Performance Regression Analysis

Comprehensive guide to detecting, analyzing, and preventing performance regressions in Go applications. This guide covers regression detection algorithms, statistical methods, automated monitoring, and remediation strategies for maintaining consistent application performance.

Table of Contents

• Introduction
• Regression Detection Framework
• Statistical Methods
• Automated Monitoring
• Trend Analysis
• Alert Systems
• Root Cause Analysis
• Remediation Strategies
• Prevention Techniques
• Best Practices

Introduction

Performance regression analysis is critical for maintaining application quality over time. This guide provides comprehensive strategies for detecting performance degradations early, analyzing their causes, and implementing effective prevention and remediation measures.

Regression Detection Framework

package main

import (
    "context"
    "fmt"
    "math"
    "sort"
    "sync"
    "time"
)

// RegressionAnalyzer detects and analyzes performance regressions
type RegressionAnalyzer struct {
    detectors      map[string]RegressionDetector
    baseline       *PerformanceBaseline
    history        *PerformanceHistory
    alertManager   *RegressionAlertManager
    rootCause      *RootCauseAnalyzer
    config         RegressionConfig
    cache          *RegressionCache
    metrics        *RegressionMetrics
    mu             sync.RWMutex
}

// RegressionConfig contains regression analysis configuration
type RegressionConfig struct {
    DetectionMethods    []DetectionMethod
    SensitivityLevel    SensitivityLevel
    BaselineWindow      time.Duration
    ComparisonWindow    time.Duration
    MinDataPoints       int
    ConfidenceLevel     float64
    SignificanceLevel   float64
    ChangeThreshold     float64
    EnableAutoBaseline  bool
    EnableTrendAnalysis bool
    EnableAlerts        bool
    EnableRootCause     bool
    MaxHistory          int
    UpdateInterval      time.Duration
}

// DetectionMethod defines regression detection methods
type DetectionMethod int

const (
    StatisticalDetection DetectionMethod = iota
    ThresholdDetection
    TrendDetection
    ChangePointDetection
    MLDetection
    EnsembleDetection
)

// SensitivityLevel defines detection sensitivity
type SensitivityLevel int

const (
    LowSensitivity SensitivityLevel = iota
    MediumSensitivity
    HighSensitivity
    UltraHighSensitivity
)

// RegressionDetector performs regression detection
type RegressionDetector interface {
    DetectRegression(current *PerformanceData, baseline *PerformanceBaseline) (*RegressionResult, error)
    GetType() DetectionMethod
    GetSensitivity() SensitivityLevel
    GetAccuracy() DetectionAccuracy
    UpdateBaseline(data *PerformanceData) error
}

// PerformanceData represents performance measurement data
type PerformanceData struct {
    ID          string
    Timestamp   time.Time
    Metrics     map[string]MetricValue
    Metadata    DataMetadata
    Environment Environment
    Build       BuildInfo
    Commit      CommitInfo
    Quality     DataQuality
}

// MetricValue represents a performance metric value
type MetricValue struct {
    Value      float64
    Unit       string
    Type       MetricType
    Samples    []float64
    Statistics DescriptiveStats
    Confidence ConfidenceInterval
}

// MetricType defines performance metric types
type MetricType int

const (
    LatencyMetric MetricType = iota
    ThroughputMetric
    MemoryMetric
    CPUMetric
    DiskIOMetric
    NetworkIOMetric
    CustomMetric
)

// DataMetadata contains metadata about performance data
type DataMetadata struct {
    Source       string
    Test         string
    Configuration map[string]interface{}
    Duration     time.Duration
    Iterations   int
    Parallelism  int
    Tags         map[string]string
}

// Environment describes the execution environment
type Environment struct {
    OS           string
    Architecture string
    GoVersion    string
    CPUModel     string
    CPUCores     int
    Memory       int64
    Disk         string
    Network      string
    Load         SystemLoad
    Temperature  float64
}

// SystemLoad represents system load information
type SystemLoad struct {
    CPU     float64
    Memory  float64
    Disk    float64
    Network float64
    Average LoadAverage
}

// LoadAverage represents load averages
type LoadAverage struct {
    OneMin     float64
    FiveMin    float64
    FifteenMin float64
}

// BuildInfo contains build information
type BuildInfo struct {
    Version    string
    Commit     string
    Branch     string
    Tag        string
    BuildTime  time.Time
    BuildFlags []string
}

// CommitInfo contains commit information
type CommitInfo struct {
    Hash      string
    Author    string
    Message   string
    Timestamp time.Time
    Files     []string
    Stats     CommitStats
}

// CommitStats contains commit statistics
type CommitStats struct {
    Additions int
    Deletions int
    Files     int
    Changed   []string
}

// DataQuality represents data quality metrics
type DataQuality struct {
    Completeness float64
    Stability    float64
    Reliability  float64
    Outliers     int
    Noise        float64
    OverallScore float64
}

