experiment: map remaining apply proposal boundaries
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# Experiment 60B.70 — Remaining apply-proposal.js Boundary Map
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**Date:** 2026-08-14
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**Branch:** `feature/decision-sufficiency-module-v0.44`
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**Type:** Read-only structural audit (no code changes)
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---
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## Objective
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Identify the highest-value zero-semantic-change extraction boundary in `apply-proposal.js` (4,480 lines) that would materially reduce edit/context risk without obscuring lifecycle orchestration.
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---
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## Git Pre-check
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```
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branch = feature/decision-sufficiency-module-v0.44
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working tree = clean
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HEAD includes: 36b4f47, 1ca5026, 6cb9109 ✓
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```
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---
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## Responsibility Map
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### Proposal reconciliation (lines 320–409)
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- **Approx line count:** 90 lines
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- **Primary responsibility:** Normalize `resolvedUnknownNodeIds` ↔ `updatedNodes` symmetry; auto-add synthetic updatedNode when proposal lists a resolved ID without corresponding update; nuke selectedQuestion if its node was resolved by the same proposal
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- **Pure / impure / mixed:** Mixed (pure on proposal object, reads graph state only for existence checks)
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- **Depends heavily on applyValidatedProposal locals:** NO — takes `graph` + `proposal` as parameters; returns `{proposal, errors}`
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- **Existing focused tests:** STRONG (60B.49 suite: 6 integration tests across reconciliation, staleness, dedup, non-unknown guard)
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### Proposal compatibility / selected-question validation (lines ~3581–3648)
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- **Approx line count:** 130 lines of inline validation logic within applyValidatedProposal
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- **Primary responsibility:** Pre-mutation graph integrity — added edge duplicates, edge reference validity (from/to node existence, cross-boundary edges), removed edge existence, combined node deduplication, semantic duplicate unknown detection, added-unknown support validation, selectedQuestion node validity, answer-meaning compatibility with raw answer, answer-meaning alignment, question-selection requirement
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- **Pure / impure / mixed:** Mixed — calls helpers that read graph + proposal; mutates no state
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- **Depends heavily on applyValidatedProposal locals:** PARTIAL — operates on `validatedProposal` (local) and `situationGraph` (param); calls imported `validateGraphUpdate`
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- **Existing focused tests:** STRONG — 60B.61/64 suites, structured-fidelity suite (8 tests), boundary overlap tests (3), regression A/B/C/D suites, add-unknown support tests (7 cases)
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### Resolution propagation (lines 902–1261; `propagateResolvedChildEvidence`)
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- **Approx line count:** 360 lines (exported function)
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- **Primary responsibility:** Post-mutation parent progress state computation; child branch evidence aggregation; ancestor chain confidence propagation; confidence cap logic; comparison vs independent evidence distinction
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- **Pure / impure / mixed:** Mixed — reads graph, computes derived metrics, returns rich result object
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- **Depends heavily on applyValidatedProposal locals:** NO — already extracted as standalone export
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- **Existing focused tests:** MEDIUM (covered by 60B.43/64 integration; no dedicated unit suite)
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### Active unknown / target selection (lines ~2556–3488 + inlined orchestration at 3907–4121)
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- **Approx line count:** 933 lines (exported `determineGraphBackedQuestion`) + ~215 lines inlined within applyValidatedProposal
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- **Primary responsibility:** Unknown candidate eligibility filtering; reasoning pattern compatibility scoring; decomposition child selection; reseat-after-rejection; model-selected target preference via depends_on prerequisite check; sibling ordering tiebreakers
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- **Pure / impure / mixed:** Mixed — reads graph, returns selection result (no mutations)
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- **Depons heavily on applyValidatedProposal locals:** NO — the exported `determineGraphBackedQuestion` is fully self-contained. The inlined 257 lines at 3860–4121 are orchestration glue that depends on decompositionResult/propagationResult locals.
