aiwg/agentic/code/frameworks/sdlc-complete/schemas/testing/regression-learning.yaml

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# Regression Learning Schema
# Based on REF-013 MetaGPT and REF-015 Self-Refine
# Finding: Cross-task learning improves regression detection over time
# Integrates with Ralph's debug memory for continuous improvement

$schema: "https://json-schema.org/draft/2020-12/schema"
$id: "https://aiwg.io/schemas/regression-learning/v1"
title: "Regression Learning Schema"
description: |
  Schema for cross-task learning that improves regression detection through
  pattern recognition, test prioritization, and historical analysis. Stores
  accumulated knowledge from past regressions to prevent future occurrences.

  Key principles:
  - Learn from every regression
  - Build pattern taxonomy
  - Prioritize high-value tests
  - Predict regression risk
  - Share knowledge across projects

type: object
required:
  - learning_id
  - patterns
  - hotspots
  - test_effectiveness

properties:
  learning_id:
    type: string
    format: uuid
    description: "Unique identifier for this learning session"

  created_at:
    type: string
    format: date-time

  last_updated:
    type: string
    format: date-time

  patterns:
    type: array
    items:
      $ref: "#/$defs/RegressionPattern"
    description: "Learned regression patterns"

  hotspots:
    type: array
    items:
      $ref: "#/$defs/CodeHotspot"
    description: "High-risk code areas"

  test_effectiveness:
    type: array
    items:
      $ref: "#/$defs/TestEffectiveness"
    description: "Test value metrics"

  fix_templates:
    type: array
    items:
      $ref: "#/$defs/FixTemplate"
    description: "Reusable fix patterns"

  predictions:
    type: array
    items:
      $ref: "#/$defs/RegressionPrediction"
    description: "Risk predictions for code changes"

  metadata:
    type: object
    properties:
      project:
        type: string
        description: "Project identifier"
      agent:
        type: string
        description: "Agent that performed learning"
      total_regressions_analyzed:
        type: integer
      learning_confidence:
        type: number
        minimum: 0
        maximum: 1

$defs:
  RegressionPattern:
    type: object
    required:
      - pattern_id
      - pattern_name
      - category
      - occurrences
    description: "Identified recurring regression pattern"
    properties:
      pattern_id:
        type: string
        pattern: "^RP-[0-9]{3}$"
        description: "Pattern identifier (RP-XXX format)"
        examples:
          - "RP-001"
          - "RP-042"

      pattern_name:
        type: string
        description: "Human-readable pattern name"
        examples:
          - "null_access_without_check"
          - "type_mismatch_string_number"
          - "off_by_one_array_bounds"

      category:
        type: string
        enum:
          - null_undefined_access
          - type_mismatch
          - off_by_one
          - race_condition
          - missing_validation
          - logic_error
          - resource_leak
          - missing_error_handling
          - api_misuse
          - configuration_error
          - dependency_issue
          - other
        description: "Pattern category"

      occurrences:
        type: array
        items:
          type: object
          required:
            - regression_id
            - file
            - root_cause
            - fix
          properties:
            regression_id:
              type: string
              pattern: "^REG-[0-9]{4}$"
              description: "Reference to regression record"

            file:
              type: string
              description: "File where regression occurred"

            line:
              type: integer
              description: "Line number"

            function:
              type: string
              description: "Function/method name"

            root_cause:
              type: string
              description: "Root cause description"

            fix:
              type: string
              description: "How it was fixed"

            effectiveness:
              type: number
              minimum: 0
              maximum: 1
              description: "Fix success rate (0-1)"

            fix_time_hours:
              type: number
              description: "Time to fix in hours"

            recurred:
              type: boolean
              description: "Did this regression recur?"