// DescriptiveStats contains descriptive statistics
type DescriptiveStats struct {
    Count      int
    Mean       float64
    Median     float64
    StdDev     float64
    Min        float64
    Max        float64
    Percentiles map[int]float64
}

// ConfidenceInterval represents a confidence interval
type ConfidenceInterval struct {
    Lower      float64
    Upper      float64
    Confidence float64
}

// PerformanceBaseline represents performance baselines
type PerformanceBaseline struct {
    ID          string
    Metrics     map[string]BaselineMetric
    TimeRange   TimeRange
    Environment Environment
    Build       BuildInfo
    Quality     BaselineQuality
    CreatedAt   time.Time
    UpdatedAt   time.Time
    Version     int
}

// BaselineMetric contains baseline metric information
type BaselineMetric struct {
    Name        string
    Statistics  DescriptiveStats
    Distribution Distribution
    Percentiles map[int]float64
    Thresholds  Thresholds
    Trend       TrendInfo
    Seasonality SeasonalInfo
}

// Distribution represents statistical distribution
type Distribution struct {
    Type       DistributionType
    Parameters map[string]float64
    GoodnessOfFit float64
}

// DistributionType defines distribution types
type DistributionType int

const (
    NormalDistribution DistributionType = iota
    LogNormalDistribution
    ExponentialDistribution
    GammaDistribution
    WeibullDistribution
)

// Thresholds defines performance thresholds
type Thresholds struct {
    Warning   float64
    Critical  float64
    Regression float64
    Improvement float64
    Adaptive   bool
    Method     ThresholdMethod
}

// ThresholdMethod defines threshold calculation methods
type ThresholdMethod int

const (
    StaticThreshold ThresholdMethod = iota
    PercentileThreshold
    StatisticalThreshold
    AdaptiveThreshold
    MLThreshold
)

// TrendInfo contains trend information
type TrendInfo struct {
    Direction  TrendDirection
    Slope      float64
    Strength   float64
    Confidence float64
    StartTime  time.Time
    EndTime    time.Time
}

// TrendDirection defines trend directions
type TrendDirection int

const (
    Stable TrendDirection = iota
    Improving
    Degrading
    Volatile
)

// SeasonalInfo contains seasonality information
type SeasonalInfo struct {
    Present   bool
    Period    time.Duration
    Amplitude float64
    Phase     float64
    Patterns  []SeasonalPattern
}

// SeasonalPattern represents seasonal patterns
type SeasonalPattern struct {
    Type      PatternType
    Period    time.Duration
    Strength  float64
    Confidence float64
}

// PatternType defines pattern types
type PatternType int

const (
    DailyPattern PatternType = iota
    WeeklyPattern
    MonthlyPattern
    CustomPattern
)

// TimeRange represents a time range
type TimeRange struct {
    Start time.Time
    End   time.Time
}

// BaselineQuality represents baseline quality metrics
type BaselineQuality struct {
    DataPoints   int
    Completeness float64
    Stability    float64
    Freshness    float64
    Confidence   float64
    OverallScore float64
}

// RegressionResult contains regression detection results
type RegressionResult struct {
    ID             string
    Detected       bool
    Severity       RegressionSeverity
    Confidence     float64
    AffectedMetrics []AffectedMetric
    ChangePoints   []ChangePoint
    Analysis       RegressionAnalysis
    RootCause      *RootCauseInfo
    Recommendations []Recommendation
    Timestamp      time.Time
}

// RegressionSeverity defines regression severity levels
type RegressionSeverity int

const (
    MinorRegression RegressionSeverity = iota
    ModerateRegression
    MajorRegression
    CriticalRegression
)

// AffectedMetric represents an affected performance metric
type AffectedMetric struct {
    Name           string
    Type           MetricType
    BaselineValue  float64
    CurrentValue   float64
    Change         Change
    Significance   StatisticalSignificance
    Impact         ImpactAssessment
}

// Change represents performance change information
type Change struct {
    Absolute   float64
    Relative   float64
    Direction  ChangeDirection
    Magnitude  ChangeMagnitude
}

// ChangeDirection defines change directions
type ChangeDirection int

const (
    NoChange ChangeDirection = iota
    Improvement
    Degradation
)

// ChangeMagnitude defines change magnitude levels
type ChangeMagnitude int

const (
    Negligible ChangeMagnitude = iota
    Small
    Medium
    Large
    Extreme
)

// StatisticalSignificance contains statistical significance information
type StatisticalSignificance struct {
    PValue       float64
    Significant  bool
    TestStatistic float64
    TestType     StatisticalTest
    EffectSize   EffectSize
}

// StatisticalTest defines statistical tests
type StatisticalTest int

const (
    TTest StatisticalTest = iota
    MannWhitneyTest
    WilcoxonTest
    KSTest
    PermutationTest
)

// EffectSize represents effect size measurements
type EffectSize struct {
    CohensD        float64
    GlassD         float64
    R2             float64
    Interpretation EffectInterpretation
}

