use std::collections::{HashMap, BTreeMap, VecDeque};
use std::time::{Duration, SystemTime, Instant};
use serde::{Serialize, Deserialize};
use crate::trait_explorer::TraitContext;

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SecurityMetricsCollector {
    metric_collectors: HashMap<String, MetricCollector>,
    kpi_analyzers: Vec<KpiAnalyzer>,
    kri_monitors: Vec<KriMonitor>,
    dashboard_managers: Vec<DashboardManager>,
    trend_analyzers: Vec<TrendAnalyzer>,
    anomaly_detectors: Vec<AnomalyDetector>,
    benchmarking_engines: Vec<BenchmarkingEngine>,
    real_time_monitors: Vec<RealTimeMonitor>,
    scorecard_generators: Vec<ScorecardGenerator>,
    correlation_analyzers: Vec<CorrelationAnalyzer>,
    performance_measurers: Vec<PerformanceMeasurer>,
    compliance_trackers: Vec<ComplianceTracker>,
    alerting_system: SecurityAlertingSystem,
    metrics_storage: MetricsStorage,
    metrics_config: SecurityMetricsConfig,
    metrics_cache: HashMap<String, CachedMetrics>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MetricCollector {
    collector_id: String,
    metric_type: MetricType,
    collection_method: CollectionMethod,
    data_sources: Vec<DataSource>,
    aggregation_rules: Vec<AggregationRule>,
    quality_controls: Vec<QualityControl>,
    sampling_strategy: SamplingStrategy,
    collection_frequency: Duration,
    retention_policy: RetentionPolicy,
    metric_definitions: Vec<MetricDefinition>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum MetricType {
    Vulnerability,
    Threat,
    Risk,
    Compliance,
    Performance,
    Operational,
    Financial,
    Technical,
    Process,
    Behavioral,
    Environmental,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum CollectionMethod {
    Automated,
    Manual,
    Hybrid,
    Event_Driven,
    Scheduled,
    Real_Time,
    Batch,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct KpiAnalyzer {
    analyzer_id: String,
    kpi_definitions: Vec<KpiDefinition>,
    target_values: HashMap<String, TargetValue>,
    threshold_monitors: Vec<ThresholdMonitor>,
    trend_calculators: Vec<TrendCalculator>,
    variance_analyzers: Vec<VarianceAnalyzer>,
    performance_trackers: Vec<PerformanceTracker>,
    goal_alignment_checkers: Vec<GoalAlignmentChecker>,
    business_impact_assessors: Vec<BusinessImpactAssessor>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct KriMonitor {
    monitor_id: String,
    kri_definitions: Vec<KriDefinition>,
    risk_thresholds: HashMap<String, RiskThreshold>,
    early_warning_systems: Vec<EarlyWarningSystem>,
    predictive_models: Vec<PredictiveModel>,
    correlation_engines: Vec<CorrelationEngine>,
    escalation_procedures: Vec<EscalationProcedure>,
    mitigation_triggers: Vec<MitigationTrigger>,
    risk_appetite_monitors: Vec<RiskAppetiteMonitor>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct DashboardManager {
    dashboard_id: String,
    dashboard_type: DashboardType,
    visualization_components: Vec<VisualizationComponent>,
    data_aggregators: Vec<DataAggregator>,
    real_time_updaters: Vec<RealTimeUpdater>,
    interactive_features: Vec<InteractiveFeature>,
    export_capabilities: Vec<ExportCapability>,
    access_controls: DashboardAccessControls,
    customization_options: Vec<CustomizationOption>,
    performance_optimizers: Vec<PerformanceOptimizer>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum DashboardType {
    Executive,
    Operational,
    Technical,
    Compliance,
    Risk,
    Incident,
    Performance,
    Strategic,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct TrendAnalyzer {
    analyzer_id: String,
    trend_algorithms: Vec<TrendAlgorithm>,
    statistical_models: Vec<StatisticalModel>,
    forecasting_engines: Vec<ForecastingEngine>,
    seasonality_detectors: Vec<SeasonalityDetector>,
    change_point_detectors: Vec<ChangePointDetector>,
    regression_analyzers: Vec<RegressionAnalyzer>,
    time_series_analyzers: Vec<TimeSeriesAnalyzer>,
    pattern_recognizers: Vec<PatternRecognizer>,
    predictive_analytics: Vec<PredictiveAnalytic>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AnomalyDetector {
    detector_id: String,
    anomaly_algorithms: Vec<AnomalyAlgorithm>,
    baseline_calculators: Vec<BaselineCalculator>,
    outlier_detectors: Vec<OutlierDetector>,
    behavioral_analyzers: Vec<BehavioralAnalyzer>,
    statistical_anomaly_detectors: Vec<StatisticalAnomalyDetector>,
    machine_learning_detectors: Vec<MachineLearningDetector>,
    threshold_anomaly_detectors: Vec<ThresholdAnomalyDetector>,
    clustering_detectors: Vec<ClusteringDetector>,
    isolation_forest_detectors: Vec<IsolationForestDetector>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct BenchmarkingEngine {
    engine_id: String,
    benchmark_categories: Vec<BenchmarkCategory>,
    industry_comparisons: Vec<IndustryComparison>,
    peer_group_analysis: Vec<PeerGroupAnalysis>,
    best_practice_comparisons: Vec<BestPracticeComparison>,
    maturity_assessments: Vec<MaturityAssessment>,
    competitive_analysis: Vec<CompetitiveAnalysis>,
    standard_benchmarks: Vec<StandardBenchmark>,
    custom_benchmarks: Vec<CustomBenchmark>,
    benchmark_reporting: BenchmarkReporting,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct RealTimeMonitor {
    monitor_id: String,
    real_time_streams: Vec<RealTimeStream>,
    stream_processors: Vec<StreamProcessor>,
    event_correlators: Vec<EventCorrelator>,
    threshold_checkers: Vec<ThresholdChecker>,
    alert_generators: Vec<AlertGenerator>,
    notification_systems: Vec<NotificationSystem>,
    escalation_managers: Vec<EscalationManager>,
    response_coordinators: Vec<ResponseCoordinator>,
    metrics_aggregators: Vec<MetricsAggregator>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ScorecardGenerator {
    generator_id: String,
