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Automated Program Repair Autonomous Agents Compiler & AST Optimization

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Tokenectomy Labs

Autonomous cybernetic systems for automated program repair

Tokenectomy Labs is an independent AI systems and compiler research lab building a Dual-Brain Architecture for autonomous software engineering. We pair fine-tuned code language models with zero-allocation, deterministic Rust "Sub-Cortex" runtimes to deliver cost-bounded, verifiable program repair.

Flagship Engine: Kronumos Kairos

Kronumos Kairos is an open-weights program repair engine that pairs a 7B neural Cognitive Cortex (Qwen2.5-Coder-7B-Instruct) with the deterministic Tokenectomy Sub-Cortex.

Architectural invariants:

  • Zero-allocation M2M Sub-Cortex: native Rust runtime doing AST traceback surgery, PikeVM/DFA secret sanitization, and deterministic POSIX diff re-anchoring, at under 5 ms latency.
  • Zero Dirty Diff invariant: strict AST validation plus dry-run consensus gating. Under uncertainty or syntax invalidity, the system abstains, so no polluted patches reach the repository.
  • Token efficiency: about 2,512 tokens per task on average, a 93.5% reduction versus multi-turn baselines.
  • Zero API cost: runs on commodity/cloud GPUs (dual Tesla T4) with no commercial API dependency.

Benchmark Results

Evaluated on the full 500-instance SWE-bench Verified with Docker-based evaluation:

Metric Result
Officially resolved tasks 8 / 500
Repositories repaired Django (5), Sphinx (1), scikit-learn (1), xarray (1)
Candidate patch application 100% clean GNU patch
Sub-Cortex AST Healer uplift +33% (6 → 8 resolved)

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