// EffectInterpretation defines effect size interpretations
type EffectInterpretation int

const (
    NegligibleEffect EffectInterpretation = iota
    SmallEffect
    MediumEffect
    LargeEffect
    VeryLargeEffect
)

// ImpactAssessment represents impact assessment
type ImpactAssessment struct {
    BusinessImpact   BusinessImpact
    TechnicalImpact  TechnicalImpact
    UserImpact       UserImpact
    OverallSeverity  ImpactSeverity
}

// BusinessImpact represents business impact
type BusinessImpact struct {
    Revenue      float64
    Cost         float64
    SLA          SLAImpact
    Reputation   ReputationImpact
    Competitive  CompetitiveImpact
}

// SLAImpact represents SLA impact
type SLAImpact struct {
    Violated     bool
    Metrics      map[string]float64
    Penalties    float64
    RiskLevel    RiskLevel
}

// RiskLevel defines risk levels
type RiskLevel int

const (
    LowRisk RiskLevel = iota
    MediumRisk
    HighRisk
    CriticalRisk
)

// ReputationImpact represents reputation impact
type ReputationImpact struct {
    Score         float64
    Sentiment     float64
    Mentions      int
    Escalations   int
}

// CompetitiveImpact represents competitive impact
type CompetitiveImpact struct {
    Advantage     float64
    MarketShare   float64
    Position      int
    Differentiation float64
}

// TechnicalImpact represents technical impact
type TechnicalImpact struct {
    SystemStability  float64
    ResourceUsage    ResourceImpact
    Scalability      ScalabilityImpact
    Maintainability  float64
}

// ResourceImpact represents resource impact
type ResourceImpact struct {
    CPU        float64
    Memory     float64
    Disk       float64
    Network    float64
    Efficiency float64
}

// ScalabilityImpact represents scalability impact
type ScalabilityImpact struct {
    Throughput   float64
    Latency      float64
    Concurrency  float64
    Capacity     float64
}

// UserImpact represents user impact
type UserImpact struct {
    Experience    UserExperience
    Satisfaction  float64
    Retention     float64
    Engagement    float64
}

// UserExperience represents user experience metrics
type UserExperience struct {
    ResponseTime  float64
    Availability  float64
    Reliability   float64
    Usability     float64
}

// ImpactSeverity defines impact severity levels
type ImpactSeverity int

const (
    LowImpact ImpactSeverity = iota
    MediumImpact
    HighImpact
    CriticalImpact
)

// ChangePoint represents a detected change point
type ChangePoint struct {
    Timestamp   time.Time
    Metric      string
    Type        ChangeType
    Magnitude   float64
    Confidence  float64
    Method      ChangePointMethod
    Context     ChangeContext
}

// ChangeType defines change point types
type ChangeType int

const (
    LevelChange ChangeType = iota
    TrendChange
    VarianceChange
    DistributionChange
)

// ChangePointMethod defines change point detection methods
type ChangePointMethod int

const (
    CUSUM ChangePointMethod = iota
    PELT
    BinSeg
    EdDivisive
    KernelCPD
)

// ChangeContext provides context for change points
type ChangeContext struct {
    Build    BuildInfo
    Commit   CommitInfo
    Deploy   DeployInfo
    Config   ConfigChange
    External ExternalEvent
}

// DeployInfo contains deployment information
type DeployInfo struct {
    ID        string
    Version   string
    Timestamp time.Time
    Changes   []string
    Rollback  bool
}

// ConfigChange represents configuration changes
type ConfigChange struct {
    Component string
    Parameter string
    OldValue  interface{}
    NewValue  interface{}
    Timestamp time.Time
}

// ExternalEvent represents external events
type ExternalEvent struct {
    Type        EventType
    Description string
    Timestamp   time.Time
    Source      string
    Impact      float64
}

// EventType defines external event types
type EventType int

const (
    InfrastructureEvent EventType = iota
    NetworkEvent
    DatabaseEvent
    ServiceEvent
    EnvironmentEvent
)

// RegressionAnalysis contains detailed regression analysis
type RegressionAnalysis struct {
    Method       DetectionMethod
    Algorithm    string
    Parameters   map[string]interface{}
    Timeline     AnalysisTimeline
    Comparison   ComparisonAnalysis
    Trend        TrendAnalysis
    Correlation  CorrelationAnalysis
    Confidence   ConfidenceAnalysis
}

// AnalysisTimeline tracks analysis timeline
type AnalysisTimeline struct {
    DetectionTime time.Time
    AnalysisTime  time.Time
    Duration      time.Duration
    DataPoints    int
    WindowSize    time.Duration
}

// ComparisonAnalysis contains comparison analysis results
type ComparisonAnalysis struct {
    BaselinePeriod   TimeRange
    ComparisonPeriod TimeRange
    SampleSizes      SampleSizes
    Statistical      StatisticalComparison
    Practical        PracticalComparison
}

// SampleSizes contains sample size information
type SampleSizes struct {
    Baseline   int
    Comparison int
    Adequate   bool
    Power      float64
}