      statistics:
        type: object
        properties:
          total_occurrences:
            type: integer
            minimum: 1

          avg_fix_time_hours:
            type: number
            description: "Average time to fix"

          recurrence_rate:
            type: number
            minimum: 0
            maximum: 1
            description: "Rate of recurrence after fix"

          detection_methods:
            type: object
            properties:
              automated_test:
                type: integer
              manual_test:
                type: integer
              production:
                type: integer
              code_review:
                type: integer
              ci_cd:
                type: integer

      fix_template:
        type: object
        properties:
          pattern:
            type: string
            description: "Template code showing fix pattern"

          applicability_rules:
            type: array
            items:
              type: object
              properties:
                rule_type:
                  type: string
                  enum: [language, error_pattern, context, file_pattern]
                value:
                  type: string
            description: "When this template applies"

          examples:
            type: array
            items:
              type: object
              properties:
                before:
                  type: string
                after:
                  type: string
                explanation:
                  type: string

      confidence:
        type: number
        minimum: 0
        maximum: 1
        description: "Confidence in this pattern (based on occurrences)"

      last_updated:
        type: string
        format: date-time

  CodeHotspot:
    type: object
    required:
      - file
      - risk_score
      - regression_history
    description: "High-risk code location"
    properties:
      file:
        type: string
        description: "File path"

      risk_score:
        type: number
        minimum: 0
        maximum: 10
        description: "Risk score (0-10 scale)"

      regression_history:
        type: array
        items:
          type: object
          properties:
            regression_id:
              type: string
            category:
              type: string
            severity:
              type: string
            detected_at:
              type: string
              format: date-time
        description: "Past regressions in this file"

      metrics:
        type: object
        properties:
          total_regressions:
            type: integer

          regressions_per_kloc:
            type: number
            description: "Regressions per 1000 lines of code"

          recent_changes:
            type: object
            properties:
              last_30_days:
                type: integer
              last_7_days:
                type: integer

          complexity_score:
            type: number
            minimum: 0
            maximum: 100
            description: "Code complexity (cyclomatic)"

          test_coverage_percent:
            type: number
            minimum: 0
            maximum: 100

          contributors:
            type: integer
            description: "Number of contributors"

      risk_factors:
        type: object
        properties:
          high_complexity:
            type: boolean
          frequent_changes:
            type: boolean
          multiple_regressions:
            type: boolean
          low_test_coverage:
            type: boolean
          critical_path:
            type: boolean
          many_contributors:
            type: boolean

      recommended_actions:
        type: array
        items:
          type: string
        description: "Actionable recommendations"

      test_priority:
        type: string
        enum: [critical, high, medium, low]
        description: "Test execution priority"

  TestEffectiveness:
    type: object
    required:
      - test_path
      - regression_detection_rate
    description: "Effectiveness metrics for a test"
    properties:
      test_path:
        type: string
        description: "Path to test file"

      regression_detection_rate:
        type: number
        minimum: 0
        maximum: 1
        description: "Percentage of regressions caught (0-1)"

      detected_regressions:
        type: array
        items:
          type: string
          pattern: "^REG-[0-9]{4}$"
        description: "Regressions this test caught"

      missed_regressions:
        type: array
        items:
          type: object
          properties:
            regression_id:
              type: string
            reason:
              type: string
              description: "Why test missed this regression"
        description: "Regressions this test should have caught"

      false_positive_rate:
        type: number
        minimum: 0
        maximum: 1
        description: "Rate of false alarms"

      execution_stats:
        type: object
        properties:
          avg_duration_ms:
            type: number
            description: "Average execution time"

          success_rate:
            type: number
            minimum: 0
            maximum: 1
            description: "Rate of passing (stability)"

          flakiness_score:
            type: number
            minimum: 0
            maximum: 1
            description: "Test flakiness (0=stable, 1=very flaky)"

      priority_score:
        type: number
        minimum: 0
        maximum: 10
        description: "Test value score (0-10)"

      recommendations:
        type: array
        items:
          type: string
        description: "How to improve this test"

  FixTemplate:
    type: object
    required:
      - template_id
      - name
      - pattern
    description: "Reusable fix pattern"
    properties:
      template_id:
        type: string
        pattern: "^FT-[0-9]{3}$"
        description: "Fix template identifier"

      name:
        type: string
        description: "Template name"
        examples:
          - "null-check"
          - "type-validation"
          - "error-handling"

      pattern:
        type: string
        description: "Template code"

      applies_to:
        type: object
        properties:
          categories:
            type: array
            items:
              type: string
          languages:
            type: array
            items:
              type: string
          error_patterns:
            type: array
            items:
              type: string

      examples:
        type: array
        items:
          type: object
          properties:
            before:
              type: string
            after:
              type: string
            context:
              type: string

      effectiveness:
        type: number
        minimum: 0
        maximum: 1
        description: "Success rate when applied"

      usage_count:
        type: integer
        description: "Times this template was used"

