Architecture Overview

System Design

The Review Bot Automator is designed as a modular, extensible system that can intelligently resolve conflicts in GitHub PR comments. The architecture follows a pipeline pattern with clear separation of concerns.

Core Components

1. Comment Parser & Extractor

Location: src/pr_conflict_resolver/integrations/

Responsible for:

  • Fetching PR comments from GitHub API

  • Parsing different comment formats (suggestions, diffs, codemods)

  • Extracting multi-option selections

  • Normalizing comment data

Key Classes:

  • GitHubCommentExtractor: Fetches and parses GitHub comments

  • CodeRabbitParser: Specialized parser for CodeRabbit format

  • CommentNormalizer: Standardizes comment data

2. Conflict Detection Engine

Location: src/pr_conflict_resolver/analysis/

Analyzes comments for potential conflicts:

  • Line range overlap detection

  • Semantic duplicate detection

  • File-type specific conflict analysis

  • Impact assessment

Key Classes:

  • ConflictDetector: Main conflict detection logic

  • SemanticAnalyzer: Analyzes structured file conflicts

  • ImpactAssessor: Evaluates change impact and risk

3. File-Type Handlers

Location: src/pr_conflict_resolver/handlers/

Specialized handlers for different file types:

  • JSON: Duplicate key detection, key-level merging

  • YAML: Comment preservation, structure-aware merging

  • TOML: Section merging, format preservation

  • Python/TypeScript: AST-aware analysis (planned)

Key Classes:

  • BaseHandler: Abstract base class for all handlers

  • JsonHandler: JSON-specific conflict resolution

  • YamlHandler: YAML-specific conflict resolution

  • TomlHandler: TOML-specific conflict resolution

4. Priority System

Location: src/pr_conflict_resolver/core/

Determines priority levels for different change types:

  • User selections (highest priority)

  • Security fixes

  • Syntax errors

  • Regular suggestions

  • Formatting changes (lowest priority)

Key Classes:

  • PriorityCalculator: Calculates change priorities

  • PriorityLearner: ML-assisted priority learning

  • DynamicPriorityAdjuster: Context-aware priority adjustment

5. Resolution Strategies

Location: src/pr_conflict_resolver/strategies/

Implements different conflict resolution strategies:

  • Skip: Skip conflicting change

  • Override: Override lower-priority change

  • Merge: Semantic merging of compatible changes

  • Sequential: Apply changes in sequence

  • Defer: Escalate to user

Key Classes:

  • ResolutionStrategy: Base strategy class

  • PriorityBasedStrategy: Priority-based resolution

  • SemanticMergeStrategy: Semantic merging

  • InteractiveStrategy: User-guided resolution

6. Application Engine

Location: src/pr_conflict_resolver/core/

Applies resolved changes to files:

  • Backup creation

  • Change application

  • Validation

  • Rollback on failure

Key Classes:

  • ChangeApplicator: Applies changes to files

  • BackupManager: Manages file backups

  • ValidationEngine: Validates applied changes

7. Reporting & Metrics

Location: src/pr_conflict_resolver/core/

Generates reports and tracks metrics:

  • Conflict summaries

  • Visual diffs

  • Success rate tracking

  • Performance metrics

Key Classes:

  • ReportGenerator: Creates conflict reports

  • MetricsCollector: Tracks resolution metrics

  • VisualDiffGenerator: Creates visual diffs

Data Flow

GitHub PR Comments
        ↓
Comment Parser & Extractor
        ↓
Conflict Detection Engine
        ↓
    ┌─────────┴─────────┐
    ↓                   ↓
File Handlers      Priority System
    ↓                   ↓
    └─────────┬─────────┘
              ↓
Resolution Strategy Selector
              ↓
Application Engine
              ↓
Reporting & Metrics

Configuration System

Preset Configurations

  • Conservative: Skip all conflicts, manual review required

  • Balanced: Priority system + semantic merging (default)

  • Aggressive: Maximize automation, user selections always win

  • Semantic: Focus on structure-aware merging for config files

Custom Configuration

Users can create custom configurations with:

  • Priority rules

  • Resolution strategies

  • File-type specific settings

  • Learning parameters

Extension Points

Custom Handlers

Implement BaseHandler to add support for new file types:

class CustomHandler(BaseHandler):
    def can_handle(self, file_path: str) -> bool:
        return file_path.endswith('.custom')

    def apply_change(self, path: str, change: Change) -> bool:
        # Custom implementation
        pass

Custom Strategies

Implement ResolutionStrategy for custom resolution logic:

class CustomStrategy(ResolutionStrategy):
    def resolve(self, conflict: Conflict) -> Resolution:
        # Custom resolution logic
        pass

Custom Integrations

Implement comment source integrations:

class CustomCommentSource(CommentSource):
    def fetch_comments(self, pr: PullRequest) -> List[Comment]:
        # Custom comment fetching
        pass

Performance Considerations

Caching

  • Conflict analysis results cached by fingerprint

  • File content cached during processing

  • Priority calculations cached by change signature

Parallel Processing

  • Multiple files processed in parallel

  • Conflict analysis parallelized

  • Large PRs processed in batches

Memory Management

  • Streaming processing for large files

  • Lazy loading of file content

  • Garbage collection of processed data

Security Considerations

Input Validation

  • All file paths validated

  • Content size limits enforced

  • Malicious content detection

Backup Management

  • Secure backup storage

  • Backup cleanup policies

  • Rollback verification

Access Control

  • GitHub token scoping

  • Repository permission checks

  • User authorization validation

Testing Strategy

Unit Tests

  • Individual component testing

  • Mock external dependencies

  • Edge case coverage

Integration Tests

  • End-to-end workflow testing

  • Real GitHub API testing (with test repos)

  • Performance benchmarking

Test Fixtures

  • Sample PR comments

  • Test repositories

  • Conflict scenarios

  • Expected outcomes

Deployment

Package Distribution

  • PyPI package distribution

  • Docker container support

  • GitHub Actions integration

Configuration Management

  • Environment-based configuration

  • Secret management

  • Configuration validation

Monitoring

  • Health checks

  • Performance metrics

  • Error tracking

  • Usage analytics

Future Enhancements

ML-Assisted Learning

  • Priority learning from user decisions

  • Conflict pattern recognition

  • Automatic strategy optimization

Advanced Merging

  • Three-way merge support

  • Intelligent conflict resolution

  • Context-aware merging

Multi-Platform Support

  • GitLab integration

  • Bitbucket support

  • Azure DevOps compatibility

Enterprise Features

  • Team-wide configuration

  • Audit logging

  • Compliance reporting

  • Advanced security controls