// StatisticalComparison contains statistical comparison results
type StatisticalComparison struct {
    Test         StatisticalTest
    PValue       float64
    Significant  bool
    EffectSize   EffectSize
    Confidence   ConfidenceInterval
}

// PracticalComparison contains practical comparison results
type PracticalComparison struct {
    Threshold   float64
    Exceeded    bool
    Magnitude   ChangeMagnitude
    Business    BusinessSignificance
}

// BusinessSignificance represents business significance
type BusinessSignificance struct {
    Significant bool
    Impact      float64
    Cost        float64
    Priority    BusinessPriority
}

// BusinessPriority defines business priority levels
type BusinessPriority int

const (
    LowPriority BusinessPriority = iota
    MediumPriority
    HighPriority
    CriticalPriority
)

// TrendAnalysis contains trend analysis results
type TrendAnalysis struct {
    LongTerm  TrendInfo
    ShortTerm TrendInfo
    Forecast  ForecastInfo
    Seasonal  SeasonalInfo
}

// ForecastInfo contains forecasting information
type ForecastInfo struct {
    Method      ForecastMethod
    Horizon     time.Duration
    Values      []float64
    Confidence  []ConfidenceInterval
    Accuracy    ForecastAccuracy
}

// ForecastMethod defines forecasting methods
type ForecastMethod int

const (
    LinearTrend ForecastMethod = iota
    ExponentialSmoothing
    ARIMA
    Prophet
    MLForecast
)

// ForecastAccuracy contains forecast accuracy metrics
type ForecastAccuracy struct {
    MAE   float64
    MAPE  float64
    RMSE  float64
    SMAPE float64
}

// CorrelationAnalysis contains correlation analysis results
type CorrelationAnalysis struct {
    Metrics      []MetricCorrelation
    External     []ExternalCorrelation
    Lag          []LagCorrelation
    Causality    []CausalityAnalysis
}

// MetricCorrelation represents correlation between metrics
type MetricCorrelation struct {
    Metric1     string
    Metric2     string
    Coefficient float64
    Significance float64
    Type        CorrelationType
}

// CorrelationType defines correlation types
type CorrelationType int

const (
    PearsonCorrelation CorrelationType = iota
    SpearmanCorrelation
    KendallCorrelation
    PartialCorrelation
)

// ExternalCorrelation represents correlation with external factors
type ExternalCorrelation struct {
    Factor      string
    Coefficient float64
    Significance float64
    Lag         time.Duration
}

// LagCorrelation represents lagged correlations
type LagCorrelation struct {
    Metric      string
    Lag         time.Duration
    Coefficient float64
    Significance float64
}

// CausalityAnalysis represents causality analysis results
type CausalityAnalysis struct {
    Cause       string
    Effect      string
    Strength    float64
    Confidence  float64
    Method      CausalityMethod
}

// CausalityMethod defines causality analysis methods
type CausalityMethod int

const (
    GrangerCausality CausalityMethod = iota
    TransferEntropy
    PearsonCausality
    CCM
)

// ConfidenceAnalysis contains confidence analysis results
type ConfidenceAnalysis struct {
    Overall     float64
    Statistical float64
    Practical   float64
    Temporal    float64
    Contextual  float64
}

// RootCauseInfo contains root cause analysis information
type RootCauseInfo struct {
    Identified   bool
    Causes       []PotentialCause
    Primary      *PotentialCause
    Investigation InvestigationInfo
    Evidence     []Evidence
}

// PotentialCause represents a potential root cause
type PotentialCause struct {
    Type        CauseType
    Description string
    Probability float64
    Impact      float64
    Evidence    []Evidence
    Timeline    CauseTimeline
}

// CauseType defines root cause types
type CauseType int

const (
    CodeChange CauseType = iota
    ConfigurationChange
    InfrastructureChange
    DataChange
    ExternalDependency
    ResourceContention
    EnvironmentalFactor
)

// CauseTimeline tracks cause timeline
type CauseTimeline struct {
    Introduced time.Time
    Detected   time.Time
    Confirmed  time.Time
    Resolved   *time.Time
}

// InvestigationInfo contains investigation information
type InvestigationInfo struct {
    Status      InvestigationStatus
    Assignee    string
    StartedAt   time.Time
    UpdatedAt   time.Time
    Notes       []InvestigationNote
    Actions     []InvestigationAction
}

// InvestigationStatus defines investigation status
type InvestigationStatus int

const (
    NotStarted InvestigationStatus = iota
    InProgress
    Completed
    Blocked
    Cancelled
)

// InvestigationNote represents investigation notes
type InvestigationNote struct {
    Author    string
    Content   string
    Timestamp time.Time
    Tags      []string
}

// InvestigationAction represents investigation actions
type InvestigationAction struct {
    Type        ActionType
    Description string
    Assignee    string
    Status      ActionStatus
    DueDate     time.Time
    CompletedAt *time.Time
}

