The Pipeline Orchestrator

The Pipeline Orchestrator enforces a deterministic, ordered sequence from codebase discovery to selective learning. It ensures that every test pattern survives increasing levels of pressure before admission.

“Truth is accumulated only by surviving pressure. Every stage is mandatory and irreversible.”

Pipeline Invariants

/ The pipeline is strictly LINEAR.
/ Each stage has a single responsibility.
/ Output of a stage is immutable input to the next.
/ No stage may weaken the requirements of an earlier one.

01 — Pipeline Stages

ST-01

Required

Discover Surface

Map the behavioral surface of the Laravel application to establish the analytical boundary.

Must Execute:

→ Statically scan codebase
→ Identify Models, Routes, & Services
→ Build deterministic behavior map

Must NOT:

✖ Execute application code
✖ Infer runtime side-effects

ST-02

Optional

Generate Pressure

Produce candidate tests designed to exert pressure on the discovered surface.

Must Execute:

→ Mark all output as CANDIDATES
→ Treat generation as hypothetical

Must NOT:

✖ Assume logical correctness
✖ Admit candidates to learning

ST-03

Required

Verify Tests

Enforce audit-grade verification on all tests (existing and candidate).

Must Execute:

→ Apply all verification gates
→ Anchor evidence to observed state

Must NOT:

✖ Bypass any gate
✖ Downgrade audit failures

ST-04

Required

Observe Failures

Capture and classify failures as structured technical signals.

Must Execute:

→ Categorize using failure taxonomy
→ Capture full causal traces

Must NOT:

✖ Auto-fix failing logic
✖ Suppress signal details

ST-05

Required

Learn (Selective)

Admit only anchored truths into the systemic knowledge base.

Must Execute:

→ Strictly enforce admission rules
→ Maintain knowledge base integrity

Must NOT:

✖ Learn from failures
✖ Admit unanchored patterns

02 — Pipeline Guarantees

Audit-Grade Patterns

Every pattern admitted to the knowledge base has survived the full rigor of the Auditor's verification gates.

Zero Noise Ingestion

The pipeline acts as a physical barrier against flaky tests, redundant assertions, and unanchored evidence.

Monotonic Improvement

The selective learning model ensures that generation quality improves consistently as it adapts to your application's unique surface.

03 — Output Contract

Deterministic Pipeline Artifacts:

surfaceMap

candidateTests?

verifiedTests

failureSignals

learnedPatterns

Note: Silent stages and skipped gates are physically impossible within the orchestrator's execution thread.