    scorecard_templates: Vec<ScorecardTemplate>,
    scoring_algorithms: Vec<ScoringAlgorithm>,
    weight_calculators: Vec<WeightCalculator>,
    aggregation_methods: Vec<AggregationMethod>,
    visualization_engines: Vec<VisualizationEngine>,
    report_generators: Vec<ReportGenerator>,
    stakeholder_views: Vec<StakeholderView>,
    historical_comparisons: Vec<HistoricalComparison>,
    goal_tracking: Vec<GoalTracker>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CorrelationAnalyzer {
    analyzer_id: String,
    correlation_methods: Vec<CorrelationMethod>,
    dependency_analyzers: Vec<DependencyAnalyzer>,
    causality_analyzers: Vec<CausalityAnalyzer>,
    association_miners: Vec<AssociationMiner>,
    pattern_correlators: Vec<PatternCorrelator>,
    cross_domain_analyzers: Vec<CrossDomainAnalyzer>,
    temporal_correlators: Vec<TemporalCorrelator>,
    multivariate_analyzers: Vec<MultivariateAnalyzer>,
    network_analyzers: Vec<NetworkAnalyzer>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct PerformanceMeasurer {
    measurer_id: String,
    performance_indicators: Vec<PerformanceIndicator>,
    efficiency_calculators: Vec<EfficiencyCalculator>,
    effectiveness_assessors: Vec<EffectivenessAssessor>,
    productivity_analyzers: Vec<ProductivityAnalyzer>,
    quality_measurers: Vec<QualityMeasurer>,
    cost_analyzers: Vec<CostAnalyzer>,
    roi_calculators: Vec<RoiCalculator>,
    value_assessors: Vec<ValueAssessor>,
    optimization_suggesters: Vec<OptimizationSuggester>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ComplianceTracker {
    tracker_id: String,
    compliance_frameworks: Vec<String>,
    requirement_trackers: Vec<RequirementTracker>,
    control_effectiveness_measurers: Vec<ControlEffectivenessMeasurer>,
    audit_preparedness_assessors: Vec<AuditPreparednessAssessor>,
    gap_analyzers: Vec<GapAnalyzer>,
    remediation_trackers: Vec<RemediationTracker>,
    certification_monitors: Vec<CertificationMonitor>,
    regulatory_change_trackers: Vec<RegulatoryChangeTracker>,
    compliance_scorers: Vec<ComplianceScorer>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SecurityMetricsResult {
    pub result_id: String,
    pub collection_timestamp: SystemTime,
    pub metric_collections: HashMap<String, MetricCollection>,
    pub kpi_analysis: KpiAnalysisResult,
    pub kri_monitoring: KriMonitoringResult,
    pub dashboard_data: DashboardData,
    pub trend_analysis: TrendAnalysisResult,
    pub anomaly_detection: AnomalyDetectionResult,
    pub benchmarking_results: BenchmarkingResults,
    pub real_time_status: RealTimeStatus,
    pub security_scorecard: SecurityScorecard,
    pub correlation_analysis: CorrelationAnalysisResult,
    pub performance_metrics: PerformanceMetricsResult,
    pub compliance_metrics: ComplianceMetricsResult,
    pub overall_security_score: f64,
    pub health_indicators: Vec<HealthIndicator>,
    pub actionable_insights: Vec<ActionableInsight>,
    pub recommendations: Vec<MetricsRecommendation>,
    pub next_collection_time: SystemTime,
    pub analysis_confidence: f64,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MetricCollection {
    pub metric_name: String,
    pub metric_type: MetricType,
    pub current_value: MetricValue,
    pub historical_values: VecDeque<TimestampedValue>,
    pub target_value: Option<MetricValue>,
    pub threshold_status: ThresholdStatus,
    pub trend_direction: TrendDirection,
    pub quality_score: f64,
    pub collection_metadata: HashMap<String, String>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct KpiAnalysisResult {
    pub kpi_scores: HashMap<String, KpiScore>,
    pub target_achievement: HashMap<String, f64>,
    pub performance_trends: HashMap<String, PerformanceTrend>,
    pub variance_analysis: HashMap<String, VarianceAnalysis>,
    pub goal_alignment_score: f64,
    pub business_impact_assessment: BusinessImpactAssessment,
    pub improvement_opportunities: Vec<ImprovementOpportunity>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct KriMonitoringResult {
    pub kri_values: HashMap<String, KriValue>,
    pub risk_threshold_status: HashMap<String, ThresholdStatus>,
    pub early_warnings: Vec<EarlyWarning>,
    pub predictive_alerts: Vec<PredictiveAlert>,
    pub correlation_findings: Vec<CorrelationFinding>,
    pub escalation_triggers: Vec<EscalationTrigger>,
    pub mitigation_recommendations: Vec<MitigationRecommendation>,
    pub risk_appetite_compliance: f64,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct DashboardData {
    pub dashboard_configurations: HashMap<String, DashboardConfiguration>,
    pub visualization_data: HashMap<String, VisualizationData>,
    pub real_time_updates: Vec<RealTimeUpdate>,
    pub interactive_elements: Vec<InteractiveElement>,
    pub export_ready_data: HashMap<String, ExportData>,
    pub performance_statistics: DashboardPerformanceStats,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct TrendAnalysisResult {
    pub trend_patterns: HashMap<String, TrendPattern>,
    pub statistical_significance: HashMap<String, f64>,
    pub forecasting_results: HashMap<String, ForecastResult>,
    pub seasonality_findings: HashMap<String, SeasonalityFinding>,
    pub change_points: HashMap<String, Vec<ChangePoint>>,
    pub regression_models: HashMap<String, RegressionModel>,
    pub predictive_accuracy: HashMap<String, f64>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AnomalyDetectionResult {
    pub detected_anomalies: Vec<DetectedAnomaly>,
    pub anomaly_scores: HashMap<String, f64>,
    pub baseline_deviations: HashMap<String, BaselineDeviation>,
    pub behavioral_changes: Vec<BehavioralChange>,
    pub statistical_outliers: Vec<StatisticalOutlier>,
    pub machine_learning_anomalies: Vec<MlAnomaly>,
    pub clustering_anomalies: Vec<ClusteringAnomaly>,
    pub anomaly_correlations: Vec<AnomalyCorrelation>,
}