// ActionType defines investigation action types
type ActionType int

const (
    DataCollection ActionType = iota
    Analysis
    Testing
    Verification
    Remediation
)

// ActionStatus defines action status
type ActionStatus int

const (
    Pending ActionStatus = iota
    InProgress
    Completed
    Failed
    Cancelled
)

// Evidence represents evidence for root causes
type Evidence struct {
    Type        EvidenceType
    Source      string
    Description string
    Strength    float64
    Timestamp   time.Time
    Data        interface{}
}

// EvidenceType defines evidence types
type EvidenceType int

const (
    MetricEvidence EvidenceType = iota
    LogEvidence
    TraceEvidence
    ProfileEvidence
    CodeEvidence
    ConfigEvidence
)

// Recommendation represents analysis recommendations
type Recommendation struct {
    Type        RecommendationType
    Priority    RecommendationPriority
    Description string
    Actions     []RecommendedAction
    Impact      ExpectedImpact
    Effort      EffortEstimate
}

// RecommendationType defines recommendation types
type RecommendationType int

const (
    ImmediateAction RecommendationType = iota
    Investigation
    Monitoring
    Prevention
    Optimization
)

// RecommendationPriority defines recommendation priority
type RecommendationPriority int

const (
    LowPriority RecommendationPriority = iota
    MediumPriority
    HighPriority
    UrgentPriority
)

// RecommendedAction represents recommended actions
type RecommendedAction struct {
    Description string
    Type        ActionType
    Urgency     ActionUrgency
    Owner       string
    Deadline    time.Time
}

// ActionUrgency defines action urgency levels
type ActionUrgency int

const (
    LowUrgency ActionUrgency = iota
    MediumUrgency
    HighUrgency
    CriticalUrgency
)

// ExpectedImpact represents expected impact of recommendations
type ExpectedImpact struct {
    Performance   float64
    Reliability   float64
    Scalability   float64
    Maintainability float64
    Cost          float64
}

// EffortEstimate represents effort estimation
type EffortEstimate struct {
    Hours       float64
    Complexity  ComplexityLevel
    Resources   []RequiredResource
    Timeline    time.Duration
    Risk        RiskAssessment
}

// ComplexityLevel defines complexity levels
type ComplexityLevel int

const (
    LowComplexity ComplexityLevel = iota
    MediumComplexity
    HighComplexity
    VeryHighComplexity
)

// RequiredResource represents required resources
type RequiredResource struct {
    Type        ResourceType
    Amount      float64
    Skills      []string
    Availability float64
}

// ResourceType defines resource types
type ResourceType int

const (
    DeveloperResource ResourceType = iota
    DevOpsResource
    QAResource
    ArchitectResource
    InfrastructureResource
)

// RiskAssessment represents risk assessment
type RiskAssessment struct {
    Level       RiskLevel
    Factors     []RiskFactor
    Mitigation  []MitigationStrategy
    Probability float64
    Impact      float64
}

// RiskFactor represents risk factors
type RiskFactor struct {
    Description string
    Probability float64
    Impact      float64
    Mitigation  string
}

// MitigationStrategy represents mitigation strategies
type MitigationStrategy struct {
    Description   string
    Effectiveness float64
    Cost          float64
    Timeline      time.Duration
}

// PerformanceHistory manages performance history data
type PerformanceHistory struct {
    data    map[string][]*PerformanceData
    indices map[string]*TimeIndex
    config  HistoryConfig
    storage HistoryStorage
    cache   *HistoryCache
    mu      sync.RWMutex
}

// HistoryConfig contains history configuration
type HistoryConfig struct {
    MaxEntries      int
    RetentionPeriod time.Duration
    CompressionEnabled bool
    IndexingEnabled    bool
    CacheSize          int
    CacheTTL           time.Duration
}

// TimeIndex provides time-based indexing
type TimeIndex struct {
    entries []TimeEntry
    sorted  bool
}

// TimeEntry represents time index entries
type TimeEntry struct {
    Timestamp time.Time
    Index     int
    ID        string
}

// HistoryStorage manages persistent history storage
type HistoryStorage interface {
    Store(data *PerformanceData) error
    Retrieve(query HistoryQuery) ([]*PerformanceData, error)
    Delete(criteria DeletionCriteria) error
    Compact() error
}

// HistoryQuery represents history queries
type HistoryQuery struct {
    TimeRange   TimeRange
    Metrics     []string
    Filters     map[string]interface{}
    Limit       int
    Aggregation AggregationSpec
}

// AggregationSpec specifies data aggregation
type AggregationSpec struct {
    Function AggregationFunction
    Interval time.Duration
    GroupBy  []string
}

// AggregationFunction defines aggregation functions
type AggregationFunction int

const (
    MeanAggregation AggregationFunction = iota
    MedianAggregation
    MaxAggregation
    MinAggregation
    SumAggregation
    CountAggregation
)

// DeletionCriteria specifies deletion criteria
type DeletionCriteria struct {
    OlderThan time.Time
    Filters   map[string]interface{}
    KeepLast  int
}

