Magda Dettlaff

25 papers C 1Journal 24
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Karl Bartolo, Peter Borg, Magda Dettlaff, Magdalena Lemanska, Pawel Zylinski
2025 J jnl
Australas. J Comb.
Magda Dettlaff, Michael A. Henning, Magdalena Lemanska, Adriana Roux, Jerzy Topp
2025 J jnl
Discuss. Math. Graph Theory
Magda Dettlaff, Michael A. Henning, Jerzy Topp
2025 J jnl
Discret. Appl. Math.
Magda Dettlaff, Magdalena Lemanska, Jerzy Topp
2025 J jnl
Ars Math. Contemp.
Magda Dettlaff, Magdalena Lemanska, Juan A. Rodríguez-Velázquez, Ismael G. Yero
2025 J jnl
Discuss. Math. Graph Theory
Abel Cabrera Martínez, Magda Dettlaff, Magdalena Lemanska, Juan Alberto Rodríguez-Velázquez
2024 J jnl
Appl. Math. Comput.
Magda Dettlaff, Hanna Furmanczyk, Iztok Peterin, Adriana Roux, Radoslaw Ziemann
2024 J jnl
Discret. Appl. Math.
Magda Dettlaff, Michael A. Henning, Jerzy Topp
2023 C conf
LAGOS
Magda Dettlaff, Magdalena Lemanska, Jerzy Topp
2022 J jnl
J. Comb. Optim.
Magda Dettlaff, Didem Gözüpek, Joanna Raczek
2021 J jnl
Symmetry
Magda Dettlaff, Magdalena Lemanska, Jerzy Topp
2021 J jnl
Graphs Comb.
Ammar Babikir, Magda Dettlaff, Michael A. Henning, Magdalena Lemanska
2021 J jnl
J. Comb. Optim.
Magda Dettlaff, Magdalena Lemanska, Juan A. Rodríguez-Velázquez
2021 J jnl
Discret. Appl. Math.
Sergio Bermudo, Magda Dettlaff, Magdalena Lemanska
2020 J jnl
AKCE Int. J. Graphs Comb.
Magda Dettlaff, Magdalena Lemanska, Jerzy Topp, Radoslaw Ziemann, Pawel Zylinski
2019 J jnl
Discuss. Math. Graph Theory
Magda Dettlaff, Joanna Raczek, Jerzy Topp
2019 J jnl
Discret. Appl. Math.
Magda Dettlaff, Magdalena Lemanska, Juan Alberto Rodríguez-Velázquez, Rita Zuazua
2019 J jnl
CoRR
Magda Dettlaff, Didem Gözüpek, Joanna Raczek
2018 J jnl
Graphs Comb.
Joanna Cyman, Magda Dettlaff, Michael A. Henning, Magdalena Lemanska, Joanna Raczek
2018 J jnl
Discuss. Math. Graph Theory
Joanna Cyman, Magda Dettlaff, Michael A. Henning, Magdalena Lemanska, Joanna Raczek
2016 J jnl
Discuss. Math. Graph Theory
Magda Dettlaff, Magdalena Lemanska, Gabriel Semanisin, Rita Zuazua
2015 J jnl
Discuss. Math. Graph Theory
Diana Avella-Alaminos, Magda Dettlaff, Magdalena Lemanska, Rita Zuazua
2014 J jnl
Discret. Appl. Math.
Magda Dettlaff, Magdalena Lemanska, Ismael González Yero
2012 J jnl
Australas. J Comb.
Magda Dettlaff, Magdalena Lemanska
2010 J jnl
Australas. J Comb.
Magda Dettlaff, Magdalena Lemanska
tests/scripts/test_macho_extractors_local.py
← Index tests/scripts/test_macho_extractors_local.py python
#!/usr/bin/env python3
"""
Local MachO extractors test - test actual extractors without server connections
"""

import sys
import os
import logging
import hashlib
from datetime import datetime, timezone
from typing import Dict, Any, Optional
from unittest.mock import Mock, patch

