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BDD runtime-tracing plan — execution-evidence tier for the RTM

Source: plans/bdd-runtime-tracing-plan.md at 8a2cb42ad · last changed 2026-07-27 · first committed 2026-07-21 · 100 lines.

Prose pending.

Plan text

BDD runtime-tracing plan — execution-evidence tier for the RTM

Session 244, 2026-07-21. Execution plan derived from reports/research-bdd-runtime-tracing-rtm.md (verdict: PARTIAL YES — runtime attribution fixes the PRECISION half of the frozen-at-55% trace problem; recall moves only as test-side citations grow). Read the report for the measured evidence; this file is the actionable plan of record. Related: plans/trace-remediation-plan.md (the freeze ruling this plan operates under), scripts/sync_traces_to_neo4j.py (the TRACES_TO writer, committed 4c5d5615 and deployed live 2026-07-21 — 6,298 edges).

Goal

Make the RTM truthful, graded, and monotonically improvable by adding a deterministic EXECUTED evidence tier: per-test coverage attribution joins (test → requirement citation) × (test → executed def) into (def → requirement) edges with provenance — zero LLM tokens, no judge noise floor. Plus the wrong-trace detector: a static @traces id whose citing tests all pass but never execute the decorated def is CONTRADICTED by the only behavioral evidence there is.

Non-negotiable constraints (from the report's measurements)

Phases

Phase 0 — harvester completeness (0.5 day, unblocked)

Phase 1 — scripts/attribute_traces_runtime.py (1–2 days, unblocked)

Phase 2 — runner integration (0.5–1 day)

Phase 3 — consumers (1 day)

Phase 4 — recall program (open-ended; BLOCKED on user decision D2)

Total Phases 0–3: ~3–4.5 builder days, ~0 LLM tokens at runtime.

User decisions (report §9 — all OPEN)