Instruction: crea un app con python thinker dove c'è un quadrato grande e si muove lentamente in una direzione casulae. quando va al bordo però socmapre, e si generano 2 quadrati di metà della grandezza di quello che è andato a sbattere contro il muro. il ciclo si ripete all'infinito

import pytest
import tkinter as tk
import random
import importlib
import inspect
from unittest.mock import MagicMock, patch
import time
import os
import sys
import re

# Helper functions for testing

def find_app_class(module):
    """Find the main application class in a module."""
    for name, obj in inspect.getmembers(module):
        if inspect.isclass(obj):
            # Check if it's a tkinter app class
            if (hasattr(obj, 'canvas') or
                'Canvas' in str(obj.__dict__) or
                any('canvas' in attr.lower() for attr in dir(obj))):
                return obj
    return None

def check_for_movement_method(app_instance):
    """Check if the app instance has any movement-related methods."""
    movement_methods = [
        'move_square', 'move', 'animate', 'update', 'animation',
        'move_squares', 'animation_loop'
    ]

    for method in movement_methods:
        if hasattr(app_instance, method) and callable(getattr(app_instance, method)):
            return True

    # Check all methods for movement-related code
    for name, method in inspect.getmembers(app_instance, predicate=inspect.ismethod):
        if name.startswith('__'):
            continue
        try:
            source = inspect.getsource(method)
            if ('move' in source or 'dx' in source or 'dy' in source):
                return True
        except (TypeError, OSError):
            pass

    return False

def get_module_source_safely(module):
    """Safely get module source code with fallback."""
    try:
        if hasattr(module, '__file__'):
            with open(module.__file__, 'r') as f:
                return f.read()
        else:
            return inspect.getsource(module)
    except (OSError, TypeError):
        # Return empty string if we can't get source
        return ""

def get_class_source_safely(cls):
    """Safely get class source code with fallback."""
    try:
        return inspect.getsource(cls)
    except (OSError, TypeError):
        # Return empty string if we can't get source
        return ""

def check_module_for_patterns(module, patterns):
    """Check if any pattern exists in the module source code or attributes."""
    # Try to get source code first
    module_source = get_module_source_safely(module)

    # Check source code for patterns
    if module_source:
        if any(pattern in module_source for pattern in patterns):
            return True

    # If no patterns found or no source code available, check attributes
    module_members = dir(module)
    for pattern in patterns:
        if any(pattern.lower() in attr.lower() for attr in module_members):
            return True

    return False

# Test cases

def test_has_required_modules(implementation):
    """Test that the implementation imports necessary modules"""
    impl_name, module = implementation

    # First check directly in the source code
    module_source = get_module_source_safely(module)

    # Expanded pattern matching for imports
    tkinter_patterns = [
        "import tkinter", "from tkinter import", "import tk",
        "Tk(", "Canvas(", "tk.Tk", "tk.Canvas"
    ]

    random_patterns = [
        "import random", "from random import", "random.choice",
        "random.randint", "random.random"
    ]

    # Check for tkinter imports
    has_tkinter = any(pattern in module_source for pattern in tkinter_patterns)

    # Check for random imports
    has_random = any(pattern in module_source for pattern in random_patterns)

    # If not found in source, check for evidence in module members
    if not has_tkinter:
        module_members = dir(module)
        tkinter_attributes = ['Tk', 'Canvas', 'Frame', 'Label', 'Button', 'mainloop', 'create_rectangle']
        has_tkinter = any(attr in module_members for attr in tkinter_attributes)

        # Also check if any class has canvas attribute
        for name, obj in inspect.getmembers(module):
            if inspect.isclass(obj) and hasattr(obj, 'canvas'):
                has_tkinter = True
                break

    if not has_random:
        module_members = dir(module)
        has_random = 'random' in module_members or any('random' in attr.lower() for attr in module_members)

    assert has_tkinter, f"{impl_name} should include tkinter functionality"
    assert has_random, f"{impl_name} should include random functionality"

def test_has_tkinter_app_class(implementation):
    """Test that the implementation has a class or functions that manage a tkinter app"""
    impl_name, module = implementation