  RegressionPrediction:
    type: object
    required:
      - prediction_id
      - file
      - risk_level
      - confidence
    description: "Prediction of regression risk"
    properties:
      prediction_id:
        type: string
        format: uuid

      timestamp:
        type: string
        format: date-time

      file:
        type: string
        description: "File being analyzed"

      change_type:
        type: string
        enum: [addition, modification, deletion, rename]

      lines_changed:
        type: integer

      risk_level:
        type: string
        enum: [critical, high, medium, low]
        description: "Predicted risk level"

      confidence:
        type: number
        minimum: 0
        maximum: 1
        description: "Confidence in prediction"

      risk_factors:
        type: array
        items:
          type: object
          properties:
            factor:
              type: string
              description: "Risk factor description"
            weight:
              type: number
              minimum: 0
              maximum: 1
        description: "Factors contributing to risk"

      similar_past_changes:
        type: array
        items:
          type: object
          properties:
            commit:
              type: string
            lines_changed:
              type: integer
            result:
              type: string
              enum: [clean, regression]
            regression_id:
              type: string
            time_to_detect_hours:
              type: number
        description: "Similar changes from history"

      recommendations:
        type: array
        items:
          type: string
        description: "Recommended actions"

      suggested_tests:
        type: array
        items:
          type: string
        description: "Tests to run for this change"

      actual_outcome:
        type: object
        properties:
          regression_occurred:
            type: boolean
          regression_id:
            type: string
          prediction_correct:
            type: boolean
        description: "Actual outcome (for learning)"

# Test Prioritization Algorithm

test_prioritization:
  description: "Algorithm for prioritizing test execution"

  factors:
    code_change_correlation:
      weight: 0.30
      description: "How often this test catches changes in affected code"

    historical_regression_detection:
      weight: 0.25
      description: "Past regression detection rate"

    code_hotspot_coverage:
      weight: 0.20
      description: "Whether test covers high-risk areas"

    recent_failure_trend:
      weight: 0.15
      description: "Recent failure patterns"

    execution_efficiency:
      weight: 0.10
      description: "Test execution speed"

  priority_levels:
    critical:
      threshold: 8.0
      description: "Run first, never skip"

    high:
      threshold: 6.0
      description: "Run early"

    medium:
      threshold: 4.0
      description: "Standard priority"

    low:
      threshold: 0.0
      description: "Run if time allows, may skip in fast mode"

# Cross-Project Learning

cross_project_learning:
  description: "Share learning across projects"

  shared_patterns:
    - null_undefined_access
    - type_mismatch
    - missing_validation
    - off_by_one
    - race_condition
    - logic_error
    - resource_leak
    - missing_error_handling
    - api_misuse
    - configuration_error

  privacy:
    anonymize_file_paths: true
    anonymize_business_logic: true
    share_only_patterns: true
    require_opt_in: true

  storage:
    location: "~/.aiwg/global-learning/"
    format: yaml
    encryption: optional

# Metrics

metrics:
  learning_effectiveness:
    pattern_accuracy:
      description: "Pattern matching accuracy"
      target: 0.85
      calculation: "correct_matches / total_matches"

    fix_template_success_rate:
      description: "Fix template effectiveness"
      target: 0.90
      calculation: "successful_fixes / total_applications"

    prediction_accuracy:
      description: "Risk prediction accuracy"
      target: 0.75
      calculation: "correct_predictions / total_predictions"

    test_prioritization_efficiency:
      description: "Time saved by prioritization"
      target: 0.50
      calculation: "time_saved / baseline_time"

    false_positive_rate:
      description: "Rate of spurious alerts"
      target: 0.10
      calculation: "false_positives / total_predictions"

    cross_project_reuse:
      description: "Pattern reuse across projects"
      target: 0.30
      calculation: "patterns_reused / total_patterns"