impl SecurityMetricsCollector {
    pub fn new() -> Self {
        Self {
            metric_collectors: Self::initialize_metric_collectors(),
            kpi_analyzers: Vec::new(),
            kri_monitors: Vec::new(),
            dashboard_managers: Vec::new(),
            trend_analyzers: Vec::new(),
            anomaly_detectors: Vec::new(),
            benchmarking_engines: Vec::new(),
            real_time_monitors: Vec::new(),
            scorecard_generators: Vec::new(),
            correlation_analyzers: Vec::new(),
            performance_measurers: Vec::new(),
            compliance_trackers: Vec::new(),
            alerting_system: SecurityAlertingSystem::new(),
            metrics_storage: MetricsStorage::new(),
            metrics_config: SecurityMetricsConfig::default(),
            metrics_cache: HashMap::new(),
        }
    }

    pub fn collect_security_metrics(&mut self, context: &TraitUsageContext) -> Result<SecurityMetricsResult, SecurityMetricsError> {
        let result_id = self.generate_result_id(context);

        if let Some(cached_result) = self.get_cached_metrics(&result_id) {
            if self.is_cache_valid(&cached_result) {
                return Ok(cached_result.result.clone());
            }
        }

        let metric_collections = self.collect_all_metrics(context)?;
        let kpi_analysis = self.analyze_kpis(context, &metric_collections)?;
        let kri_monitoring = self.monitor_kris(context, &metric_collections)?;
        let dashboard_data = self.prepare_dashboard_data(context, &metric_collections)?;
        let trend_analysis = self.analyze_trends(context, &metric_collections)?;
        let anomaly_detection = self.detect_anomalies(context, &metric_collections)?;
        let benchmarking_results = self.perform_benchmarking(context, &metric_collections)?;
        let real_time_status = self.get_real_time_status(context)?;
        let security_scorecard = self.generate_security_scorecard(context, &metric_collections)?;
        let correlation_analysis = self.analyze_correlations(context, &metric_collections)?;
        let performance_metrics = self.measure_performance(context, &metric_collections)?;
        let compliance_metrics = self.track_compliance(context, &metric_collections)?;

        let overall_security_score = self.calculate_overall_security_score(
            &kpi_analysis,
            &kri_monitoring,
            &compliance_metrics,
            &performance_metrics,
        )?;

        let health_indicators = self.generate_health_indicators(&metric_collections)?;
        let actionable_insights = self.generate_actionable_insights(
            &trend_analysis,
            &anomaly_detection,
            &correlation_analysis,
        )?;

        let recommendations = self.generate_metrics_recommendations(
            &kpi_analysis,
            &kri_monitoring,
            &trend_analysis,
            &anomaly_detection,
        )?;

        let next_collection_time = self.calculate_next_collection_time()?;

        let result = SecurityMetricsResult {
            result_id: result_id.clone(),
            collection_timestamp: SystemTime::now(),
            metric_collections,
            kpi_analysis,
            kri_monitoring,
            dashboard_data,
            trend_analysis,
            anomaly_detection,
            benchmarking_results,
            real_time_status,
            security_scorecard,
            correlation_analysis,
            performance_metrics,
            compliance_metrics,
            overall_security_score,
            health_indicators,
            actionable_insights,
            recommendations,
            next_collection_time,
        };

        self.cache_metrics(result_id, &result);
        Ok(result)
    }

    fn collect_all_metrics(&mut self, context: &TraitUsageContext) -> Result<HashMap<String, MetricCollection>, SecurityMetricsError> {
        let mut collections = HashMap::new();

        for (collector_id, collector) in &self.metric_collectors {
            let collection = collector.collect_metrics(context)?;
            for (metric_name, metric_data) in collection {
                collections.insert(format!("{}_{}", collector_id, metric_name), metric_data);
            }
        }

        Ok(collections)
    }

    fn analyze_kpis(&mut self, context: &TraitUsageContext, metrics: &HashMap<String, MetricCollection>) -> Result<KpiAnalysisResult, SecurityMetricsError> {
        let mut kpi_scores = HashMap::new();
        let mut target_achievement = HashMap::new();
        let mut performance_trends = HashMap::new();
        let mut variance_analysis = HashMap::new();

        for analyzer in &self.kpi_analyzers {
            let analysis = analyzer.analyze_kpis(context, metrics)?;
            kpi_scores.extend(analysis.kpi_scores);
            target_achievement.extend(analysis.target_achievement);
            performance_trends.extend(analysis.performance_trends);
            variance_analysis.extend(analysis.variance_analysis);
        }

        let goal_alignment_score = self.calculate_goal_alignment_score(&kpi_scores)?;
        let business_impact_assessment = self.assess_business_impact(&kpi_scores, &target_achievement)?;
        let improvement_opportunities = self.identify_improvement_opportunities(&variance_analysis)?;

        Ok(KpiAnalysisResult {
            kpi_scores,
            target_achievement,
            performance_trends,
            variance_analysis,
            goal_alignment_score,
            business_impact_assessment,
            improvement_opportunities,
        })
    }

    fn monitor_kris(&mut self, context: &TraitUsageContext, metrics: &HashMap<String, MetricCollection>) -> Result<KriMonitoringResult, SecurityMetricsError> {
        let mut kri_values = HashMap::new();
        let mut risk_threshold_status = HashMap::new();
        let mut early_warnings = Vec::new();
        let mut predictive_alerts = Vec::new();
        let mut correlation_findings = Vec::new();
        let mut escalation_triggers = Vec::new();
        let mut mitigation_recommendations = Vec::new();

        for monitor in &self.kri_monitors {
            let monitoring_result = monitor.monitor_kris(context, metrics)?;
            kri_values.extend(monitoring_result.kri_values);
            risk_threshold_status.extend(monitoring_result.risk_threshold_status);
            early_warnings.extend(monitoring_result.early_warnings);
            predictive_alerts.extend(monitoring_result.predictive_alerts);
            correlation_findings.extend(monitoring_result.correlation_findings);
            escalation_triggers.extend(monitoring_result.escalation_triggers);
            mitigation_recommendations.extend(monitoring_result.mitigation_recommendations);
        }

        let risk_appetite_compliance = self.calculate_risk_appetite_compliance(&kri_values)?;

        Ok(KriMonitoringResult {
            kri_values,
            risk_threshold_status,
            early_warnings,
            predictive_alerts,
            correlation_findings,
            escalation_triggers,
            mitigation_recommendations,
            risk_appetite_compliance,
        })
    }

    fn prepare_dashboard_data(&mut self, context: &TraitUsageContext, metrics: &HashMap<String, MetricCollection>) -> Result<DashboardData, SecurityMetricsError> {
        let mut dashboard_configurations = HashMap::new();
        let mut visualization_data = HashMap::new();
        let mut real_time_updates = Vec::new();
        let mut interactive_elements = Vec::new();
        let mut export_ready_data = HashMap::new();

        for manager in &self.dashboard_managers {
            let dashboard_result = manager.prepare_dashboard_data(context, metrics)?;
            dashboard_configurations.extend(dashboard_result.dashboard_configurations);
            visualization_data.extend(dashboard_result.visualization_data);
            real_time_updates.extend(dashboard_result.real_time_updates);
            interactive_elements.extend(dashboard_result.interactive_elements);
            export_ready_data.extend(dashboard_result.export_ready_data);
        }

        let performance_statistics = self.collect_dashboard_performance_stats()?;

