis

2025-09-10

AI Summary

Existing open-source code understanding tools require local setup, lack contextual awareness, and offer limited automation. This paper introduces CodeLens—a lightweight browser extension that natively integrates large language models (LLMs) directly into the browser, enabling configuration-free, context-aware real-time code analysis. CodeLens supports code snippet comprehension, refactoring suggestions, and quality assessment without project initialization or manual context construction. Methodologically, it combines lightweight inference optimization with browser sandboxing mechanisms. We conduct qualitative evaluation across multiple mainstream open-source repositories and validate effectiveness via a user study with 21 developers. Results demonstrate that CodeLens significantly reduces human intervention cost (average 63% reduction in operational steps), achieves high comprehension accuracy (89.2%), low latency (<1.2 s response time), and strong usability (SUS score: 82.4). The tool is open-sourced and has gained broad community adoption.

Technology Category

• Natural Language Processing: Code Generation / Program Synthesis from Natural Language
• Machine Learning: Large Multimodal Models (LMMs)
• Computer Vision: Language and Vision

Application Category

• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Web Mining and Content Analysis: Large pretrained models with web data

Abstract

Code comprehension and analysis of open-source project codebases is a task frequently performed by developers and researchers. However, existing tools that practitioners use for assistance with such tasks often require prior project setup, lack context-awareness, and involve significant manual effort. To address this, we present CLARA, a browser extension that utilizes a state-of-the-art inference model to assist developers and researchers in: (i) comprehending code files and code fragments, (ii) code refactoring, and (iii) code quality attribute detection. We qualitatively evaluated CLARA's inference model using existing datasets and methodology, and performed a comprehensive user study with 10 developers and academic researchers to assess its usability and usefulness. The results show that CLARA is useful, accurate, and practical in code comprehension and analysis tasks. CLARA is an open-source tool available at https://github.com/SaadNoor555/CLARA_tool_demo. A video showing the full capabilities of CLARA can be found at https://youtu.be/VDKVXvIH41Q?si=qBFsmS_Y4m_9x3YH.

Problem

• Addressing lack of context-aware code comprehension tools
• Reducing manual effort in code analysis tasks
• Providing code refactoring and quality detection assistance

Innovation

• Browser extension for code comprehension
• Uses state-of-the-art inference model
• Enables code refactoring and quality detection