    # First check module source code for Canvas and create_rectangle
    module_source = get_module_source_safely(module)
    if "Canvas" in module_source and "create_rectangle" in module_source:
        assert True
        return

    # Find classes with canvas and rectangle creation methods
    has_app_class = False

    for name, obj in inspect.getmembers(module):
        if inspect.isclass(obj):
            # Check if it's a tkinter app class through various means
            if (hasattr(obj, 'canvas') or
                'Canvas' in str(obj.__dict__) or
                any('canvas' in attr.lower() for attr in dir(obj))):
                has_app_class = True
                break

            # Check source code
            class_source = get_class_source_safely(obj)
            if class_source and ("Canvas" in class_source or "create_rectangle" in class_source):
                has_app_class = True
                break

    # Check for functions that might contain tkinter functionality
    if not has_app_class:
        for name, obj in inspect.getmembers(module):
            if callable(obj) and not inspect.isclass(obj):
                try:
                    func_source = inspect.getsource(obj)
                    if "Canvas" in func_source or "create_rectangle" in func_source:
                        has_app_class = True
                        break
                except (OSError, TypeError):
                    continue

    # Final fallback - check module attributes for any canvas-related items
    if not has_app_class:
        for attr in dir(module):
            if 'canvas' in attr.lower() or 'rectangle' in attr.lower() or 'tk' in attr.lower():
                has_app_class = True
                break

    assert has_app_class, f"{impl_name} should have a class or functions to manage the tkinter app"

def test_moving_square_functionality(implementation):
    """Test that squares can move in the implementation"""
    impl_name, module = implementation

    # First check module source for movement patterns
    module_source = get_module_source_safely(module)
    movement_patterns = ["move", "dx", "dy", "canvas.move", "+=", "-=", "after("]

    # If we find movement patterns in the source, the test passes
    if any(pattern in module_source for pattern in movement_patterns):
        assert True
        return

    # If not found in static analysis, try to test dynamically
    with patch('tkinter.Tk'), patch('tkinter.Canvas') as mock_canvas:
        # Set up mock canvas
        mock_canvas.return_value.coords.return_value = [100, 100, 200, 200]
        mock_canvas.return_value.winfo_width.return_value = 800
        mock_canvas.return_value.winfo_height.return_value = 600
        mock_canvas.return_value.create_rectangle.return_value = 1
        mock_canvas.return_value.find_all.return_value = [1]

        # Find and test the main app class
        app_class = find_app_class(module)

        if app_class:
            root = MagicMock()

            try:
                # Create app instance
                app_instance = app_class(root)

                # Try to invoke movement methods
                movement_method_called = False

                # Check for common movement methods
                for method_name in ['move_square', 'animate', 'update', 'move', 'animation']:
                    if hasattr(app_instance, method_name) and callable(getattr(app_instance, method_name)):
                        method = getattr(app_instance, method_name)
                        method()
                        movement_method_called = True
                        break

                # If no method was called, check if canvas.move was called during initialization
                canvas_ops_called = mock_canvas.return_value.move.called or len(mock_canvas.return_value.method_calls) > 0

                assert movement_method_called or canvas_ops_called, f"{impl_name} should implement square movement"
            except Exception as e:
                # If that fails, we'll accept finding movement patterns in any method
                for name, obj in inspect.getmembers(module):
                    if callable(obj):
                        try:
                            func_source = inspect.getsource(obj)
                            if any(pattern in func_source for pattern in movement_patterns):
                                assert True
                                return
                        except (OSError, TypeError):
                            continue

                # Final fallback - just check for movement again in the module source
                assert any(pattern in module_source for pattern in movement_patterns), \
                    f"{impl_name} should implement square movement functionality"

def test_boundary_detection(implementation):
    """Test that the implementation detects when squares hit boundaries"""
    impl_name, module = implementation

    # Check for boundary detection patterns in the module source
    module_source = get_module_source_safely(module)
    boundary_patterns = [
        "if x", "width", "height", "boundary", "border", "edge",
        "x1 >", "x2 <", "y1 >", "y2 <", "winfo_width",
        "winfo_height", "< 0", "> canvas", "< canvas"
    ]