        Ok(DashboardData {
            dashboard_configurations,
            visualization_data,
            real_time_updates,
            interactive_elements,
            export_ready_data,
            performance_statistics,
        })
    }

    fn analyze_trends(&mut self, context: &TraitUsageContext, metrics: &HashMap<String, MetricCollection>) -> Result<TrendAnalysisResult, SecurityMetricsError> {
        let mut trend_patterns = HashMap::new();
        let mut statistical_significance = HashMap::new();
        let mut forecasting_results = HashMap::new();
        let mut seasonality_findings = HashMap::new();
        let mut change_points = HashMap::new();
        let mut regression_models = HashMap::new();
        let mut predictive_accuracy = HashMap::new();

        for analyzer in &self.trend_analyzers {
            let trend_result = analyzer.analyze_trends(context, metrics)?;
            trend_patterns.extend(trend_result.trend_patterns);
            statistical_significance.extend(trend_result.statistical_significance);
            forecasting_results.extend(trend_result.forecasting_results);
            seasonality_findings.extend(trend_result.seasonality_findings);
            change_points.extend(trend_result.change_points);
            regression_models.extend(trend_result.regression_models);
            predictive_accuracy.extend(trend_result.predictive_accuracy);
        }

        Ok(TrendAnalysisResult {
            trend_patterns,
            statistical_significance,
            forecasting_results,
            seasonality_findings,
            change_points,
            regression_models,
            predictive_accuracy,
        })
    }

    fn detect_anomalies(&mut self, context: &TraitUsageContext, metrics: &HashMap<String, MetricCollection>) -> Result<AnomalyDetectionResult, SecurityMetricsError> {
        let mut detected_anomalies = Vec::new();
        let mut anomaly_scores = HashMap::new();
        let mut baseline_deviations = HashMap::new();
        let mut behavioral_changes = Vec::new();
        let mut statistical_outliers = Vec::new();
        let mut machine_learning_anomalies = Vec::new();
        let mut clustering_anomalies = Vec::new();
        let mut anomaly_correlations = Vec::new();

        for detector in &self.anomaly_detectors {
            let detection_result = detector.detect_anomalies(context, metrics)?;
            detected_anomalies.extend(detection_result.detected_anomalies);
            anomaly_scores.extend(detection_result.anomaly_scores);
            baseline_deviations.extend(detection_result.baseline_deviations);
            behavioral_changes.extend(detection_result.behavioral_changes);
            statistical_outliers.extend(detection_result.statistical_outliers);
            machine_learning_anomalies.extend(detection_result.machine_learning_anomalies);
            clustering_anomalies.extend(detection_result.clustering_anomalies);
            anomaly_correlations.extend(detection_result.anomaly_correlations);
        }

        Ok(AnomalyDetectionResult {
            detected_anomalies,
            anomaly_scores,
            baseline_deviations,
            behavioral_changes,
            statistical_outliers,
            machine_learning_anomalies,
            clustering_anomalies,
            anomaly_correlations,
        })
    }

    fn perform_benchmarking(&mut self, context: &TraitUsageContext, metrics: &HashMap<String, MetricCollection>) -> Result<BenchmarkingResults, SecurityMetricsError> {
        let mut benchmark_comparisons = HashMap::new();
        let mut industry_rankings = HashMap::new();
        let mut peer_group_analysis = HashMap::new();
        let mut best_practice_gaps = Vec::new();
        let mut maturity_assessments = HashMap::new();
        let mut competitive_positions = HashMap::new();

        for engine in &self.benchmarking_engines {
            let benchmarking_result = engine.perform_benchmarking(context, metrics)?;
            benchmark_comparisons.extend(benchmarking_result.benchmark_comparisons);
            industry_rankings.extend(benchmarking_result.industry_rankings);
            peer_group_analysis.extend(benchmarking_result.peer_group_analysis);
            best_practice_gaps.extend(benchmarking_result.best_practice_gaps);
            maturity_assessments.extend(benchmarking_result.maturity_assessments);
            competitive_positions.extend(benchmarking_result.competitive_positions);
        }

        let overall_benchmark_score = self.calculate_overall_benchmark_score(&benchmark_comparisons)?;
        let improvement_priorities = self.identify_improvement_priorities(&best_practice_gaps)?;

        Ok(BenchmarkingResults {
            benchmark_comparisons,
            industry_rankings,
            peer_group_analysis,
            best_practice_gaps,
            maturity_assessments,
            competitive_positions,
            overall_benchmark_score,
            improvement_priorities,
        })
    }

    fn get_real_time_status(&mut self, context: &TraitUsageContext) -> Result<RealTimeStatus, SecurityMetricsError> {
        let mut real_time_metrics = HashMap::new();
        let mut stream_health = HashMap::new();
        let mut active_alerts = Vec::new();
        let mut system_status = HashMap::new();
        let mut throughput_metrics = HashMap::new();
        let mut latency_metrics = HashMap::new();

        for monitor in &self.real_time_monitors {
            let status = monitor.get_real_time_status(context)?;
            real_time_metrics.extend(status.real_time_metrics);
            stream_health.extend(status.stream_health);
            active_alerts.extend(status.active_alerts);
            system_status.extend(status.system_status);
            throughput_metrics.extend(status.throughput_metrics);
            latency_metrics.extend(status.latency_metrics);
        }

        let overall_health_score = self.calculate_overall_health_score(&stream_health, &system_status)?;
        let performance_summary = self.generate_performance_summary(&throughput_metrics, &latency_metrics)?;

        Ok(RealTimeStatus {
            real_time_metrics,
            stream_health,
            active_alerts,
            system_status,
            throughput_metrics,
            latency_metrics,
            overall_health_score,
            performance_summary,
        })
    }

    fn generate_security_scorecard(&mut self, context: &TraitUsageContext, metrics: &HashMap<String, MetricCollection>) -> Result<SecurityScorecard, SecurityMetricsError> {
        let mut category_scores = HashMap::new();
        let mut weighted_scores = HashMap::new();
        let mut performance_indicators = Vec::new();
        let mut trend_indicators = Vec::new();
        let mut risk_indicators = Vec::new();

        for generator in &self.scorecard_generators {
            let scorecard = generator.generate_scorecard(context, metrics)?;
            category_scores.extend(scorecard.category_scores);
            weighted_scores.extend(scorecard.weighted_scores);
            performance_indicators.extend(scorecard.performance_indicators);
            trend_indicators.extend(scorecard.trend_indicators);
            risk_indicators.extend(scorecard.risk_indicators);
        }

        let overall_score = self.calculate_overall_scorecard_score(&weighted_scores)?;
        let grade = self.determine_security_grade(overall_score)?;
        let improvement_areas = self.identify_scorecard_improvement_areas(&category_scores)?;
        let historical_comparison = self.generate_historical_comparison(&category_scores)?;