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- **Existing focused tests:** STRONG (60B.42 active selector guard: 5 tests; 60B.11 prerequisite-aware targeting: 9 tests; selectedQuestion lifecycle in 60B.43/64)
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### Answer semantic validation (lines ~3267–3454)
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- **Approx line count:** 297 lines (validateAnswerMeaningCompatibilityWithRawAnswer + validateAnswerMeaningAlignment helpers)
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- **Primary responsibility:** Raw answer → userSupportedMeaning alignment verification; unclassified meaning support detection; hard constraint boundary language analysis; conditional qualification preservation
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- **Pure / impure / mixed:** Mostly pure — reads answer + proposal, returns errors array
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- **Depends heavily on applyValidatedProposal locals:** NO — operates on `answer` + `proposal` only
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- **Existing focused tests:** MEDIUM (regression A/B/C suites test the path end-to-end but don't isolate the helpers)
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### Graph mutation (applyGraphUpdate import from utils.js)
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- **Approx line count:** ~0 in apply-proposal.js (imported)
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- **Primary responsibility:** The single mutation point — applies node updates, resolves nodes, adds/removes edges
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- **Pure / impure / mixed:** Pure mutation function
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### Final selectedQuestion lifecycle (lines ~4152–4312 within applyValidatedProposal)
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- **Approx line count:** ~160 lines of inlined orchestration
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- **Primary responsibility:** Compose finalSelectedQuestion from deterministicSelection + formulatedQuestion; repeated-question rejection + reseat; effectiveSelectedQuestion composition
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- **Pure / impure / mixed:** Mixed — reads multiple locals, returns selected question or null
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- **Depends heavily on applyValidatedProposal locals:** YES — tight coupling with deterministicSelection, proposedNode, decompositionResult
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### Supporting pure helpers (lines 38–569)
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- **Approx line count:** ~530 lines
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- **Primary responsibility:** JSON cloning, Zod error formatting, edge duplicate detection, text normalization, node lookup, compound question detection, confidence assessment, branch conflict signature computation, token overlap utilities
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- **Pure / impure / mixed:** All pure — no side effects
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- **Depends heavily on applyValidatedProposal locals:** NO
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---
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## Orchestration vs Extractable Logic
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```text
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proposal reconciliation: GOOD EXTRACTION CANDIDATE (pure on proposal+graph)
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proposal compatibility val: GOOD EXTRACTION CANDIDATE (complex but stateless)
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answer semantic validation: POSSIBLE LATER (good candidate but lower priority)
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resolution propagation: ALREADY EXTRACTED (standalone export)
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active unknown / target sel: ALREADY PARTIALLY EXTRACTED (determineGraphBackedQuestion is standalone; inlined orchestration stays)
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final selectedQuestion: SHOULD STAY IN apply-proposal.js (tightly coupled to deterministicSelection lifecycle)
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graph mutation: MUST STAY IN apply-proposal.js (single ownership point)
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supporting pure helpers: POSSIBLE LATER (large cluster, but low edit frequency)
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```
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---
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## Candidate Assessment
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### Candidate A — Proposal Reconciliation (`reconcileResolutionSemantics`)
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- **Approx removable lines:** ~90 (lines 320–409)
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- **Semantic-change risk:** LOW — pure function on proposal object; existing tests cover all paths
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- **Coupling:** LOW — takes graph + proposal; returns {proposal, errors}
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- **Test coverage:** STRONG — 6 dedicated integration tests in 60B.49
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- **Context reduction:** MEDIUM — removes 90 lines of self-contained logic
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- **Future edit-frequency:** LOW — stable reconciliation rules unlikely to change
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- **Lifecycle clarity after extraction:** BETTER — apply-proposal.js pre-validation flow becomes a clear sequence of named steps
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- **Principal risk:** Must verify every edge case (selectedQuestion nuke on resolution, bidirectional update-node/ID consistency) is captured in the new module's tests
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### Candidate B — Proposal Compatibility Validation
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- **Approx removable lines:** ~130 (lines 3581–3648 inline within applyValidatedProposal)
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- **Semantic-change risk:** LOW — stateless validation logic; all callers pass through same helpers
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- **Coupling:** MEDIUM — imports `validateGraphUpdate` from utils.js and calls other internal helpers
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- **Test coverage:** STRONG — 25+ tests across multiple suites exercise every validation path
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- **Context reduction:** HIGH — removes the largest single block of inline logic from applyValidatedProposal, splitting it into a named pre-check step
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- **Future edit-frequency:** MEDIUM — schema-driven, may need updates when graph schema evolves