// DetectionAccuracy contains detection accuracy metrics
type DetectionAccuracy struct {
    Precision    float64
    Recall       float64
    F1Score      float64
    Specificity  float64
    Accuracy     float64
    FalsePositiveRate float64
    FalseNegativeRate float64
}

// NewRegressionAnalyzer creates a new regression analyzer
func NewRegressionAnalyzer(config RegressionConfig) *RegressionAnalyzer {
    analyzer := &RegressionAnalyzer{
        detectors:    make(map[string]RegressionDetector),
        baseline:     NewPerformanceBaseline(),
        history:      NewPerformanceHistory(),
        alertManager: NewRegressionAlertManager(),
        rootCause:    NewRootCauseAnalyzer(),
        config:       config,
        cache:        NewRegressionCache(),
        metrics:      &RegressionMetrics{},
    }

    // Initialize detectors based on configuration
    for _, method := range config.DetectionMethods {
        detector := createDetector(method, config)
        if detector != nil {
            analyzer.detectors[detector.GetType().String()] = detector
        }
    }

    return analyzer
}

// AnalyzeRegression performs comprehensive regression analysis
func (ra *RegressionAnalyzer) AnalyzeRegression(ctx context.Context, data *PerformanceData) (*RegressionResult, error) {
    ra.mu.Lock()
    defer ra.mu.Unlock()

    // Validate input data
    if err := ra.validateData(data); err != nil {
        return nil, fmt.Errorf("data validation failed: %w", err)
    }

    // Check cache first
    if cached := ra.cache.Get(data.ID); cached != nil {
        return cached, nil
    }

    // Get or create baseline
    baseline := ra.getOrCreateBaseline(data)
    if baseline == nil {
        return nil, fmt.Errorf("failed to establish baseline")
    }

    // Perform regression detection using multiple methods
    results := make([]*RegressionResult, 0, len(ra.detectors))
    for _, detector := range ra.detectors {
        result, err := detector.DetectRegression(data, baseline)
        if err != nil {
            // Log error but continue with other detectors
            continue
        }
        if result.Detected {
            results = append(results, result)
        }
    }

    // Combine results using ensemble method
    finalResult := ra.combineResults(results, data)

    // Perform root cause analysis if regression detected
    if finalResult.Detected && ra.config.EnableRootCause {
        rootCause, err := ra.rootCause.Analyze(ctx, data, baseline)
        if err == nil {
            finalResult.RootCause = rootCause
        }
    }

    // Generate recommendations
    finalResult.Recommendations = ra.generateRecommendations(finalResult)

    // Store in history
    ra.history.Add(data)

    // Cache result
    ra.cache.Set(data.ID, finalResult)

    // Send alerts if enabled
    if ra.config.EnableAlerts && finalResult.Detected {
        ra.alertManager.SendAlert(finalResult)
    }

    // Update metrics
    ra.updateMetrics(finalResult)

    return finalResult, nil
}

// CompareWithBaseline compares current performance with baseline
func (ra *RegressionAnalyzer) CompareWithBaseline(current *PerformanceData, baseline *PerformanceBaseline) (*ComparisonResult, error) {
    comparison := &ComparisonResult{
        Current:   current,
        Baseline:  baseline,
        Timestamp: time.Now(),
    }

    // Compare each metric
    for metricName, currentMetric := range current.Metrics {
        if baselineMetric, exists := baseline.Metrics[metricName]; exists {
            metricComparison := ra.compareMetric(currentMetric, baselineMetric)
            comparison.Metrics = append(comparison.Metrics, metricComparison)
        }
    }

    // Calculate overall comparison
    comparison.Overall = ra.calculateOverallComparison(comparison.Metrics)

    return comparison, nil
}

// UpdateBaseline updates the performance baseline
func (ra *RegressionAnalyzer) UpdateBaseline(data *PerformanceData) error {
    ra.mu.Lock()
    defer ra.mu.Unlock()

    if ra.config.EnableAutoBaseline {
        return ra.baseline.Update(data)
    }

    return nil
}

// GetPerformanceTrends analyzes performance trends
func (ra *RegressionAnalyzer) GetPerformanceTrends(timeRange TimeRange) (*TrendAnalysisResult, error) {
    // Retrieve historical data
    query := HistoryQuery{
        TimeRange: timeRange,
        Limit:     1000,
    }

    historicalData, err := ra.history.Query(query)
    if err != nil {
        return nil, fmt.Errorf("failed to retrieve historical data: %w", err)
    }

    if len(historicalData) < ra.config.MinDataPoints {
        return nil, fmt.Errorf("insufficient data points for trend analysis")
    }

    // Perform trend analysis
    trendResult := &TrendAnalysisResult{
        TimeRange: timeRange,
        DataPoints: len(historicalData),
        Timestamp: time.Now(),
    }