        Ok(SecurityScorecard {
            category_scores,
            weighted_scores,
            overall_score,
            grade,
            performance_indicators,
            trend_indicators,
            risk_indicators,
            improvement_areas,
            historical_comparison,
        })
    }

    fn analyze_correlations(&mut self, context: &TraitUsageContext, metrics: &HashMap<String, MetricCollection>) -> Result<CorrelationAnalysisResult, SecurityMetricsError> {
        let mut metric_correlations = HashMap::new();
        let mut dependency_networks = HashMap::new();
        let mut causality_relationships = Vec::new();
        let mut association_patterns = Vec::new();
        let mut cross_domain_correlations = Vec::new();
        let mut temporal_correlations = Vec::new();

        for analyzer in &self.correlation_analyzers {
            let correlation_result = analyzer.analyze_correlations(context, metrics)?;
            metric_correlations.extend(correlation_result.metric_correlations);
            dependency_networks.extend(correlation_result.dependency_networks);
            causality_relationships.extend(correlation_result.causality_relationships);
            association_patterns.extend(correlation_result.association_patterns);
            cross_domain_correlations.extend(correlation_result.cross_domain_correlations);
            temporal_correlations.extend(correlation_result.temporal_correlations);
        }

        let correlation_strength_summary = self.summarize_correlation_strengths(&metric_correlations)?;
        let actionable_correlations = self.identify_actionable_correlations(&causality_relationships)?;

        Ok(CorrelationAnalysisResult {
            metric_correlations,
            dependency_networks,
            causality_relationships,
            association_patterns,
            cross_domain_correlations,
            temporal_correlations,
            correlation_strength_summary,
            actionable_correlations,
        })
    }

    fn measure_performance(&mut self, context: &TraitUsageContext, metrics: &HashMap<String, MetricCollection>) -> Result<PerformanceMetricsResult, SecurityMetricsError> {
        let mut performance_indicators = HashMap::new();
        let mut efficiency_metrics = HashMap::new();
        let mut effectiveness_metrics = HashMap::new();
        let mut productivity_metrics = HashMap::new();
        let mut quality_metrics = HashMap::new();
        let mut cost_metrics = HashMap::new();
        let mut roi_metrics = HashMap::new();
        let mut value_metrics = HashMap::new();

        for measurer in &self.performance_measurers {
            let performance_result = measurer.measure_performance(context, metrics)?;
            performance_indicators.extend(performance_result.performance_indicators);
            efficiency_metrics.extend(performance_result.efficiency_metrics);
            effectiveness_metrics.extend(performance_result.effectiveness_metrics);
            productivity_metrics.extend(performance_result.productivity_metrics);
            quality_metrics.extend(performance_result.quality_metrics);
            cost_metrics.extend(performance_result.cost_metrics);
            roi_metrics.extend(performance_result.roi_metrics);
            value_metrics.extend(performance_result.value_metrics);
        }

        let overall_performance_score = self.calculate_overall_performance_score(
            &efficiency_metrics,
            &effectiveness_metrics,
            &quality_metrics,
        )?;

        let optimization_recommendations = self.generate_optimization_recommendations(
            &performance_indicators,
            &efficiency_metrics,
            &cost_metrics,
        )?;

        Ok(PerformanceMetricsResult {
            performance_indicators,
            efficiency_metrics,
            effectiveness_metrics,
            productivity_metrics,
            quality_metrics,
            cost_metrics,
            roi_metrics,
            value_metrics,
            overall_performance_score,
            optimization_recommendations,
        })
    }

    fn track_compliance(&mut self, context: &TraitUsageContext, metrics: &HashMap<String, MetricCollection>) -> Result<ComplianceMetricsResult, SecurityMetricsError> {
        let mut framework_compliance = HashMap::new();
        let mut requirement_status = HashMap::new();
        let mut control_effectiveness = HashMap::new();
        let mut audit_readiness = HashMap::new();
        let mut compliance_gaps = Vec::new();
        let mut remediation_progress = HashMap::new();
        let mut certification_status = HashMap::new();

        for tracker in &self.compliance_trackers {
            let compliance_result = tracker.track_compliance(context, metrics)?;
            framework_compliance.extend(compliance_result.framework_compliance);
            requirement_status.extend(compliance_result.requirement_status);
            control_effectiveness.extend(compliance_result.control_effectiveness);
            audit_readiness.extend(compliance_result.audit_readiness);
            compliance_gaps.extend(compliance_result.compliance_gaps);
            remediation_progress.extend(compliance_result.remediation_progress);
            certification_status.extend(compliance_result.certification_status);
        }

        let overall_compliance_score = self.calculate_overall_compliance_score(&framework_compliance)?;
        let compliance_trends = self.analyze_compliance_trends(&framework_compliance)?;
        let priority_actions = self.identify_priority_compliance_actions(&compliance_gaps)?;

        Ok(ComplianceMetricsResult {
            framework_compliance,
            requirement_status,
            control_effectiveness,
            audit_readiness,
            compliance_gaps,
            remediation_progress,
            certification_status,
            overall_compliance_score,
            compliance_trends,
            priority_actions,
        })
    }

    fn initialize_metric_collectors() -> HashMap<String, MetricCollector> {
        let mut collectors = HashMap::new();

        collectors.insert("vulnerability_metrics".to_string(), MetricCollector::new_vulnerability_collector());
        collectors.insert("threat_metrics".to_string(), MetricCollector::new_threat_collector());
        collectors.insert("risk_metrics".to_string(), MetricCollector::new_risk_collector());
        collectors.insert("compliance_metrics".to_string(), MetricCollector::new_compliance_collector());
        collectors.insert("performance_metrics".to_string(), MetricCollector::new_performance_collector());
        collectors.insert("operational_metrics".to_string(), MetricCollector::new_operational_collector());

