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agentHEAT 11.1°

AI CLUSTERED EVENT · 10/12/2026

CodeScene Demos AI Agents Refactoring 300k Lines of C in Three Weeks Using Code Health MCP and Replay Testing

1 reports archived1 independent sourcesupdated 10/12/2026, 16:32:33
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1 Sources Cross-Validated

CodeScene released a case study demonstrating coding agents refactoring 300,000 lines of C code from the Street Fighter III decompilation project in three weeks for ~$4,000 in token costs. By leveraging a CodeHealth MCP Server for deterministic quality signals and a replay trajectory testing framework for behavioral correctness, agents autonomously evolved 22 refactoring patterns, raising the Code Health score from 5.6 to 10.0. This validates the feasibility of closed-loop automated maintenance for large-scale legacy systems.

LATEST/CodeScene released a case study demonstrating coding agents refactoring 300,000 lines of C code from the Street Fighter III decompilation project in three weeks for ~$4,000 in token costs. By leveraging a CodeHealth MCP Server for deterministic quality signals and a replay trajectory testing framework for behavioral correctness, agents autonomously evolved 22 refactoring patterns, raising the Code Health score from 5.6 to 10.0. This validates the feasibility of closed-loop automated maintenance for large-scale legacy systems.

HEAT TRENDHourly heat curve

4 fully observed hours
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11.1
Peak
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24h change
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The line compares only sources observed throughout; gap hours are interpolated to keep the trend continuous.

TIMELINECoverage timeline

Total 1 reports · Latest first
  1. InfoQ 中文T2·78 pts
    • Agents generated 2,903 commits modifying over 250,000 lines in a 300k-line C codebase within three weeks at a cost of ~$4,000.
    • The workflow utilized a CodeHealth MCP Server for deterministic scoring feedback and a replay trajectory testing framework comparing state hashes to ensure behavioral integrity.
    • Instead of applying a fixed catalog, agents autonomously accumulated a refactoring handbook with 22 patterns, including specialized strategies like Shared Index Range and Action Parameter.