# Add the redb directory to the path so we can import the extractors
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'redb'))

# Mock settings to avoid database connections
with patch.dict('os.environ', {'REDB_ENV': 'test'}):
    # Import the actual extractors
    from redb.extractors.macho_extractors.macho_features import MachOFeaturesExtractor
    from redb.extractors.macho_extractors.macho_segments import MachOSegmentExtractor
    from redb.extractors.macho_extractors.macho_imports import MachOImportExtractor
    from redb.extractors.macho_extractors.macho_exports import MachOExportExtractor
    from redb.extractors.macho_extractors.macho_dylibs import MachODylibExtractor
    from redb.extractors.macho_extractors.macho_signature import MachOSignatureExtractor
    from redb.extractors.macho_extractors.macho_universal import MachOUniversalExtractor

def setup_logging():
    """Setup basic logging configuration."""
    logging.basicConfig(
        level=logging.INFO,
        format='%(asctime)s - %(levelname)s - %(message)s'
    )
    return logging.getLogger(__name__)

class MockLogger:
    """Mock logger for testing without RedB dependencies."""
    def __init__(self):
        self.logger = logging.getLogger(__name__)
    
    def debug(self, msg):
        self.logger.debug(msg)
    
    def info(self, msg):
        self.logger.info(msg)
    
    def warning(self, msg):
        self.logger.warning(msg)
    
    def error(self, msg):
        self.logger.error(msg)

class MockExporter:
    """Mock exporter that does nothing."""
    def export(self, data):
        pass

def create_mock_extractor(extractor_class, filepath):
    """Create an extractor instance with mocked dependencies."""
    log = MockLogger()
    
    # Mock the exporters to avoid database connections
    mock_exporters = [MockExporter()]
    
    # Create the extractor with mocked dependencies
    extractor = extractor_class(
        filepath=filepath,
        log=log,
        exporters=mock_exporters,
        index_prefix="test",
        elastic_index="test_macho",
        known_benign=False,
        known_malicious=False
    )
    
    return extractor

def test_extractor(extractor_class, filepath, extractor_name):
    """Test a specific extractor."""
    log = setup_logging()
    log.info(f"Testing {extractor_name}...")
    
    try:
        # Create the extractor with mocked dependencies
        extractor = create_mock_extractor(extractor_class, filepath)
        
        if not extractor.macho:
            log.error(f"{extractor_name}: No MachO object created")
            return False

        # Test the actual extract method
        result = extractor.extract()
        
        if result:
            log.info(f"{extractor_name}: Successfully extracted data")
            print(f"\n{'='*60}")
            print(f"=== {extractor_name.upper()} RESULTS ===")
            print(f"{'='*60}")
            