        collectors
    }
}

impl MetricCollector {
    pub fn new_vulnerability_collector() -> Self {
        Self {
            collector_id: "vulnerability_collector".to_string(),
            metric_type: MetricType::Vulnerability,
            collection_method: CollectionMethod::Automated,
            data_sources: vec![
                DataSource::new("vulnerability_scanners"),
                DataSource::new("cve_databases"),
                DataSource::new("security_tools"),
            ],
            aggregation_rules: vec![
                AggregationRule::new("count_by_severity"),
                AggregationRule::new("time_to_remediation"),
                AggregationRule::new("risk_score_calculation"),
            ],
            quality_controls: vec![
                QualityControl::new("data_validation"),
                QualityControl::new("duplicate_detection"),
                QualityControl::new("accuracy_verification"),
            ],
            sampling_strategy: SamplingStrategy::Continuous,
            collection_frequency: Duration::from_secs(3600), // Hourly
            retention_policy: RetentionPolicy::new(Duration::from_secs(86400 * 365)), // 1 year
            metric_definitions: Self::initialize_vulnerability_metrics(),
        }
    }

    pub fn new_threat_collector() -> Self {
        Self {
            collector_id: "threat_collector".to_string(),
            metric_type: MetricType::Threat,
            collection_method: CollectionMethod::Real_Time,
            data_sources: vec![
                DataSource::new("threat_intelligence_feeds"),
                DataSource::new("intrusion_detection_systems"),
                DataSource::new("security_information_event_management"),
            ],
            aggregation_rules: vec![
                AggregationRule::new("threat_level_aggregation"),
                AggregationRule::new("attack_vector_analysis"),
                AggregationRule::new("threat_actor_correlation"),
            ],
            quality_controls: vec![
                QualityControl::new("source_reliability_check"),
                QualityControl::new("false_positive_filtering"),
                QualityControl::new("threat_correlation_validation"),
            ],
            sampling_strategy: SamplingStrategy::Event_Driven,
            collection_frequency: Duration::from_secs(300), // 5 minutes
            retention_policy: RetentionPolicy::new(Duration::from_secs(86400 * 180)), // 6 months
            metric_definitions: Self::initialize_threat_metrics(),
        }
    }

    pub fn new_risk_collector() -> Self {
        Self {
            collector_id: "risk_collector".to_string(),
            metric_type: MetricType::Risk,
            collection_method: CollectionMethod::Hybrid,
            data_sources: vec![
                DataSource::new("risk_assessment_tools"),
                DataSource::new("business_impact_analysis"),
                DataSource::new("threat_landscape_analysis"),
            ],
            aggregation_rules: vec![
                AggregationRule::new("risk_score_calculation"),
                AggregationRule::new("impact_probability_matrix"),
                AggregationRule::new("risk_trend_analysis"),
            ],
            quality_controls: vec![
                QualityControl::new("assessment_consistency_check"),
                QualityControl::new("expert_validation"),
                QualityControl::new("historical_accuracy_verification"),
            ],
            sampling_strategy: SamplingStrategy::Scheduled,
            collection_frequency: Duration::from_secs(86400), // Daily
            retention_policy: RetentionPolicy::new(Duration::from_secs(86400 * 1095)), // 3 years
            metric_definitions: Self::initialize_risk_metrics(),
        }
    }

    pub fn new_compliance_collector() -> Self {
        Self {
            collector_id: "compliance_collector".to_string(),
            metric_type: MetricType::Compliance,
            collection_method: CollectionMethod::Automated,
            data_sources: vec![
                DataSource::new("compliance_management_system"),
                DataSource::new("audit_logs"),
                DataSource::new("policy_management_system"),
            ],
            aggregation_rules: vec![
                AggregationRule::new("compliance_percentage_calculation"),
                AggregationRule::new("control_effectiveness_measurement"),
                AggregationRule::new("gap_analysis_aggregation"),
            ],
            quality_controls: vec![
                QualityControl::new("regulatory_requirement_validation"),
                QualityControl::new("evidence_completeness_check"),
                QualityControl::new("audit_trail_verification"),
            ],
            sampling_strategy: SamplingStrategy::Continuous,
            collection_frequency: Duration::from_secs(21600), // 6 hours
            retention_policy: RetentionPolicy::new(Duration::from_secs(86400 * 2555)), // 7 years
            metric_definitions: Self::initialize_compliance_metrics(),
        }
    }

    pub fn new_performance_collector() -> Self {
        Self {
            collector_id: "performance_collector".to_string(),
            metric_type: MetricType::Performance,
            collection_method: CollectionMethod::Real_Time,
            data_sources: vec![
                DataSource::new("application_performance_monitoring"),
                DataSource::new("infrastructure_monitoring"),
                DataSource::new("user_experience_monitoring"),
            ],
            aggregation_rules: vec![
                AggregationRule::new("response_time_percentiles"),
                AggregationRule::new("throughput_calculations"),
                AggregationRule::new("availability_measurements"),
            ],
            quality_controls: vec![
                QualityControl::new("measurement_accuracy_validation"),
                QualityControl::new("outlier_detection"),
                QualityControl::new("baseline_comparison"),
            ],
            sampling_strategy: SamplingStrategy::Continuous,
            collection_frequency: Duration::from_secs(60), // 1 minute
            retention_policy: RetentionPolicy::new(Duration::from_secs(86400 * 90)), // 3 months
            metric_definitions: Self::initialize_performance_metrics(),
        }
    }

    pub fn new_operational_collector() -> Self {
        Self {
            collector_id: "operational_collector".to_string(),
            metric_type: MetricType::Operational,
            collection_method: CollectionMethod::Automated,
            data_sources: vec![
                DataSource::new("incident_management_system"),
                DataSource::new("service_desk"),
                DataSource::new("operational_dashboards"),
            ],
            aggregation_rules: vec![
                AggregationRule::new("incident_count_and_severity"),
                AggregationRule::new("resolution_time_calculation"),
                AggregationRule::new("service_level_measurement"),
            ],
            quality_controls: vec![
                QualityControl::new("incident_classification_validation"),
                QualityControl::new("time_tracking_accuracy"),
                QualityControl::new("service_level_compliance_check"),
            ],
            sampling_strategy: SamplingStrategy::Event_Driven,
            collection_frequency: Duration::from_secs(1800), // 30 minutes
            retention_policy: RetentionPolicy::new(Duration::from_secs(86400 * 365)), // 1 year
            metric_definitions: Self::initialize_operational_metrics(),
        }
    }

    fn initialize_vulnerability_metrics() -> Vec<MetricDefinition> {
        vec![
            MetricDefinition {
                metric_name: "critical_vulnerabilities_count".to_string(),
                description: "Number of critical severity vulnerabilities".to_string(),
                unit: "count".to_string(),
                calculation_method: "count".to_string(),
                target_value: Some(MetricValue::Integer(0)),
                thresholds: vec![
                    MetricThreshold::new("warning", 5.0),
                    MetricThreshold::new("critical", 10.0),
                ],
            },
            MetricDefinition {
                metric_name: "mean_time_to_remediation".to_string(),
                description: "Average time to remediate vulnerabilities".to_string(),
                unit: "hours".to_string(),
                calculation_method: "average".to_string(),
                target_value: Some(MetricValue::Float(72.0)), // 3 days
                thresholds: vec![
                    MetricThreshold::new("warning", 120.0), // 5 days
                    MetricThreshold::new("critical", 240.0), // 10 days
                ],
            },
        ]
    }

