RECAP: An End-to-End Platform for Capturing, Replaying, and Analyzing AI-Assisted Programming Interactions

TL;DR

RECAP is an open-source platform that passively records, replays, and analyzes AI-assisted programming interactions within VS Code to better understand developer-AI collaboration.

Contribution

It introduces a comprehensive system for capturing, merging, and analyzing AI coding sessions, enabling new insights into developer behavior.

Findings

Captured 2,034 prompts and 8,239 code edits from students

Enabled detailed analysis of developer-AI interaction patterns

Demonstrated the platform's ability to support complex behavioral studies

Abstract

Understanding how developers interact with AI coding assistants requires more than chat logs or git histories in isolation; it requires reconstructing the full context: which prompt led to which edit, what the developer tried and discarded, and how their strategy evolved over time. We present RECAP (Replay and Examine Captured AI Programming), an open-source platform that (1) passively records AI chat sessions and fine-grained code edits inside VS Code without disrupting the developer's workflow, (2) merges them into a unified timeline for interactive session replay, and (3) exposes an extensible analysis layer, with example modules for behavioral classification and AI reliance measurement. Deployed in a university software engineering course, RECAP captured 2,034 prompts and 8,239 code edits from 41 students across a multi-week project. We demonstrate how the platform's linked data and replay capabilities enable analyses of developer-AI interaction patterns that no single data source could support.