            if isinstance(result, list):
                print(f"📊 Extracted {len(result)} items")
                print()
                for i, item in enumerate(result):
                    print(f"📦 Item {i+1}:")
                    print(f"   {'─'*40}")
                    # Handle dataclass objects in lists
                    if hasattr(item, '__dataclass_fields__'):
                        from dataclasses import asdict
                        item_dict = asdict(item)
                        for key, value in item_dict.items():
                            if isinstance(value, (list, dict)):
                                if isinstance(value, list):
                                    print(f"   🔹 {key}: List with {len(value)} items")
                                    print(f"      {value}")
                                elif isinstance(value, dict):
                                    print(f"   🔹 {key}: Dict with {len(value)} keys")
                                    for k, v in value.items():
                                        print(f"      {k}: {v}")
                            else:
                                print(f"   🔹 {key}: {value}")
                    else:
                        # Regular dict
                        for key, value in item.items():
                            if isinstance(value, (list, dict)):
                                if isinstance(value, list):
                                    print(f"   🔹 {key}: List with {len(value)} items")
                                    print(f"      {value}")
                                elif isinstance(value, dict):
                                    print(f"   🔹 {key}: Dict with {len(value)} keys")
                                    for k, v in value.items():
                                        print(f"      {k}: {v}")
                            else:
                                print(f"   🔹 {key}: {value}")
                    print()
            else:
                print("📊 Extracted data:")
                print()
                # Handle dataclass objects
                if hasattr(result, '__dataclass_fields__'):
                    # It's a dataclass, use dataclasses.asdict
                    from dataclasses import asdict
                    result_dict = asdict(result)
                    for key, value in result_dict.items():
                        if isinstance(value, (list, dict)):
                            if isinstance(value, list):
                                print(f"🔹 {key}: List with {len(value)} items")
                                print(f"   {value}")
                            elif isinstance(value, dict):
                                print(f"🔹 {key}: Dict with {len(value)} keys")
                                for k, v in value.items():
                                    print(f"   {k}: {v}")
                        else:
                            print(f"🔹 {key}: {value}")
                        print()
                else:
                    # It's a regular dict
                    for key, value in result.items():
                        if isinstance(value, (list, dict)):
                            if isinstance(value, list):
                                print(f"🔹 {key}: List with {len(value)} items")
                                print(f"   {value}")
                            elif isinstance(value, dict):
                                print(f"🔹 {key}: Dict with {len(value)} keys")
                                for k, v in value.items():
                                    print(f"   {k}: {v}")
                        else:
                            print(f"🔹 {key}: {value}")
                        print()
        else:
            log.warning(f"{extractor_name}: No data extracted")
            print(f"\n❌ {extractor_name}: No data extracted")
        
        return True
        
    except Exception as e:
        log.error(f"{extractor_name}: Error during extraction: {e}")
        import traceback
        traceback.print_exc()
        return False

def main():
    """Main function."""
    if len(sys.argv) < 2:
        print("Usage: python test_macho_extractors_local.py <macho_file> [extractor_name]")
        print("\nAvailable extractors:")
        print("  features    - Basic MachO header and metadata")
        print("  segments    - Segment information and analysis")
        print("  imports     - Imported functions and libraries")
        print("  exports     - Exported symbols")
        print("  dylibs      - Dynamic library dependencies")
        print("  signature   - Code signing information")
        print("  universal   - FAT/Universal binary information")
        print("  all         - Test all extractors")
        sys.exit(1)
    
    filepath = sys.argv[1]
    extractor_name = sys.argv[2] if len(sys.argv) > 2 else "all"
    
    if not os.path.exists(filepath):
        print(f"File not found: {filepath}")
        sys.exit(1)
    
    # Define extractors
    extractors = {
        'features': (MachOFeaturesExtractor, "MachO Features"),
        'segments': (MachOSegmentExtractor, "MachO Segments"),
        'imports': (MachOImportExtractor, "MachO Imports"),
        'exports': (MachOExportExtractor, "MachO Exports"),
        'dylibs': (MachODylibExtractor, "MachO Dylibs"),
        'signature': (MachOSignatureExtractor, "MachO Code Signature"),
        'universal': (MachOUniversalExtractor, "MachO Universal/FAT"),
    }
    
    if extractor_name == "all":
        print(f"Testing all extractors with file: {filepath}")
        success_count = 0
        for name, (extractor_class, display_name) in extractors.items():
            if test_extractor(extractor_class, filepath, display_name):
                success_count += 1
            print("-" * 50)
        
        print(f"\n✅ {success_count}/{len(extractors)} extractors completed successfully")
        
    elif extractor_name in extractors:
        extractor_class, display_name = extractors[extractor_name]
        success = test_extractor(extractor_class, filepath, display_name)
        
        if success:
            print(f"\n✅ {display_name} testing completed successfully")
        else:
            print(f"\n❌ {display_name} testing failed")
            sys.exit(1)
    else:
        print(f"Unknown extractor: {extractor_name}")
        print("Available extractors:", ", ".join(extractors.keys()) + ", all")
        sys.exit(1)

if __name__ == "__main__":
    main()