DebugTracker: Lightweight Process Evidence for Classroom Debugging

2026-07-07

AI Summary

This work addresses the limitation of traditional debugging assessments, which focus solely on final code and test outcomes while neglecting students’ full cognitive debugging processes. To bridge this gap, the authors propose DebugTracker—a lightweight Visual Studio Code extension that, for the first time, enables language-agnostic tracking of debugging activities. Leveraging standard VS Code mechanisms, DebugTracker captures multimodal data—including code snapshots, debugger events, editor metadata, and optional screenshots—and logs them incrementally in JSONL format. The system distinguishes between training and evaluation modes and automatically generates human-reviewable timelines and Markdown reports. Validated across Python, TypeScript, and Java tasks on all three major operating systems, DebugTracker has passed 16 automated checks and 11 manual test cases and is publicly available as an installable VSIX plugin.

Abstract

Debugging exercises are often assessed from final code and test outcomes, yet these artifacts hide how students reproduced failures, formed hypotheses, inspected evidence, edited code, and verified fixes. We present DebugTracker, a Visual Studio Code extension that records lightweight debugging-process evidence for classroom tasks. DebugTracker separates uncoached Evaluation Mode traces from coached Training Mode traces, stores append-only JSONL events, and exports timeline and Markdown reports for human review. The prototype records test commands, editor and debugger metadata, student checkpoints, source snapshots, optional image evidence, human labels, and optional AI-assisted practice feedback. DebugTracker is largely language-agnostic: it captures process evidence through standard VS Code mechanisms rather than language-specific tooling, although debugger evidence depends on the relevant VS Code language extension. We validate the prototype with debugging tasks in Python, TypeScript, and Java, 16 automated checks, and an 11-case manual trial matrix spanning packaged VSIX installation and three operating systems.

Problem

• debugging
• process evidence
• classroom assessment
• student behavior
• code debugging

Innovation

• DebugTracker
• debugging process evidence
• language-agnostic
• VS Code extension
• educational assessment