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- **Lifecycle clarity after extraction:** BETTER — `validateProposalCompatibility()` becomes a single readable call replacing 7+ individual validation pushes
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- **Principal risk:** Must preserve exact error aggregation order and deduplication semantics across the extracted validator
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### Candidate C — Resolution Propagation
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- **Already extracted as standalone export (lines 902–1261)**
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- **No remaining inline logic to extract**
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### Candidate D — Active Unknown / Target Selection
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- **Approx removable lines:** ~215 (inlined orchestration at 3870–4121 within applyValidatedProposal)
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- **Semantic-change risk:** MEDIUM — the inlined block has many local-variable side effects and interacts with decompositionResult/propagationResult state
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- **Coupling:** HIGH — deeply reads locals from applyValidatedProposal; recomputes deterministicSelection multiple times
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- **Test coverage:** STRONG (exported function); but inlined orchestration has MEDIUM test coverage
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- **Context reduction:** MEDIUM
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- **Future edit-frequency:** LOW-MEDIUM
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- **Lifecycle clarity after extraction:** WORSE — would separate the "post-propagation reselection decision" from its governing state variables across function boundary
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- **Principal risk:** Extracting the inlined orchestration block would scatter the candidate selection logic across multiple function boundaries, making it harder to trace the active unknown lifecycle
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### Candidate E — Answer Semantic Validation
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- **Approx removable lines:** ~297 (validateAnswerMeaningCompatibilityWithRawAnswer + validateAnswerMeaningAlignment at lines 3267–3454)
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- **Semantic-change risk:** LOW — mostly pure text analysis
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- **Coupling:** LOW — operates on answer + proposal only
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- **Test coverage:** MEDIUM — tested end-to-end but not as isolated unit tests for the helpers
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- **Context reduction:** MEDIUM
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- **Future edit-frequency:** MEDIUM — answer semantics may evolve with prompt changes
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- **Lifecycle clarity after extraction:** BETTER
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- **Principal risk:** Answer semantics is tightly coupled to prompt contract; extraction alone doesn't reduce orchestration complexity in applyValidatedProposal
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---
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## Mutation Ownership
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```text
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Can mutation ownership remain central while extracting candidate modules: YES
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applyGraphUpdate(...) invocation — MUST stay (single mutation entry point)
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proposalSnapshot lifecycle — MUST stay (built up locally, passed to mutation)
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updatedSituationGraph lifecycle — MUST stay (accumulates mutation state across pipeline stages)
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resolvedUnknownNodeIds bookkeeping — MUST stay (derived from proposalSnapshot.resolvedUnknownNodeIds)
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activeUnknownNodeId mutation — MUST stay (tied to post-mutation candidate reselection lifecycle)
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selectedQuestion finalisation — MUST stay (composed from deterministicSelection + formulatedQuestion in same scope)
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```
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The key insight: all mutations flow through `applyGraphUpdate(graphSnapshot, proposalSnapshot)`. Once extracted modules return their outputs, the mutation remains a single point of truth. Extraction of validation/reconciliation doesn't fragment mutation ownership because these are pre-mutation checks that operate on copies/clones.
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---
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## Ranking
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1. **Candidate B — Proposal compatibility validation** (highest context reduction, strongest tests, LOW semantic risk, removes largest inline logic block)
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2. **Candidate A — Proposal reconciliation** (LOW risk, STRONG tests, self-contained, but fewer lines than B)
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3. **Candidate E — Answer semantic validation** (pure text analysis, good candidate but lower priority)
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4. **Candidate D — Active unknown / target selection** (HIGH coupling to applyValidatedProposal locals makes it a weak extraction candidate despite strong tests)
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5. **Supporting pure helpers** (LOW edit frequency; not worth the abstraction cost)
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---
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## Strategy Assessment
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### Strategy A — ONE EXTRACTION ONLY
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Extract Candidate B (validation), verify, stop.
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```text
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Risk: LOW
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Expected line reduction: ~130 lines from apply-proposal.js (now ~4,350)
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Expected context reduction: HIGH — removes the largest single inline logic block
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Semantic-drift risk: LOW — stateless validation functions are easy to extract correctly
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```
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### Strategy B — TWO SMALL EXTRACTIONS
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Extract A + B in separate commits. Both are independent pure-checking modules with STRONG test coverage.
