generated from coulomb/repo-seed
Bernd Worsch
0f505feb2d
Closes the long-range feedback loop: outcome signals now enrich the full
traceability chain and feed back into routing, triage, and AI proposals.
Schema (T01):
- outcome_correlations (CHECK correlation_type)
- pattern_performance_records
- adaptive_threshold_configs
- institutional_knowledge_entries (GIN tsvector FTS)
- learning_insights (CHECK insight_type)
- ALTER TABLE decision_records + requirement_candidates: outcome_summary JSONB
- AFTER INSERT trigger trg_enrich_lineage on outcome_signals
- contracts/core/ updated (outcome-summary-columns-v1, append-only addendum)
Correlation engine (T02):
- Application/Helper/CorrelationEngine.hs: pure annotation→outcome SQL
- Web/Controller/OutcomeCorrelations.hs: ComputeCorrelationsAction + index
Pattern performance (T03):
- Web/Controller/PatternPerformance.hs: ComputePatternPerformanceAction
Adaptive thresholds (T04):
- Web/Controller/AdaptiveThresholds.hs: CalibrateThresholdsAction
- Application/Helper/FrictionScore.hs: applyAdaptiveWeights
Institutional knowledge (T05):
- DistilDecisionAction in DecisionRecords controller
- Web/Controller/InstitutionalKnowledge.hs: QueryKnowledgeBaseAction
Lineage enrichment (T06):
- Web/Controller/LineageEnrichment.hs: EnrichLineageAction (batch backfill)
- enrich_lineage_on_outcome_batch() PL/pgSQL helper in migration
Learning dashboard (T07):
- Web/Controller/LearningDashboard.hs: 5-panel autoRefresh view
- "Learning" nav link in FrontController
API v2 learning endpoints (T08):
- GET /api/v2/outcome-correlations, /pattern-performance, /knowledge-base/{id}
- OpenAPI schemas: OutcomeCorrelation, PatternPerformanceRecord, InstitutionalKnowledgeEntry
GAAF scorecard + docs (T09):
- Core 3.8→3.9, Functional 3.6→3.8, overall 3.61→3.68
- CLAUDE.md: IHF v0.2 complete, no active workplan
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
32 lines
1.3 KiB
Haskell
32 lines
1.3 KiB
Haskell
module Application.Helper.CorrelationEngine where
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import IHP.Prelude
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import Generated.Types
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import IHP.ModelSupport (sqlQuery)
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import Database.PostgreSQL.Simple (Only(..))
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-- | For a hub, compute the correlation score per annotation category:
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-- fraction of traceability chains ending in a positive outcome signal
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-- (signal_type IN ('success', 'adoption', 'satisfaction')).
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computeAnnotationCorrelations ::
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(?modelContext :: ModelContext) =>
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Id Hub -> IO [(Text, Double, Int)]
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-- ^ [(category, score, sample_count)]
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computeAnnotationCorrelations hubId =
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sqlQuery
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"SELECT a.category, \
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\ COALESCE(AVG(CASE WHEN os.signal_type IN ('success','adoption','satisfaction') \
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\ THEN 1.0 ELSE 0.0 END), 0) AS score, \
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\ COUNT(os.id)::int AS sample_count \
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\ FROM annotations a \
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\ JOIN widgets w ON w.id = a.widget_id \
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\ JOIN requirement_candidates rc ON rc.source_widget_id = w.id \
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\ JOIN requirements r ON r.candidate_id = rc.id \
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\ JOIN decision_records dr ON dr.requirement_id = r.id \
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\ JOIN deployment_records dep ON dep.decision_id = dr.id \
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\ JOIN outcome_signals os ON os.deployment_id = dep.id \
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\ WHERE w.hub_id = ? \
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\ GROUP BY a.category \
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\ ORDER BY score DESC"
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[hubId]
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