Beyond Autocomplete: Designing CopilotLens Towards Transparent and Explainable AI Coding Agents

• URL: http://arxiv.org/abs/2506.20062v1
• Date: Tue, 24 Jun 2025 23:50:03 GMT
• Title: Beyond Autocomplete: Designing CopilotLens Towards Transparent and Explainable AI Coding Agents
• Authors: Runlong Ye, Zeling Zhang, Boushra Almazroua, Michael Liut,
• Abstract summary: CopilotLens is an interactive framework that reframes code completion from a simple suggestion into a transparent, explainable event.<n>CopilotLens operates as an explanation layer that reveals the AI agent's "thought process" through a dynamic two-level interface.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: AI-powered code assistants are widely used to generate code completions, significantly boosting developer productivity. However, these tools typically present suggestions without explaining their rationale, leaving their decision-making process inscrutable. This opacity hinders developers' ability to critically evaluate the output, form accurate mental models, and build calibrated trust in the system. To address this, we introduce CopilotLens, a novel interactive framework that reframes code completion from a simple suggestion into a transparent, explainable event. CopilotLens operates as an explanation layer that reveals the AI agent's "thought process" through a dynamic two-level interface, surfacing everything from its reconstructed high-level plans to the specific codebase context influencing the code. This paper presents the design and rationale of CopilotLens, offering a concrete framework for building future agentic code assistants that prioritize clarity of reasoning over speed of suggestion, thereby fostering deeper comprehension and more robust human-AI collaboration.

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