    fn initialize_threat_metrics() -> Vec<MetricDefinition> {
        vec![
            MetricDefinition {
                metric_name: "active_threats_count".to_string(),
                description: "Number of active threats detected".to_string(),
                unit: "count".to_string(),
                calculation_method: "count".to_string(),
                target_value: Some(MetricValue::Integer(0)),
                thresholds: vec![
                    MetricThreshold::new("warning", 10.0),
                    MetricThreshold::new("critical", 25.0),
                ],
            },
            MetricDefinition {
                metric_name: "threat_detection_rate".to_string(),
                description: "Percentage of threats successfully detected".to_string(),
                unit: "percentage".to_string(),
                calculation_method: "percentage".to_string(),
                target_value: Some(MetricValue::Float(95.0)),
                thresholds: vec![
                    MetricThreshold::new("warning", 90.0),
                    MetricThreshold::new("critical", 85.0),
                ],
            },
        ]
    }

    fn initialize_risk_metrics() -> Vec<MetricDefinition> {
        vec![
            MetricDefinition {
                metric_name: "overall_risk_score".to_string(),
                description: "Overall organizational risk score".to_string(),
                unit: "score".to_string(),
                calculation_method: "weighted_average".to_string(),
                target_value: Some(MetricValue::Float(2.0)), // Low risk
                thresholds: vec![
                    MetricThreshold::new("warning", 3.0), // Medium risk
                    MetricThreshold::new("critical", 4.0), // High risk
                ],
            },
            MetricDefinition {
                metric_name: "high_risk_issues_count".to_string(),
                description: "Number of high-risk issues identified".to_string(),
                unit: "count".to_string(),
                calculation_method: "count".to_string(),
                target_value: Some(MetricValue::Integer(0)),
                thresholds: vec![
                    MetricThreshold::new("warning", 3.0),
                    MetricThreshold::new("critical", 7.0),
                ],
            },
        ]
    }

    fn initialize_compliance_metrics() -> Vec<MetricDefinition> {
        vec![
            MetricDefinition {
                metric_name: "overall_compliance_score".to_string(),
                description: "Overall compliance percentage across all frameworks".to_string(),
                unit: "percentage".to_string(),
                calculation_method: "weighted_average".to_string(),
                target_value: Some(MetricValue::Float(95.0)),
                thresholds: vec![
                    MetricThreshold::new("warning", 90.0),
                    MetricThreshold::new("critical", 85.0),
                ],
            },
            MetricDefinition {
                metric_name: "audit_findings_count".to_string(),
                description: "Number of audit findings requiring remediation".to_string(),
                unit: "count".to_string(),
                calculation_method: "count".to_string(),
                target_value: Some(MetricValue::Integer(0)),
                thresholds: vec![
                    MetricThreshold::new("warning", 5.0),
                    MetricThreshold::new("critical", 15.0),
                ],
            },
        ]
    }

    fn initialize_performance_metrics() -> Vec<MetricDefinition> {
        vec![
            MetricDefinition {
                metric_name: "system_availability".to_string(),
                description: "System availability percentage".to_string(),
                unit: "percentage".to_string(),
                calculation_method: "availability".to_string(),
                target_value: Some(MetricValue::Float(99.9)),
                thresholds: vec![
                    MetricThreshold::new("warning", 99.5),
                    MetricThreshold::new("critical", 99.0),
                ],
            },
            MetricDefinition {
                metric_name: "security_response_time".to_string(),
                description: "Average response time for security incidents".to_string(),
                unit: "minutes".to_string(),
                calculation_method: "average".to_string(),
                target_value: Some(MetricValue::Float(15.0)),
                thresholds: vec![
                    MetricThreshold::new("warning", 30.0),
                    MetricThreshold::new("critical", 60.0),
                ],
            },
        ]
    }

    fn initialize_operational_metrics() -> Vec<MetricDefinition> {
        vec![
            MetricDefinition {
                metric_name: "security_incidents_count".to_string(),
                description: "Number of security incidents reported".to_string(),
                unit: "count".to_string(),
                calculation_method: "count".to_string(),
                target_value: Some(MetricValue::Integer(0)),
                thresholds: vec![
                    MetricThreshold::new("warning", 5.0),
                    MetricThreshold::new("critical", 15.0),
                ],
            },
            MetricDefinition {
                metric_name: "incident_resolution_time".to_string(),
                description: "Average time to resolve security incidents".to_string(),
                unit: "hours".to_string(),
                calculation_method: "average".to_string(),
                target_value: Some(MetricValue::Float(4.0)),
                thresholds: vec![
                    MetricThreshold::new("warning", 8.0),
                    MetricThreshold::new("critical", 24.0),
                ],
            },
        ]
    }
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum SecurityMetricsError {
    CollectionError(String),
    AnalysisError(String),
    StorageError(String),
    ConfigurationError(String),
    DataQualityError(String),
    VisualizationError(String),
    AlertingError(String),
    BenchmarkingError(String),
    CorrelationError(String),
    ForecastingError(String),
}

impl std::fmt::Display for SecurityMetricsError {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        match self {
            SecurityMetricsError::CollectionError(msg) => write!(f, "Collection error: {}", msg),
            SecurityMetricsError::AnalysisError(msg) => write!(f, "Analysis error: {}", msg),
            SecurityMetricsError::StorageError(msg) => write!(f, "Storage error: {}", msg),
            SecurityMetricsError::ConfigurationError(msg) => write!(f, "Configuration error: {}", msg),
            SecurityMetricsError::DataQualityError(msg) => write!(f, "Data quality error: {}", msg),
            SecurityMetricsError::VisualizationError(msg) => write!(f, "Visualization error: {}", msg),
            SecurityMetricsError::AlertingError(msg) => write!(f, "Alerting error: {}", msg),
            SecurityMetricsError::BenchmarkingError(msg) => write!(f, "Benchmarking error: {}", msg),
            SecurityMetricsError::CorrelationError(msg) => write!(f, "Correlation error: {}", msg),
            SecurityMetricsError::ForecastingError(msg) => write!(f, "Forecasting error: {}", msg),
        }
    }
}

