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ZeroRun

Fail-closed deterministic test-result reuse for AI coding agents and CI.

ZeroRun answers one narrow question after a code edit: can a previously passing deterministic test result be reused defensibly, or must the target execute fresh?

Reuse is eligible only inside a reviewed boundary. Changed, unknown, unsupported, or conflicting evidence fails closed and executes fresh or is quarantined.

ZeroRun v0.4 status

Internal technical qualification: PASS.

ZeroRun v0.4 cleared the unchanged formal performance gates on historical merged edits across pytest and SymPy:

Workload Corpus Same-runner compute efficiency p95 reduction Observed safety failures
pytest 10 merged patches 8.1657× 78.415% 0
SymPy 20 merged patches 5.4545× 78.309% 0

The formal gates were at least 5× same-runner compute efficiency, at least 50% p95 reduction, and zero observed stale-success/shadow-mismatch/cache-conflict events in the accepted evidence.

These are workload-specific internal historical qualification results, not universal speed guarantees or external production proof. Real-user reliability, setup friction, retention, willingness to pay, and commercial validation remain open.

See EVIDENCE.md for the claim boundary and provenance summary and docs/RELEASE_V0.4.0.md for the v0.4.0 release note.

Supported v0.4 boundary

  • Linux/amd64
  • immutable OCI runtime image pinned by digest
  • explicit operator-reviewed source closure
  • deterministic result-only targets
  • read-only checkout
  • no network during task execution
  • declared environment included in reuse identity
  • exact command/policy/runtime identity
  • uncertainty executes fresh
  • conflicting fresh verification quarantines a cached success

ZeroRun does not automatically prove that a declared source closure is complete. closure_reviewed: true remains an explicit review assertion.

See docs/BOUNDARY.md.

Private pilot

The v0.4 runtime implementation is proprietary and distributed to approved design partners as a compiled Linux/amd64 pilot package. Pilot users do not need access to the private implementation repository and do not upload their source code to ZeroRun.

The binary is intentionally not published in this public repository. Approved participants receive zerorun-pilot-linux-amd64.tar.gz and its .sha256 checksum privately after workload review.

Typical lifecycle:

agent edit
   ↓
zerorun run <task>
   ↓
MISS_EXECUTED or HIT_REUSED
   ↓
periodic zerorun run <task> --verify

A healthy initial cache lifecycle is:

MISS_EXECUTED
HIT_REUSED
VERIFY_MATCH

Public installation/onboarding guidance: docs/PILOT.md.

Public vs private repositories

This repository, floxy-21/zerorun, is the public product surface. It contains:

  • product explanation
  • supported safety boundary
  • sanitized evidence summary
  • pilot onboarding guidance
  • public roadmap
  • security/contact guidance

The runtime implementation, benchmark harnesses, internal experiments, raw qualification receipts, and private pilot build system belong in a separate private implementation repository.

Next milestone

The next meaningful proof is external usage:

  1. onboard 2–5 real developers or teams;
  2. collect at least 100 genuine external edit → test requests under the normal safety boundary;
  3. record reuse, misses/bypasses, verification outcomes, p50/p95, compute savings, setup friction, and support burden;
  4. preserve failures and broad/shared edits rather than selecting only favorable cases;
  5. use those traces to evaluate customer economics and willingness to pay.

See docs/ROADMAP.md.

Links

Do not post credentials, access tokens, confidential source code, or sensitive repository details in a public issue.

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Fail-closed deterministic test reuse for AI coding agents and CI on Linux/amd64.

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