# Integration Hooks

integration:
  ralph_hooks:
    on_test_failure:
      - query_similar_past_failures
      - retrieve_fix_templates
      - apply_learned_patterns
      - update_pattern_effectiveness

    on_test_success:
      - record_successful_fix
      - increment_fix_effectiveness
      - update_confidence_scores

    on_regression_detected:
      - create_regression_record
      - analyze_root_cause
      - store_in_learning_memory
      - update_hotspot_scores
      - adjust_test_priorities

  debug_memory:
    enabled: true
    integration_path: "@agentic/code/addons/ralph/schemas/debug-memory.yaml"
    cross_session_learning: true

  regression_schema:
    enabled: true
    integration_path: "@agentic/code/frameworks/sdlc-complete/schemas/testing/regression.yaml"
    baseline_integration: true

# Storage Structure

storage:
  paths:
    patterns: ".aiwg/ralph/learning/regression-patterns.yaml"
    hotspots: ".aiwg/ralph/learning/code-hotspots.yaml"
    test_effectiveness: ".aiwg/ralph/learning/test-effectiveness.yaml"
    fix_templates: ".aiwg/ralph/learning/fix-templates/"
    predictions: ".aiwg/ralph/learning/predictions/"
    analytics: ".aiwg/ralph/learning/analytics/"

  retention:
    regression_records: 365  # days
    pattern_library: -1      # forever
    effectiveness_metrics: 180
    predictions: 90

  indexing:
    by_pattern_category: true
    by_file_path: true
    by_regression_id: true
    by_risk_score: true

# Examples

examples:
  pattern_example:
    pattern_id: "RP-001"
    pattern_name: "null_access_without_check"
    category: null_undefined_access
    occurrences:
      - regression_id: "REG-0023"
        file: "src/auth/validate.ts"
        line: 15
        function: "validateInput"
        root_cause: "Missing null check before property access"
        fix: "Added early return for null/undefined"
        effectiveness: 1.0
        fix_time_hours: 1.2
        recurred: false
    statistics:
      total_occurrences: 3
      avg_fix_time_hours: 1.5
      recurrence_rate: 0.0
    confidence: 0.95

  hotspot_example:
    file: "src/auth/validate.ts"
    risk_score: 8.5
    regression_history:
      - regression_id: "REG-0023"
        category: null_undefined_access
        severity: high
    metrics:
      total_regressions: 3
      regressions_per_kloc: 2.1
      test_coverage_percent: 65
    risk_factors:
      high_complexity: true
      frequent_changes: true
      multiple_regressions: true
    test_priority: critical

  prediction_example:
    prediction_id: "pred-12345678"
    file: "src/payments/process.ts"
    change_type: modification
    lines_changed: 45
    risk_level: high
    confidence: 0.82
    risk_factors:
      - factor: "Known hotspot (REG-0034, REG-0067)"
        weight: 0.35
      - factor: "Large change (45 lines)"
        weight: 0.25
    recommendations:
      - "Run full payment test suite"
      - "Add integration tests for new code paths"
    suggested_tests:
      - "test/payments/process.test.ts"
      - "test/integration/payment-flow.test.ts"

# Validation Rules

validation:
  pattern_creation:
    min_occurrences: 2
    min_confidence: 0.70

  hotspot_scoring:
    factors_required: 3
    min_risk_score: 0.0
    max_risk_score: 10.0

  prediction_acceptance:
    min_confidence: 0.60
    require_similar_history: false

# References

references:
  research:
    - "@.aiwg/research/findings/REF-013-metagpt.md"
    - "@.aiwg/research/findings/REF-015-self-refine.md"

  schemas:
    - "@agentic/code/addons/ralph/schemas/debug-memory.yaml"
    - "@agentic/code/frameworks/sdlc-complete/schemas/testing/regression.yaml"
    - "@agentic/code/addons/ralph/schemas/iteration-analytics.yaml"

  rules:
    - "@.claude/rules/executable-feedback.md"
    - "@.claude/rules/best-output-selection.md"

  skills:
    - "@agentic/code/frameworks/sdlc-complete/skills/regression-learning/SKILL.md"
    - "@agentic/code/frameworks/sdlc-complete/skills/regression-baseline/SKILL.md"
    - "@agentic/code/frameworks/sdlc-complete/skills/regression-bisect/SKILL.md"