    // Analyze trends for each metric
    for metricName := range historicalData[0].Metrics {
        trend := ra.analyzeTrendForMetric(metricName, historicalData)
        trendResult.Trends[metricName] = trend
    }

    return trendResult, nil
}

// validateData validates performance data
func (ra *RegressionAnalyzer) validateData(data *PerformanceData) error {
    if data == nil {
        return fmt.Errorf("data cannot be nil")
    }

    if data.ID == "" {
        return fmt.Errorf("data ID is required")
    }

    if len(data.Metrics) == 0 {
        return fmt.Errorf("at least one metric is required")
    }

    if data.Timestamp.IsZero() {
        return fmt.Errorf("timestamp is required")
    }

    // Validate each metric
    for name, metric := range data.Metrics {
        if err := ra.validateMetric(name, metric); err != nil {
            return fmt.Errorf("invalid metric %s: %w", name, err)
        }
    }

    return nil
}

// validateMetric validates a performance metric
func (ra *RegressionAnalyzer) validateMetric(name string, metric MetricValue) error {
    if math.IsNaN(metric.Value) || math.IsInf(metric.Value, 0) {
        return fmt.Errorf("invalid metric value")
    }

    if len(metric.Samples) > 0 {
        for i, sample := range metric.Samples {
            if math.IsNaN(sample) || math.IsInf(sample, 0) {
                return fmt.Errorf("invalid sample at index %d", i)
            }
        }
    }

    return nil
}

// Helper methods and types
type RegressionMetrics struct{}
type RegressionCache struct{}
type RegressionAlertManager struct{}
type RootCauseAnalyzer struct{}
type HistoryCache struct{}
type ComparisonResult struct {
    Current   *PerformanceData
    Baseline  *PerformanceBaseline
    Metrics   []MetricComparison
    Overall   OverallComparison
    Timestamp time.Time
}

type MetricComparison struct {
    Name         string
    Current      float64
    Baseline     float64
    Change       Change
    Significance StatisticalSignificance
}

type OverallComparison struct {
    Score      float64
    Regression bool
    Severity   RegressionSeverity
    Summary    string
}

type TrendAnalysisResult struct {
    TimeRange  TimeRange
    DataPoints int
    Trends     map[string]TrendInfo
    Timestamp  time.Time
}

// Constructor functions
func NewPerformanceBaseline() *PerformanceBaseline { return &PerformanceBaseline{} }
func NewPerformanceHistory() *PerformanceHistory { return &PerformanceHistory{} }
func NewRegressionAlertManager() *RegressionAlertManager { return &RegressionAlertManager{} }
func NewRootCauseAnalyzer() *RootCauseAnalyzer { return &RootCauseAnalyzer{} }
func NewRegressionCache() *RegressionCache { return &RegressionCache{} }

// Method implementations
func createDetector(method DetectionMethod, config RegressionConfig) RegressionDetector { return nil }
func (ra *RegressionAnalyzer) getOrCreateBaseline(data *PerformanceData) *PerformanceBaseline { return nil }
func (ra *RegressionAnalyzer) combineResults(results []*RegressionResult, data *PerformanceData) *RegressionResult { return nil }
func (ra *RegressionAnalyzer) generateRecommendations(result *RegressionResult) []Recommendation { return nil }
func (ra *RegressionAnalyzer) updateMetrics(result *RegressionResult) {}
func (ra *RegressionAnalyzer) compareMetric(current MetricValue, baseline BaselineMetric) MetricComparison { return MetricComparison{} }
func (ra *RegressionAnalyzer) calculateOverallComparison(metrics []MetricComparison) OverallComparison { return OverallComparison{} }
func (ra *RegressionAnalyzer) analyzeTrendForMetric(metricName string, data []*PerformanceData) TrendInfo { return TrendInfo{} }
func (pb *PerformanceBaseline) Update(data *PerformanceData) error { return nil }
func (ph *PerformanceHistory) Add(data *PerformanceData) {}
func (ph *PerformanceHistory) Query(query HistoryQuery) ([]*PerformanceData, error) { return nil, nil }
func (rc *RegressionCache) Get(key string) *RegressionResult { return nil }
func (rc *RegressionCache) Set(key string, result *RegressionResult) {}
func (ram *RegressionAlertManager) SendAlert(result *RegressionResult) {}
func (rca *RootCauseAnalyzer) Analyze(ctx context.Context, data *PerformanceData, baseline *PerformanceBaseline) (*RootCauseInfo, error) { return nil, nil }

// String methods for enums
func (dm DetectionMethod) String() string {
    switch dm {
    case StatisticalDetection:
        return "statistical"
    case ThresholdDetection:
        return "threshold"
    case TrendDetection:
        return "trend"
    case ChangePointDetection:
        return "changepoint"
    case MLDetection:
        return "ml"
    case EnsembleDetection:
        return "ensemble"
    default:
        return "unknown"
    }
}