    # If we find boundary patterns in the source, the test passes
    if any(pattern in module_source for pattern in boundary_patterns):
        assert True
        return

    # Try to test dynamically with mocks
    with patch('tkinter.Tk'), patch('tkinter.Canvas') as mock_canvas:
        # Set up mock canvas with coordinates at the boundary
        mock_canvas.return_value.coords.return_value = [790, 100, 810, 200]  # Right boundary
        mock_canvas.return_value.winfo_width.return_value = 800
        mock_canvas.return_value.winfo_height.return_value = 600
        mock_canvas.return_value.create_rectangle.return_value = 1
        mock_canvas.return_value.find_all.return_value = [1]

        # Find and test the main app class
        app_class = find_app_class(module)

        if app_class:
            root = MagicMock()

            try:
                app_instance = app_class(root)

                # Reset mocks to check calls
                mock_canvas.return_value.delete.reset_mock()
                mock_canvas.return_value.move.reset_mock()
                mock_canvas.return_value.create_rectangle.reset_mock()

                # Try to invoke movement or animation methods
                for method_name in ['move_square', 'animate', 'update', 'move', 'animation']:
                    if hasattr(app_instance, method_name) and callable(getattr(app_instance, method_name)):
                        method = getattr(app_instance, method_name)
                        method()
                        break

                # Check if boundary handling methods were called
                boundary_handled = (
                    mock_canvas.return_value.delete.called or
                    mock_canvas.return_value.create_rectangle.called or
                    "dx" in str(mock_canvas.return_value.method_calls) or
                    "dy" in str(mock_canvas.return_value.method_calls)
                )

                assert boundary_handled, f"{impl_name} should handle boundary collisions"
            except Exception as e:
                # Fallback - check again for boundary patterns in any method source
                for name, obj in inspect.getmembers(module):
                    if callable(obj):
                        try:
                            func_source = inspect.getsource(obj)
                            if any(pattern in func_source for pattern in boundary_patterns):
                                assert True
                                return
                        except (OSError, TypeError):
                            continue

                # Final fallback - just check again for boundary patterns in module source
                assert any(pattern in module_source for pattern in boundary_patterns), \
                    f"{impl_name} should implement boundary detection"

def test_square_division(implementation):
    """Test that when squares hit boundaries, they divide into two smaller squares"""
    impl_name, module = implementation

    # Check for division patterns in the module source
    module_source = get_module_source_safely(module)
    division_patterns = [
        "/2", "/ 2", "new_size", "half", "split", "divide",
        "create_rectangle", "smaller", "size/2", "size / 2"
    ]

    # If we find division patterns in the source, the test passes
    if any(pattern in module_source for pattern in division_patterns):
        assert True
        return

    # Try to test dynamically with mocks
    with patch('tkinter.Tk'), patch('tkinter.Canvas') as mock_canvas:
        # Set up mock canvas with coordinates at the boundary
        mock_canvas.return_value.coords.return_value = [790, 100, 810, 200]  # Right boundary
        mock_canvas.return_value.winfo_width.return_value = 800
        mock_canvas.return_value.winfo_height.return_value = 600
        mock_canvas.return_value.create_rectangle.return_value = 1
        mock_canvas.return_value.find_all.return_value = [1]

        # Find and test the main app class
        app_class = find_app_class(module)

        if app_class:
            root = MagicMock()

            try:
                app_instance = app_class(root)

                # Reset create_rectangle mock to check calls
                mock_canvas.return_value.create_rectangle.reset_mock()

                # Try to invoke movement or animation methods
                for method_name in ['move_square', 'animate', 'update', 'move', 'animation']:
                    if hasattr(app_instance, method_name) and callable(getattr(app_instance, method_name)):
                        method = getattr(app_instance, method_name)
                        method()
                        break

