generated from coulomb/repo-seed
Bernd Worsch
878d2577ae
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Closes the IHF improvement loop. Full antifragility chain now traversable: Widget → Annotation → Candidate → Requirement → Decision → Deployment → OutcomeSignal New artifacts: - DeploymentRecord (immutable, links DecisionRecord to a deployed version) - OutcomeSignal (append-only; DB trigger prevents UPDATE/DELETE) - ChangeEvaluation (one-per-deployment; UNIQUE constraint; 1–5 score) New capabilities: - DeploymentRecordsController (index, show, new, create) - RecordOutcomeSignalAction — capture improved/regressed/neutral/inconclusive signals - Pre/post comparison panel on deployment show (±30-day event/annotation counts) - Regression detection — improved signal followed by high/critical annotation - ChangeEvaluation — idempotent score+rationale per deployment - Recurrence tracking — cycle count per widget, leaderboard - AntifragilityDashboardAction (autoRefresh, 5 panels) per hub - Phase 4 integration tests (T01–T08 logic coverage) - docs/phase4-summary.md; SCOPE.md updated to Phase 4 complete State Hub: workstream 07e9c860 → completed Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
71 lines
3.0 KiB
Haskell
71 lines
3.0 KiB
Haskell
module Application.Helper.Controller where
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import IHP.ControllerPrelude
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import Generated.Types
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import Data.Time.Clock (addUTCTime)
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import Data.List (sortBy)
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-- Here you can add functions which are available in all your controllers
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-- | Returns the set of widget IDs that are currently in regression.
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--
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-- A regression is defined as: a widget that has an OutcomeSignal(improved)
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-- for any deployment, followed by a new Annotation(severity IN high/critical)
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-- created more than 1 day after the signal's observed_at (grace period).
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regressedWidgetIds :: [OutcomeSignal] -> [Annotation] -> [Id Widget]
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regressedWidgetIds signals annotations =
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[ wid
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| wid <- nub (map (.widgetId) signals)
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, isInRegression signals annotations wid
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]
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isInRegression :: [OutcomeSignal] -> [Annotation] -> Id Widget -> Bool
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isInRegression signals annotations wid =
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let improvedSignals = filter (\s -> s.widgetId == wid && s.signalType == "improved") signals
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highAnns = filter (\a -> a.widgetId == wid
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&& a.severity `elem` ["high", "critical"]
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&& isNothing a.retractedAt) annotations
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graceEnd sig = addUTCTime (24 * 3600) sig.observedAt
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in any (\sig -> any (\ann -> ann.createdAt > graceEnd sig) highAnns) improvedSignals
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-- | Computes the number of completed improvement cycles per widget.
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--
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-- A cycle is counted when:
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-- 1. A RequirementCandidate for the widget was accepted
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-- 2. A DecisionRecord exists for that requirement/candidate
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-- 3. A DeploymentRecord exists for that decision
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-- 4. A new RequirementCandidate was subsequently created for the same widget
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--
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-- Returns a list of (widgetId, cycleCount) for widgets with cycleCount >= 1,
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-- sorted descending by cycleCount.
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widgetCycleCounts
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:: [RequirementCandidate]
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-> [Requirement]
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-> [DecisionRecord]
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-> [DeploymentRecord]
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-> [(Id Widget, Int)]
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widgetCycleCounts candidates requirements decisions deployments =
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sortBy (\(_, a) (_, b) -> compare b a)
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[ (wid, cycleCount wid)
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| wid <- nub (map (.sourceWidgetId) candidates)
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, cycleCount wid >= 1
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]
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where
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-- A completed cycle: accepted candidate → requirement → decision → deployment
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completedCycleDeploymentTimes wid =
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[ dr.deployedAt
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| c <- filter (\x -> x.sourceWidgetId == wid && x.status == "accepted") candidates
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, req <- filter (\x -> x.sourceCandidateId == c.id) requirements
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, dec <- filter (\x -> x.requirementId == Just req.id) decisions
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, dr <- filter (\x -> x.decisionId == dec.id) deployments
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]
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cycleCount wid =
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let deplTimes = completedCycleDeploymentTimes wid
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-- For each completed cycle, check if a subsequent candidate was created
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widCandidates = filter (\x -> x.sourceWidgetId == wid) candidates
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in length
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[ ()
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| deplTime <- deplTimes
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, any (\c -> c.createdAt > deplTime) widCandidates
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] |