// Conceptual LeakGuard integration framework
pub struct LeakGuardDetector {
    pattern_analyzer: StatisticalPatternAnalyzer,
    confidence_scorer: ConfidenceEngine,
    threshold_controller: AdaptiveThresholds,
    alert_generator: AlertSystem,
}

impl LeakGuardDetector {
    pub fn analyze_allocation_pattern(&mut self, 
        allocation: &AllocationEvent) -> DetectionResult {
        
        let pattern = self.pattern_analyzer.extract_pattern(allocation);
        let significance = self.statistical_test(&pattern);
        let confidence = self.confidence_scorer.score(&pattern, significance);
        
        if confidence.exceeds_threshold() {
            self.alert_generator.generate_alert(confidence)
        }
    }
}

use std::collections::HashMap;
use statistical_analysis::{HypothesisTest, ConfidenceInterval};

pub struct LeakGuardAnalyzer {
    allocation_patterns: HashMap<CallStack, AllocationPattern>,
    statistical_engine: StatisticalEngine,
    confidence_threshold: f64,
}

impl LeakGuardAnalyzer {
    pub fn new(confidence_threshold: f64) -> Self {
        Self {
            allocation_patterns: HashMap::new(),
            statistical_engine: StatisticalEngine::new(),
            confidence_threshold,
        }
    }
    
    pub fn process_allocation(&mut self, event: AllocationEvent) -> Option<LeakAlert> {
        let call_stack = event.call_stack.clone();
        let pattern = self.allocation_patterns
            .entry(call_stack.clone())
            .or_insert_with(|| AllocationPattern::new());
            
        pattern.add_allocation(event);
        
        if pattern.has_sufficient_data() {
            let test_result = self.statistical_engine
                .test_for_leak(pattern);
                
            if test_result.confidence > self.confidence_threshold {
                return Some(LeakAlert {
                    call_stack,
                    confidence: test_result.confidence,
                    pattern_type: test_result.pattern_type,
                    evidence: test_result.evidence,
                });
            }
        }
        
        None
    }
}

#[derive(Debug, Clone)]
pub struct AllocationPattern {
    timestamps: Vec<u64>,
    sizes: Vec<usize>,
    cumulative_size: Vec<usize>,
    allocation_rate: MovingAverage,
}

impl AllocationPattern {
    pub fn add_allocation(&mut self, event: AllocationEvent) {
        self.timestamps.push(event.timestamp);
        self.sizes.push(event.size);
        self.cumulative_size.push(
            self.cumulative_size.last().unwrap_or(&0) + event.size
        );
        self.allocation_rate.update(event.size as f64);
    }
    
    pub fn analyze_growth_pattern(&self) -> GrowthAnalysis {
        let growth_rate = self.calculate_growth_rate();
        let trend_analysis = self.analyze_trend();
        let variance_analysis = self.analyze_variance();
        
        GrowthAnalysis {
            growth_rate,
            trend_analysis,
            variance_analysis,
            confidence: self.calculate_confidence(),
        }
    }
    
    fn calculate_growth_rate(&self) -> f64 {
        if self.cumulative_size.len() < 2 {
            return 0.0;
        }
        
        let start = self.cumulative_size[0] as f64;
        let end = *self.cumulative_size.last().unwrap() as f64;
        let time_span = (self.timestamps.last().unwrap() - 
                        self.timestamps[0]) as f64;
        
        (end - start) / time_span
    }
}

pub struct SystemAgentIntegration {
    leak_guard: LeakGuardAnalyzer,
    metrics_collector: MetricsCollector,
    alert_dispatcher: AlertDispatcher,
}

impl SystemAgentIntegration {
    pub async fn monitor_memory_allocations(&mut self) {
        let mut allocation_stream = self.metrics_collector
            .stream_allocations()
            .await;
            
        while let Some(allocation) = allocation_stream.next().await {
            if let Some(alert) = self.leak_guard.process_allocation(allocation) {
                self.alert_dispatcher.dispatch_alert(alert).await;
            }
        }
    }
    
    pub fn generate_periodic_report(&self) -> LeakGuardReport {
        LeakGuardReport {
            total_patterns_analyzed: self.leak_guard.pattern_count(),
            alerts_generated: self.alert_dispatcher.alert_count(),
            confidence_distribution: self.leak_guard.confidence_distribution(),
            performance_metrics: self.leak_guard.performance_metrics(),
        }
    }
}

#[derive(Debug, Serialize)]
pub struct LeakAlert {
    pub call_stack: CallStack,
    pub confidence: f64,
    pub pattern_type: PatternType,
    pub evidence: StatisticalEvidence,
    pub timestamp: u64,
    pub severity: AlertSeverity,
}

impl LeakAlert {
    pub fn to_monitoring_alert(&self) -> MonitoringAlert {
        MonitoringAlert {
            title: format!("Memory Leak Detected ({}% confidence)", 
                          (self.confidence * 100.0) as u8),
            description: self.generate_description(),
            severity: self.severity.clone(),
            tags: vec![
                "memory-leak".to_string(),
                "leakguard".to_string(),
                format!("confidence-{}", (self.confidence * 100.0) as u8),
            ],
            metadata: self.generate_metadata(),
        }
    }
    
    fn generate_description(&self) -> String {
        format!(
            "LeakGuard detected a memory leak with {}% statistical confidence.\n\
             Pattern: {:?}\n\
             Call Stack: {}\n\
             Evidence: {}",
            (self.confidence * 100.0) as u8,
            self.pattern_type,
            self.call_stack.to_string(),
            self.evidence.summary()
        )
    }
}