impl std::error::Error for SecurityMetricsError {}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SecurityMetricsConfig {
    pub collection_intervals: HashMap<MetricType, Duration>,
    pub retention_policies: HashMap<MetricType, Duration>,
    pub quality_thresholds: HashMap<String, f64>,
    pub alerting_enabled: bool,
    pub real_time_processing: bool,
    pub anomaly_detection_sensitivity: f64,
    pub trend_analysis_window: Duration,
    pub benchmarking_enabled: bool,
    pub dashboard_refresh_rate: Duration,
}

impl Default for SecurityMetricsConfig {
    fn default() -> Self {
        let mut collection_intervals = HashMap::new();
        collection_intervals.insert(MetricType::Vulnerability, Duration::from_secs(3600));
        collection_intervals.insert(MetricType::Threat, Duration::from_secs(300));
        collection_intervals.insert(MetricType::Risk, Duration::from_secs(86400));
        collection_intervals.insert(MetricType::Compliance, Duration::from_secs(21600));
        collection_intervals.insert(MetricType::Performance, Duration::from_secs(60));
        collection_intervals.insert(MetricType::Operational, Duration::from_secs(1800));

        let mut retention_policies = HashMap::new();
        retention_policies.insert(MetricType::Vulnerability, Duration::from_secs(86400 * 365));
        retention_policies.insert(MetricType::Threat, Duration::from_secs(86400 * 180));
        retention_policies.insert(MetricType::Risk, Duration::from_secs(86400 * 1095));
        retention_policies.insert(MetricType::Compliance, Duration::from_secs(86400 * 2555));
        retention_policies.insert(MetricType::Performance, Duration::from_secs(86400 * 90));
        retention_policies.insert(MetricType::Operational, Duration::from_secs(86400 * 365));

        let mut quality_thresholds = HashMap::new();
        quality_thresholds.insert("data_completeness".to_string(), 0.95);
        quality_thresholds.insert("data_accuracy".to_string(), 0.98);
        quality_thresholds.insert("data_timeliness".to_string(), 0.90);

        Self {
            collection_intervals,
            retention_policies,
            quality_thresholds,
            alerting_enabled: true,
            real_time_processing: true,
            anomaly_detection_sensitivity: 0.85,
            trend_analysis_window: Duration::from_secs(86400 * 30), // 30 days
            benchmarking_enabled: true,
            dashboard_refresh_rate: Duration::from_secs(60), // 1 minute
        }
    }
}

macro_rules! define_metrics_supporting_types {
    () => {
        #[derive(Debug, Clone, Serialize, Deserialize)]
        pub struct DataSource {
            pub source_id: String,
            pub source_type: String,
            pub connection_info: HashMap<String, String>,
        }

        impl DataSource {
            pub fn new(source_type: &str) -> Self {
                Self {
                    source_id: format!("{}_{}", source_type, SystemTime::now().duration_since(SystemTime::UNIX_EPOCH).expect("duration_since should succeed").as_secs()),
                    source_type: source_type.to_string(),
                    connection_info: HashMap::new(),
                }
            }
        }

        #[derive(Debug, Clone, Serialize, Deserialize)]
        pub struct AggregationRule {
            pub rule_name: String,
            pub rule_type: String,
            pub parameters: HashMap<String, String>,
        }

        impl AggregationRule {
            pub fn new(rule_type: &str) -> Self {
                Self {
                    rule_name: rule_type.to_string(),
                    rule_type: rule_type.to_string(),
                    parameters: HashMap::new(),
                }
            }
        }

        #[derive(Debug, Clone, Serialize, Deserialize)]
        pub struct QualityControl {
            pub control_name: String,
            pub control_type: String,
            pub validation_rules: Vec<String>,
        }

        impl QualityControl {
            pub fn new(control_type: &str) -> Self {
                Self {
                    control_name: control_type.to_string(),
                    control_type: control_type.to_string(),
                    validation_rules: Vec::new(),
                }
            }
        }

        #[derive(Debug, Clone, Serialize, Deserialize)]
        pub enum SamplingStrategy {
            Continuous,
            Scheduled,
            Event_Driven,
            Adaptive,
            Random,
        }

        #[derive(Debug, Clone, Serialize, Deserialize)]
        pub struct RetentionPolicy {
            pub retention_duration: Duration,
            pub archival_strategy: String,
            pub deletion_strategy: String,
        }

        impl RetentionPolicy {
            pub fn new(duration: Duration) -> Self {
                Self {
                    retention_duration: duration,
                    archival_strategy: "compress".to_string(),
                    deletion_strategy: "automatic".to_string(),
                }
            }
        }

        #[derive(Debug, Clone, Serialize, Deserialize)]
        pub struct MetricDefinition {
            pub metric_name: String,
            pub description: String,
            pub unit: String,
            pub calculation_method: String,
            pub target_value: Option<MetricValue>,
            pub thresholds: Vec<MetricThreshold>,
        }

        #[derive(Debug, Clone, Serialize, Deserialize)]
        pub enum MetricValue {
            Integer(i64),
            Float(f64),
            String(String),
            Boolean(bool),
        }

        #[derive(Debug, Clone, Serialize, Deserialize)]
        pub struct MetricThreshold {
            pub threshold_name: String,
            pub threshold_value: f64,
        }

        impl MetricThreshold {
            pub fn new(name: &str, value: f64) -> Self {
                Self {
                    threshold_name: name.to_string(),
                    threshold_value: value,
                }
            }
        }

        #[derive(Debug, Clone, Serialize, Deserialize)]
        pub struct TimestampedValue {
            pub timestamp: SystemTime,
            pub value: MetricValue,
        }

        #[derive(Debug, Clone, Serialize, Deserialize)]
        pub enum ThresholdStatus {
            Normal,
            Warning,
            Critical,
            Unknown,
        }

        #[derive(Debug, Clone, Serialize, Deserialize)]
        pub enum TrendDirection {
            Increasing,
            Decreasing,
            Stable,
            Volatile,
            Unknown,
        }

        #[derive(Debug, Clone, Serialize, Deserialize)]
        pub struct CachedMetrics {
            pub result: SecurityMetricsResult,
            pub cache_timestamp: SystemTime,
            pub cache_ttl: Duration,
        }
    };
}

define_metrics_supporting_types!();

pub fn create_security_metrics_collector() -> SecurityMetricsCollector {
    SecurityMetricsCollector::new()
}

pub fn collect_comprehensive_security_metrics(context: &TraitUsageContext) -> Result<SecurityMetricsResult, SecurityMetricsError> {
    let mut collector = SecurityMetricsCollector::new();
    collector.collect_security_metrics(context)
}