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Parsed 171 explicit rules from 4 Rule Library Word documents (R051-R1550), deduplicated into 58 unique (component, energy_source) patterns, and mapped to existing IACE IDs (component tags, M-IDs, E-IDs). Changes: - hazard_patterns_extended.go: 58 new patterns derived from Rule Library - pattern_engine.go: combines builtin (44) + extended (58) = 102 total patterns - iace_handler.go: ListHazardPatterns returns all 102 patterns - iace.md: updated documentation for 102 patterns - scripts/generate-rule-patterns.py: mapping + Go code generator - scripts/parsed-rule-library.json: extracted rule data Tests: 132 passing (9 new extended pattern tests) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
244 lines
7.1 KiB
Go
244 lines
7.1 KiB
Go
package iace
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import "sort"
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// MatchInput defines the inputs for the pattern-matching engine.
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type MatchInput struct {
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ComponentLibraryIDs []string `json:"component_library_ids"`
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EnergySourceIDs []string `json:"energy_source_ids"`
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LifecyclePhases []string `json:"lifecycle_phases"`
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CustomTags []string `json:"custom_tags"`
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}
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// MatchOutput contains the results of pattern matching.
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type MatchOutput struct {
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MatchedPatterns []PatternMatch `json:"matched_patterns"`
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SuggestedHazards []HazardSuggestion `json:"suggested_hazards"`
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SuggestedMeasures []MeasureSuggestion `json:"suggested_measures"`
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SuggestedEvidence []EvidenceSuggestion `json:"suggested_evidence"`
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ResolvedTags []string `json:"resolved_tags"`
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}
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// PatternMatch records which pattern fired and why.
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type PatternMatch struct {
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PatternID string `json:"pattern_id"`
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PatternName string `json:"pattern_name"`
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Priority int `json:"priority"`
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MatchedTags []string `json:"matched_tags"`
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}
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// HazardSuggestion is a suggested hazard from pattern matching.
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type HazardSuggestion struct {
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Category string `json:"category"`
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SourcePatterns []string `json:"source_patterns"`
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Confidence float64 `json:"confidence"`
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}
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// MeasureSuggestion is a suggested protective measure from pattern matching.
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type MeasureSuggestion struct {
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MeasureID string `json:"measure_id"`
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SourcePatterns []string `json:"source_patterns"`
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}
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// EvidenceSuggestion is a suggested evidence type from pattern matching.
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type EvidenceSuggestion struct {
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EvidenceID string `json:"evidence_id"`
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SourcePatterns []string `json:"source_patterns"`
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}
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// PatternEngine evaluates hazard patterns against resolved tags.
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type PatternEngine struct {
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resolver *TagResolver
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patterns []HazardPattern
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}
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// NewPatternEngine creates a PatternEngine with built-in + extended patterns and resolver.
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func NewPatternEngine() *PatternEngine {
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// Combine built-in (HP001-HP044) and extended (HP045+) patterns
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patterns := GetBuiltinHazardPatterns()
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patterns = append(patterns, GetExtendedHazardPatterns()...)
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return &PatternEngine{
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resolver: NewTagResolver(),
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patterns: patterns,
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}
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}
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// Match executes the pattern-matching algorithm:
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// 1. Resolve component + energy IDs → tags
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// 2. Merge with custom tags
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// 3. Sort patterns by priority (descending)
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// 4. For each pattern: check required_tags (AND) and excluded_tags (NOT)
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// 5. Collect hazards, measures, evidence from fired patterns (deduplicated)
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// 6. Calculate confidence scores
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func (e *PatternEngine) Match(input MatchInput) *MatchOutput {
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// Step 1+2: resolve all tags
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allTags := e.resolver.ResolveTags(input.ComponentLibraryIDs, input.EnergySourceIDs, input.CustomTags)
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if len(allTags) == 0 {
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return &MatchOutput{ResolvedTags: []string{}}
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}
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tagSet := toSet(allTags)
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// Step 3: sort patterns by priority descending
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patterns := make([]HazardPattern, len(e.patterns))
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copy(patterns, e.patterns)
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sort.Slice(patterns, func(i, j int) bool {
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return patterns[i].Priority > patterns[j].Priority
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})
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// Step 4+5: evaluate each pattern
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var matchedPatterns []PatternMatch
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hazardCatSources := make(map[string][]string) // category → pattern IDs
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measureSources := make(map[string][]string) // measure ID → pattern IDs
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evidenceSources := make(map[string][]string) // evidence ID → pattern IDs
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for _, p := range patterns {
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if !patternMatches(p, tagSet, input.LifecyclePhases) {
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continue
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}
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// Collect the tags that contributed to this match
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var matchedTags []string
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for _, t := range p.RequiredComponentTags {
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if tagSet[t] {
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matchedTags = append(matchedTags, t)
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}
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}
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for _, t := range p.RequiredEnergyTags {
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if tagSet[t] {
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matchedTags = append(matchedTags, t)
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}
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}