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```text
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Risk: LOW (two independent, low-risk extractions)
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Expected line reduction: ~220 lines total (~4,260 remaining)
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Expected context reduction: HIGH — two clear named pre-validation steps replace inline logic
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Semantic-drift risk: LOW (both have STRONG test coverage and pure/mixed character)
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```
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### Strategy C — LARGE APPLY-PROPOSAL DECOMPOSITION
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Break apply-proposal.js into several lifecycle modules now.
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```text
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Risk: MEDIUM-HIGH — too many extraction points to verify in one pass; risk of scattering orchestration awareness across modules
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Expected line reduction: ~600+ lines (aggressive)
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Semantic-drift risk: MEDIUM — more boundaries to cross during verification
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```
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### Strategy D — STOP REFACTORING
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Current structure is good enough.
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```text
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Risk: LOW (no risk)
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But 4,480 lines still has one ~990-line function with 15+ phases of inline logic
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Context reduction: NONE
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Semantic-drift risk: NONE
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Future Claude/Codex context cost: HIGH — every session loads all 4,480 lines
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```
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**Chosen: Strategy B — TWO SMALL EXTRACTIONS in separate commits**
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Rationale: Candidates A and B are independent pure-checking modules with STRONG test coverage. Extracting both gives ~220 lines of reduction for minimal risk. Candidate D is excluded because its HIGH coupling to orchestration locals makes it a weak extraction candidate despite strong tests.
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---
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## File Size Estimates
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```text
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Current apply-proposal.js lines: 4,480
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After reconciliation extraction (A): ~4,390 (-90)
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After compatibility validation extraction (B): ~4,260 (-220 total)
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Reasonable medium-term target: ~4,250-4,300
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Why not lower? Because apply-proposal.js must retain:
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- Lifecycle ordering visibility (~150 lines of orchestration scaffolding)
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- Graph mutation ownership (applyGraphUpdate invocation + proposalSnapshot buildup)
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- Active target reselection lifecycle (~260 lines, partially extracted already)
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- Final selectedQuestion composition (~160 lines)
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Target of ~4,250-4,300 reflects a clear orchestration file — not tiny wrapper-only, not giant mixed-responsibility.
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```
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---
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## Critical Distinction
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**Choice: B — validation should be next**
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Why: Candidate B removes the largest single inline logic block (~130 lines) that currently scatters 7+ validation calls across applyValidatedProposal's pre-mutation phase. Extracting `validateProposalCompatibility()` into its own module gives the highest context reduction per line extracted. Both A and B are equally justified as clean extractions, but B has higher priority because:
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1. It removes more lines (130 vs 90)
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2. The validation block in applyValidatedProposal is visually dominant — it obscures the post-validation lifecycle
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3. STRONG test coverage across multiple independent suites (60B.49/61/64/structured-fidelity/boundary/edge-case)
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4. No new tests needed for extraction — existing integration tests provide sufficient boundary coverage
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---
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## Minimum Next Refactor Boundary
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**Choice: B — one new validation module**
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Why: Extract `validateProposalCompatibility(graph, proposal)` as a single function that encapsulates all 8 pre-mutation validations currently scattered across applyValidatedProposal. The extracted function takes the same inputs (`graph`, `proposal`) and returns `{valid, errors}`. This matches the existing pattern established by decision-sufficiency.js extraction (pure logic out, mutation stays).
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---
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## Refactor Timing
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**Choice: B — RETURN TO REASONING WORK FIRST**
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Why: Experiment 60B.70 is a read-only audit with no implementation directive. The highest-value next action is completing this documentation and returning to active reasoning work. A future session can implement the validation extraction when there's a natural editing context (e.g., when schema changes require touching that validation layer anyway). Forcing an extraction without a natural editing trigger increases semantic drift risk because there's no external pressure ensuring the extraction serves a real need.
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---
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## Verification
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- Production code changed: NO
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- Tests changed: NO
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- Prompt changed: NO
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- Schema changed: NO
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- Ollama calls: 0
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- Live API calls: 0
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- Vitest run: NO
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- Jest run: NO
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- Watchman used: NO
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