// Example usage
func ExampleRegressionAnalysis() {
    // Create analyzer configuration
    config := RegressionConfig{
        DetectionMethods:    []DetectionMethod{StatisticalDetection, TrendDetection, ChangePointDetection},
        SensitivityLevel:    MediumSensitivity,
        BaselineWindow:      7 * 24 * time.Hour, // 7 days
        ComparisonWindow:    time.Hour,
        MinDataPoints:       10,
        ConfidenceLevel:     0.95,
        SignificanceLevel:   0.05,
        ChangeThreshold:     0.1, // 10% change threshold
        EnableAutoBaseline:  true,
        EnableTrendAnalysis: true,
        EnableAlerts:        true,
        EnableRootCause:     true,
        MaxHistory:          10000,
        UpdateInterval:      time.Minute,
    }

    // Create analyzer
    analyzer := NewRegressionAnalyzer(config)

    // Create sample performance data
    data := &PerformanceData{
        ID:        "perf-001",
        Timestamp: time.Now(),
        Metrics: map[string]MetricValue{
            "response_time": {
                Value:   150.5,
                Unit:    "ms",
                Type:    LatencyMetric,
                Samples: []float64{145.2, 148.7, 152.1, 149.8, 154.2},
                Statistics: DescriptiveStats{
                    Count:  5,
                    Mean:   150.0,
                    Median: 149.8,
                    StdDev: 3.2,
                    Min:    145.2,
                    Max:    154.2,
                },
            },
            "throughput": {
                Value:   950.2,
                Unit:    "req/s",
                Type:    ThroughputMetric,
                Samples: []float64{945.1, 952.3, 948.7, 951.8, 953.2},
                Statistics: DescriptiveStats{
                    Count:  5,
                    Mean:   950.2,
                    Median: 951.8,
                    StdDev: 3.1,
                    Min:    945.1,
                    Max:    953.2,
                },
            },
        },
        Build: BuildInfo{
            Version: "v1.2.3",
            Commit:  "abc123def456",
            Branch:  "main",
        },
        Environment: Environment{
            OS:           "linux",
            Architecture: "amd64",
            GoVersion:    "1.21.0",
            CPUCores:     8,
            Memory:       16 * 1024 * 1024 * 1024, // 16GB
        },
        Quality: DataQuality{
            Completeness: 1.0,
            Stability:    0.95,
            Reliability:  0.98,
            OverallScore: 0.97,
        },
    }

    // Analyze for regressions
    ctx := context.Background()
    result, err := analyzer.AnalyzeRegression(ctx, data)
    if err != nil {
        fmt.Printf("Regression analysis failed: %v\n", err)
        return
    }

    fmt.Println("Regression Analysis Results:")
    fmt.Printf("Regression detected: %t\n", result.Detected)
    if result.Detected {
        fmt.Printf("Severity: %v\n", result.Severity)
        fmt.Printf("Confidence: %.2f\n", result.Confidence)
        fmt.Printf("Affected metrics: %d\n", len(result.AffectedMetrics))

        for _, metric := range result.AffectedMetrics {
            fmt.Printf("  - %s: %.2f -> %.2f (%.2f%% change)\n",
                metric.Name,
                metric.BaselineValue,
                metric.CurrentValue,
                metric.Change.Relative*100)
        }

        if len(result.Recommendations) > 0 {
            fmt.Println("Recommendations:")
            for _, rec := range result.Recommendations {
                fmt.Printf("  - %s: %s\n", rec.Type, rec.Description)
            }
        }
    }

    fmt.Printf("Analysis completed at: %v\n", result.Timestamp)
}

Statistical Methods

Advanced statistical techniques for robust regression detection.

Hypothesis Testing

Statistical hypothesis testing for performance comparisons.

Change Point Detection

Algorithms for detecting significant changes in performance metrics.

Time Series Analysis

Time series methods for trend analysis and forecasting.

Automated Monitoring

Continuous monitoring systems for real-time regression detection.

Real-time Detection

Streaming analysis for immediate regression identification.

Baseline Management

Automated baseline establishment and maintenance.

Alert Integration

Integration with alerting systems for timely notifications.

Best Practices

1. Baseline Quality: Maintain high-quality baselines with sufficient data
2. Multiple Methods: Use multiple detection methods for robust analysis
3. Statistical Rigor: Apply proper statistical methods with appropriate thresholds
4. Context Awareness: Consider environmental and deployment context
5. Root Cause Analysis: Implement comprehensive root cause identification
6. Automated Response: Automate common remediation actions
7. Continuous Learning: Continuously improve detection algorithms
8. Documentation: Maintain detailed documentation of regression events

Summary

Performance regression analysis provides critical capabilities for maintaining application quality:

1. Early Detection: Identify performance regressions as soon as they occur
2. Statistical Rigor: Apply robust statistical methods for reliable detection
3. Root Cause Analysis: Automatically identify likely causes of regressions
4. Impact Assessment: Quantify the business and technical impact
5. Automated Response: Implement automated remediation for common issues
6. Continuous Improvement: Learn from historical data to improve detection

These techniques enable organizations to maintain consistent application performance and quickly address issues before they impact users.