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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) |
Research & Publications
- Preprint: Kronumos 2 Kairos: Cost-Bounded Automated Program Repair via Dual-Brain Cybernetic Sub-Cortex on SWE-bench Verified
- DOI: 10.5281/zenodo.22929676
- Code: Tokenectomy-Labs/Kronomus
Connect
- GitHub: Tokenectomy-Labs
- Lead Systems Architect: M N Daffa
- Research inquiries: daffa250r@gmail.com
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