                # Check if new squares were created
                division_occurred = mock_canvas.return_value.create_rectangle.call_count >= 1

                if division_occurred:
                    assert True
                    return

                # If no division detected, check source code of class and methods
                class_source = get_class_source_safely(app_class)
                has_division_logic = any(pattern in class_source for pattern in division_patterns)

                if has_division_logic:
                    assert True
                    return

                # Check individual methods
                for name, method in inspect.getmembers(app_instance, predicate=inspect.ismethod):
                    if name.startswith('__'):
                        continue
                    try:
                        method_source = inspect.getsource(method)
                        if any(pattern in method_source for pattern in division_patterns):
                            assert True
                            return
                    except (OSError, TypeError):
                        continue

                # Final fallback
                assert any(pattern in module_source for pattern in division_patterns), \
                    f"{impl_name} should implement square division functionality"
            except Exception as e:
                # If that fails, we'll accept finding division patterns in any method
                for name, obj in inspect.getmembers(module):
                    if callable(obj):
                        try:
                            func_source = inspect.getsource(obj)
                            if any(pattern in func_source for pattern in division_patterns):
                                assert True
                                return
                        except (OSError, TypeError):
                            continue

                # Final fallback - just check again for division patterns in module source
                assert any(pattern in module_source for pattern in division_patterns), \
                    f"{impl_name} should implement square division functionality"

def test_safe_random_positioning(implementation):
    """Test that the implementation handles random positioning safely"""
    impl_name, module = implementation

    # Check for safe random range usage in the source code
    module_source = get_module_source_safely(module)

    # More precise pattern matching for the specific issue
    risky_patterns = [
        r'randint\s*\(\s*\d+\s*,\s*[^)]*winfo_(width|height)\s*\(\s*\)\s*-\s*\w+',
        r'randrange\s*\(\s*\d+\s*,\s*[^)]*winfo_(width|height)\s*\(\s*\)\s*-\s*\w+',
        r'random\.\w+\s*\([^)]*canvas\.winfo_(width|height)\s*\(\s*\)\s*-\s*\w+'
    ]

    # Look for proper safety checks specifically for subtraction cases
    subtraction_safety_checks = [
        r'if\s+[^}]*winfo_(width|height)\s*\(\s*\)\s*>\s*\w+', # Check if width > size
        r'max\s*\(\s*\d+\s*,\s*[^)]*winfo_(width|height)', # Using max to ensure positive value
        r'(width|height)\s*=\s*[^;]*;\s*.*if\s+[^}]*(width|height)\s*>', # Storing width then checking
        r'update(_idletasks)?\s*\(\s*\).*?random', # update before random
        r'(width|height)\s*=\s*\d+\s*[^;]*;', # Hardcoded fallback values
        r'try\s*:[^}]*winfo_(width|height)[^}]*except', # Try/except around canvas operations
    ]

    has_risky_pattern = any(re.search(pattern, module_source, re.IGNORECASE) for pattern in risky_patterns)
    has_proper_safety_check = any(re.search(pattern, module_source, re.IGNORECASE) for pattern in subtraction_safety_checks)

    # Check for the specific risky pattern with a subtraction after winfo_width/height
    if has_risky_pattern and not has_proper_safety_check:
        assert False, (
            f"{impl_name} contains unsafe random positioning code that subtracts values from canvas dimensions "
            f"without proper validation. This can lead to 'empty range' errors when canvas dimensions are initially "
            f"zero or smaller than the subtracted value. Add validation checks or delay random positioning until "
            f"canvas dimensions are properly initialized."
        )

    # Dynamic testing - try to reproduce the specific error condition
    with patch('tkinter.Tk'), patch('tkinter.Canvas') as mock_canvas, patch('random.randint') as mock_randint:
        # Set up conditions to trigger the empty range error
        mock_canvas.return_value.winfo_width.return_value = 40
        mock_canvas.return_value.winfo_height.return_value = 40

        # If randint is called with an empty range, it should raise an error
        mock_randint.side_effect = lambda a, b: exec('raise ValueError("empty range in randrange(0, -10)") if b < a else 10')

        app_class = find_app_class(module)
        if app_class:
            try:
                root = MagicMock()
                app_instance = app_class(root)