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matchedPatterns = append(matchedPatterns, PatternMatch{
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PatternID: p.ID,
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PatternName: p.NameDE,
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Priority: p.Priority,
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MatchedTags: matchedTags,
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})
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for _, cat := range p.GeneratedHazardCats {
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hazardCatSources[cat] = appendUnique(hazardCatSources[cat], p.ID)
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}
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for _, mid := range p.SuggestedMeasureIDs {
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measureSources[mid] = appendUnique(measureSources[mid], p.ID)
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}
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for _, eid := range p.SuggestedEvidenceIDs {
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evidenceSources[eid] = appendUnique(evidenceSources[eid], p.ID)
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}
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}
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// Step 6: build output with confidence scores
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totalPatterns := len(patterns)
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firedCount := len(matchedPatterns)
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var suggestedHazards []HazardSuggestion
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for cat, sources := range hazardCatSources {
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confidence := float64(len(sources)) / float64(maxInt(firedCount, 1))
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if confidence > 1.0 {
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confidence = 1.0
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}
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suggestedHazards = append(suggestedHazards, HazardSuggestion{
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Category: cat,
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SourcePatterns: sources,
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Confidence: confidence,
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})
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}
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// Sort by confidence descending
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sort.Slice(suggestedHazards, func(i, j int) bool {
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return suggestedHazards[i].Confidence > suggestedHazards[j].Confidence
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})
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var suggestedMeasures []MeasureSuggestion
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for mid, sources := range measureSources {
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suggestedMeasures = append(suggestedMeasures, MeasureSuggestion{
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MeasureID: mid,
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SourcePatterns: sources,
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})
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}
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sort.Slice(suggestedMeasures, func(i, j int) bool {
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return suggestedMeasures[i].MeasureID < suggestedMeasures[j].MeasureID
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})
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var suggestedEvidence []EvidenceSuggestion
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for eid, sources := range evidenceSources {
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suggestedEvidence = append(suggestedEvidence, EvidenceSuggestion{
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EvidenceID: eid,
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SourcePatterns: sources,
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})
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}
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sort.Slice(suggestedEvidence, func(i, j int) bool {
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return suggestedEvidence[i].EvidenceID < suggestedEvidence[j].EvidenceID
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})
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_ = totalPatterns // used conceptually for confidence normalization
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return &MatchOutput{
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MatchedPatterns: matchedPatterns,
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SuggestedHazards: suggestedHazards,
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SuggestedMeasures: suggestedMeasures,
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SuggestedEvidence: suggestedEvidence,
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ResolvedTags: allTags,
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}
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}
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// patternMatches checks if a pattern fires given the resolved tag set and lifecycle phases.
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func patternMatches(p HazardPattern, tagSet map[string]bool, lifecyclePhases []string) bool {
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// All required component tags must be present (AND)
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for _, t := range p.RequiredComponentTags {
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if !tagSet[t] {
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return false
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}
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}
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// All required energy tags must be present (AND)
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for _, t := range p.RequiredEnergyTags {
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if !tagSet[t] {
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return false
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}
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}
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// None of the excluded tags may be present (NOT)
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for _, t := range p.ExcludedComponentTags {
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if tagSet[t] {
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return false
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}
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}
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// If pattern requires specific lifecycle phases, at least one must match
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if len(p.RequiredLifecycles) > 0 && len(lifecyclePhases) > 0 {
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found := false
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phaseSet := toSet(lifecyclePhases)
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for _, lp := range p.RequiredLifecycles {
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if phaseSet[lp] {
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found = true
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break
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}
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}
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if !found {
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return false
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}
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}
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return true
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}
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// appendUnique appends val to slice if not already present.
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func appendUnique(slice []string, val string) []string {
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for _, s := range slice {
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if s == val {
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return slice
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}
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}
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return append(slice, val)
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}
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// maxInt returns the larger of a and b.
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func maxInt(a, b int) int {
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if a > b {
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return a
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}
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return b
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}
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