// Example optimization for pattern storage
pub struct BoundedPatternStorage {
    max_patterns: usize,
    max_history_per_pattern: usize,
    patterns: LRUCache<CallStack, AllocationPattern>,
}

impl BoundedPatternStorage {
    pub fn add_allocation(&mut self, event: AllocationEvent) {
        let pattern = self.patterns.get_mut(&event.call_stack)
            .unwrap_or_else(|| {
                if self.patterns.len() >= self.max_patterns {
                    self.patterns.pop_lru();
                }
                self.patterns.insert(event.call_stack.clone(), 
                                   AllocationPattern::new())
            });
            
        pattern.add_allocation_bounded(event, self.max_history_per_pattern);
    }
}

// Fast path for common cases
impl LeakGuardAnalyzer {
    #[inline]
    pub fn fast_process_allocation(&mut self, event: AllocationEvent) -> Option<LeakAlert> {
        // Fast path: check if pattern exists and has enough data
        if let Some(pattern) = self.allocation_patterns.get_mut(&event.call_stack) {
            pattern.add_allocation_fast(event);
            
            // Only run full analysis periodically
            if pattern.should_analyze() {
                return self.full_statistical_analysis(pattern);
            }
        } else {
            // Slow path: new pattern creation
            self.create_new_pattern(event);
        }
        
        None
    }
}

pub struct EnterpriseLeakGuard {
    core_analyzer: LeakGuardAnalyzer,
    policy_engine: PolicyEngine,
    audit_logger: AuditLogger,
    metrics_exporter: MetricsExporter,
    cluster_coordinator: ClusterCoordinator,
}

impl EnterpriseLeakGuard {
    pub fn with_enterprise_features(config: EnterpriseConfig) -> Self {
        Self {
            core_analyzer: LeakGuardAnalyzer::new(config.confidence_threshold),
            policy_engine: PolicyEngine::new(config.policies),
            audit_logger: AuditLogger::new(config.audit_config),
            metrics_exporter: MetricsExporter::new(config.metrics_config),
            cluster_coordinator: ClusterCoordinator::new(config.cluster_config),
        }
    }
    
    pub async fn run_enterprise_monitoring(&mut self) {
        // Enterprise monitoring loop with additional features
        tokio::join!(
            self.run_core_analysis(),
            self.run_policy_enforcement(),
            self.run_audit_logging(),
            self.export_metrics(),
            self.coordinate_cluster()
        );
    }
}

// Future pattern recognition enhancements
pub enum AdvancedPattern {
    GradualLeak { growth_rate: f64, confidence: f64 },
    BurstLeak { burst_intervals: Vec<Duration>, severity: f64 },
    ConditionalLeak { trigger_conditions: Vec<Condition> },
    PeriodicLeak { period: Duration, amplitude: f64 },
    HybridPattern { components: Vec<Box<AdvancedPattern>> },
}

impl AdvancedPattern {
    pub fn detect_complex_patterns(history: &AllocationHistory) -> Vec<AdvancedPattern> {
        // Advanced pattern detection using multiple statistical methods
        vec![
            Self::detect_gradual_patterns(history),
            Self::detect_burst_patterns(history),
            Self::detect_conditional_patterns(history),
            Self::detect_periodic_patterns(history),
        ].into_iter().flatten().collect()
    }
}

// High-reliability system configuration
pub struct HighReliabilityConfig {
    confidence_threshold: f64,  // 99.9% for critical systems
    alert_escalation: EscalationPolicy,
    failsafe_mode: FailsafeConfig,
    audit_requirements: AuditConfig,
}

impl HighReliabilityConfig {
    pub fn for_critical_system() -> Self {
        Self {
            confidence_threshold: 0.999,  // 99.9% confidence
            alert_escalation: EscalationPolicy::immediate(),
            failsafe_mode: FailsafeConfig::safe_shutdown(),
            audit_requirements: AuditConfig::comprehensive(),
        }
    }
}

pub struct FinancialSystemIntegration {
    leak_guard: LeakGuardAnalyzer,
    trading_monitor: TradingMonitor,
    compliance_logger: ComplianceLogger,
    risk_assessor: RiskAssessor,
}

impl FinancialSystemIntegration {
    pub fn process_trading_allocation(&mut self, 
        allocation: AllocationEvent,
        trading_context: &TradingContext) -> Option<RiskAlert> {
        
        // Analyze memory allocation in trading context
        if let Some(leak_alert) = self.leak_guard.process_allocation(allocation) {
            let risk_level = self.risk_assessor.assess_risk(&leak_alert, trading_context);
            
            // Log for compliance
            self.compliance_logger.log_detection(&leak_alert, &risk_level);
            
            // Generate risk-weighted alert
            return Some(RiskAlert::from_leak_alert(leak_alert, risk_level));
        }
        
        None
    }
}

pub struct ResearchFramework {
    detectors: Vec<Box<dyn MemoryLeakDetector>>,
    data_collector: ResearchDataCollector,
    comparator: AlgorithmComparator,
    reporter: ResearchReporter,
}

impl ResearchFramework {
    pub fn comparative_study(&mut self, workload: &ResearchWorkload) -> ComparisonReport {
        let results: Vec<DetectionResult> = self.detectors
            .iter_mut()
            .map(|detector| detector.analyze_workload(workload))
            .collect();
            
        let comparison = self.comparator.compare_results(&results);
        self.data_collector.record_comparison(&comparison);
        
        self.reporter.generate_report(comparison)
    }
}