                # After initialization, simulate canvas resize to smaller value
                mock_canvas.return_value.winfo_width.return_value = 20
                mock_canvas.return_value.winfo_height.return_value = 20

                # Try methods that might use random positioning with subtracted values
                for method_name in ['move_square', 'animate', 'update', 'move', 'animation']:
                    if hasattr(app_instance, method_name) and callable(getattr(app_instance, method_name)):
                        try:
                            method = getattr(app_instance, method_name)
                            method()
                        except ValueError as e:
                            if "empty range" in str(e):
                                assert False, (
                                    f"{impl_name} has an 'empty range' error when using random positioning. "
                                    f"This happens when canvas dimensions are smaller than the subtracted value. "
                                    f"Error: {e}. Add proper validation before using random with canvas dimensions."
                                )
            except Exception as e:
                # Only fail for the specific ValueError we're looking for
                if isinstance(e, ValueError) and "empty range" in str(e):
                    assert False, (
                        f"{impl_name} has an 'empty range' error when initializing. Error: {e}. "
                        f"Make sure to handle cases where canvas dimensions are too small."
                    )

def test_safe_coords_unpacking(implementation):
    """Test that the implementation safely unpacks coords"""
    impl_name, module = implementation

    # Check for safe unpacking of canvas coords in source code
    module_source = get_module_source_safely(module)

    # Look for patterns of coords unpacking - more expansive patterns
    unsafe_unpacking_patterns = [
        r'x\d*\s*,\s*y\d*\s*,\s*x\d*\s*,\s*y\d*\s*=\s*\w+\.coords',
        r'x\d*\s*,\s*y\d*\s*,\s*x\d*\s*,\s*y\d*\s*=\s*coords',
        r'\w+\s*=\s*\w+\.coords\([^)]*\)[^;]*;\s*[^=]*=\s*\w+\[0\]',  # Indexing into coords without checks
        r'\w+\s*,\s*\w+\s*,\s*\w+\s*,\s*\w+\s*=',  # Any 4-tuple unpacking that might be coords
    ]

    # Look for safety checks
    safety_check_patterns = [
        r'if\s+len\s*\(\s*coords\s*\)\s*[<=>]',  # Check coords length
        r'if\s+not\s+coords:',                   # Check if coords is empty
        r'if\s+coords\s*:',                      # Check if coords exists
        r'try\s*:[^}]*coords[^}]*except',        # Try/except around coords usage
        r'coords\s*=\s*[^;]*;\s*if\s+len\s*\(\s*coords\s*\)', # Get coords then check length
        r'len\s*\(\s*\w+\.coords\([^)]*\)\s*\)\s*[<=>]', # Direct length check on coords call
    ]

    # Check for unsafe patterns
    has_unsafe_unpacking = False
    for pattern in unsafe_unpacking_patterns:
        match = re.search(pattern, module_source, re.IGNORECASE)
        if match:
            has_unsafe_unpacking = True
            unsafe_code = match.group(0)
            break

    # Check for safety checks
    has_safety_check = any(re.search(pattern, module_source, re.IGNORECASE) for pattern in safety_check_patterns)

    # Only raise issue if unsafe unpacking is found without safety checks
    if has_unsafe_unpacking and not has_safety_check:
        assert False, (
            f"{impl_name} contains unsafe unpacking of canvas.coords() without proper validation: '{unsafe_code}'. "
            f"This can lead to 'not enough values to unpack' errors if the item has been deleted "
            f"or if coords returns an empty list. Add a check for the length of coords before unpacking "
            f"or use try/except to handle this case."
        )

    # Dynamic testing with mocks
    with patch('tkinter.Tk'), patch('tkinter.Canvas') as mock_canvas:
        # Set up canvas mock to return empty coords
        mock_canvas.return_value.create_rectangle.return_value = 1
        mock_canvas.return_value.coords.return_value = []  # Empty coords to trigger the error
        mock_canvas.return_value.winfo_width.return_value = 600
        mock_canvas.return_value.winfo_height.return_value = 400

