The Bug Finder Agent is an AI-powered tool designed to identify, analyze, and help fix bugs in your codebase. It uses advanced code analysis techniques and machine learning to detect potential issues before they cause problems in production.

Key Features

  • Automated Bug Detection: Identifies potential bugs using static and dynamic analysis
  • Code Quality Assessment: Evaluates code quality and suggests improvements
  • Security Vulnerability Detection: Finds security vulnerabilities and suggests fixes
  • Performance Issue Detection: Identifies performance bottlenecks
  • Interactive Debugging: Assists in debugging by providing context and suggestions

Usage

1. Basic Bug Scanning 

from prometheus_swarm.clients import AnthropicClient
from prometheus_swarm.workflows import BugFinderWorkflow
from prometheus_swarm.types import WorkflowConfig

config = WorkflowConfig(
    model="claude-3-opus-20240229",
    scan_type="full",
    severity_threshold="medium"
)

workflow = BugFinderWorkflow(config)
results = workflow.scan_codebase("./src")

2. Security Audit 

# Perform security-focused scan
workflow = BugFinderWorkflow(config)
security_results = workflow.security_audit({
    "scan_dependencies": True,
    "check_vulnerabilities": True,
    "audit_configurations": True
})

3. Performance Analysis 

# Analyze performance issues
workflow = BugFinderWorkflow(config)
performance_results = workflow.analyze_performance({
    "profile_code": True,
    "check_algorithms": True,
    "analyze_memory": True
})

Scan Types

Full Scan

  • Complete codebase analysis
  • Dependency checking
  • Security vulnerability assessment
  • Performance profiling
  • Code quality evaluation

Quick Scan

  • Basic syntax checking
  • Common bug patterns
  • Critical security issues
  • Major performance bottlenecks

Custom Scan

  • User-defined rules
  • Specific file types
  • Selected directories
  • Custom severity thresholds

Issue Categories

1. Logic Bugs

  • Off-by-one errors
  • Null pointer exceptions
  • Race conditions
  • Memory leaks
  • Infinite loops

2. Security Issues

  • SQL injection vulnerabilities
  • Cross-site scripting (XSS)
  • Authentication bypass
  • Insecure cryptography
  • CSRF vulnerabilities

3. Performance Issues

  • Inefficient algorithms
  • Resource leaks
  • Database query problems
  • Memory management issues
  • Network bottlenecks

Example Workflow

Here’s a complete example of using the Bug Finder Agent:

from prometheus_swarm.workflows import BugFinderWorkflow
from prometheus_swarm.types import WorkflowConfig, ScanSpec

# Define scan specification
scan_spec = ScanSpec(
    directories=["./src", "./tests"],
    exclude_patterns=["*.test.js", "*.min.js"],
    severity_levels=["high", "medium"],
    scan_types=[
        "security",
        "performance",
        "logic"
    ],
    rules={
        "max_complexity": 10,
        "max_line_length": 100,
        "require_tests": True
    }
)

# Configure workflow
config = WorkflowConfig(
    model="claude-3-opus-20240229",
    temperature=0.7
)

# Create and run workflow
workflow = BugFinderWorkflow(config)
results = workflow.run_scan(scan_spec)

# Generate report
report = workflow.generate_report({
    "format": "markdown",
    "include_fixes": True,
    "group_by": "severity"
})

# Apply suggested fixes
workflow.apply_fixes(results.fixes, interactive=True)

Configuration Options

Severity Levels

  • Critical
  • High
  • Medium
  • Low
  • Info

Scan Modes

  • Fast
  • Normal
  • Deep
  • Custom

Output Formats

  • JSON
  • Markdown
  • HTML
  • CSV
  • PDF

Integration

The Bug Finder Agent integrates with:

Version Control

  • Git
  • SVN
  • Mercurial

CI/CD Platforms

  • Jenkins
  • GitHub Actions
  • GitLab CI
  • CircleCI

Issue Trackers

  • JIRA
  • GitHub Issues
  • GitLab Issues
  • Linear

Best Practices

  1. Regular Scanning: Schedule regular automated scans
  2. Custom Rules: Define custom rules for project-specific requirements
  3. Integration Tests: Run bug finder as part of CI/CD pipeline
  4. Issue Prioritization: Focus on high-severity issues first
  5. Documentation: Document known issues and their fixes

Error Handling 

try:
    workflow = BugFinderWorkflow(config)
    results = workflow.run_scan(scan_spec)
except BugFinderError as e:
    if e.error_type == "ScanError":
        print("Scan failed:", e.details)
    elif e.error_type == "ConfigurationError":
        print("Configuration issue:", e.details)
    else:
        print("Unknown error:", str(e))

Contributing

To contribute to the Bug Finder Agent:

  1. Fork the repository
  2. Create a feature branch
  3. Add new detection rules or improve existing ones
  4. Add tests for new functionality
  5. Submit a pull request

Future Developments

Planned features include:

  • Machine learning-based bug prediction
  • More language support
  • Enhanced security scanning
  • Real-time monitoring
  • Automated fix suggestions
  • Integration with more development tools