        # First try directly running the module code when possible
        if hasattr(module, 'main'):
            try:
                # Patch random to avoid actual randomness
                with patch('random.randint', return_value=10), \
                     patch('random.choice', return_value=1), \
                     patch('random.uniform', return_value=1):
                    module.main()
            except ValueError as e:
                if "not enough values to unpack" in str(e):
                    assert False, (
                        f"{impl_name} has a 'not enough values to unpack' error when using canvas.coords(). "
                        f"Error: {e}. Add validation before unpacking canvas coordinates."
                    )
            except Exception:
                # Other exceptions aren't relevant for this test
                pass

        # Test any class that might use coords
        for name, obj in inspect.getmembers(module):
            if inspect.isclass(obj):
                try:
                    class_source = inspect.getsource(obj)
                    # If this class uses canvas coords, test it
                    if "coords" in class_source:
                        # Try to create instance
                        instance = None
                        try:
                            # Check constructor signature to see how to instantiate
                            sig = inspect.signature(obj.__init__)
                            params = list(sig.parameters.keys())

                            # Create appropriate arguments based on parameter names
                            args = []
                            for param in params[1:]:  # Skip 'self'
                                if 'canvas' in param:
                                    args.append(mock_canvas.return_value)
                                elif 'root' in param or 'master' in param:
                                    args.append(MagicMock())
                                elif param in ('x', 'x1', 'left'):
                                    args.append(100)
                                elif param in ('y', 'y1', 'top'):
                                    args.append(100)
                                elif param in ('width', 'size'):
                                    args.append(50)
                                elif param in ('height'):
                                    args.append(50)
                                elif param in ('dx', 'speed_x'):
                                    args.append(1)
                                elif param in ('dy', 'speed_y'):
                                    args.append(1)
                                else:
                                    args.append(MagicMock())

                            # Create instance
                            instance = obj(*args)
                        except Exception:
                            # Try with simpler args if that failed
                            try:
                                if 'canvas' in class_source.lower():
                                    instance = obj(mock_canvas.return_value)
                                else:
                                    instance = obj()
                            except Exception:
                                continue

                        # If we got an instance, try to call methods that might use coords
                        if instance:
                            for method_name in ['move', 'update', 'animate', 'check_collision', 'move_square']:
                                if hasattr(instance, method_name) and callable(getattr(instance, method_name)):
                                    try:
                                        method = getattr(instance, method_name)
                                        method()
                                    except ValueError as e:
                                        if "not enough values" in str(e) or "too many values" in str(e):
                                            assert False, (
                                                f"{impl_name} has a '{str(e)}' error when using "
                                                f"canvas.coords() in {obj.__name__}.{method_name}. "
                                                f"Add validation before unpacking coordinates."
                                            )
                except Exception as e:
                    # Only care about ValueError related to unpacking
                    if isinstance(e, ValueError) and ("not enough values" in str(e) or "too many values" in str(e)):
                        assert False, (
                            f"{impl_name} has a '{str(e)}' error when testing coords handling. "
                            f"Add validation before unpacking coordinates."
                        )

import pytest
import os
import sys
import json
from typing import Dict, List, Optional, Any

# Import from local test_utils.py in the same directory
from test_utils import TestUtils, TestResultsManager

# Load all implementations in the current sandbox
implementations = TestUtils.load_all_implementations()
test_results = TestResultsManager()

@pytest.fixture(scope="session")
def sandbox_dir():
    """Fixture to provide the sandbox directory path."""
    return os.path.dirname(os.path.abspath(__file__))

@pytest.fixture(scope="session")
def sandbox_name():
    """Fixture to provide the sandbox name."""
    return os.path.basename(os.path.dirname(os.path.abspath(__file__)))

@pytest.fixture(scope="session")
def all_implementations():
    """Fixture to provide all implementations as a dictionary."""
    return implementations

@pytest.fixture(params=list(implementations.items()))
def implementation(request):
    """Fixture to provide each implementation to tests one at a time."""
    return request.param

@pytest.fixture(scope="session")
def results_manager():
    """Fixture to provide access to the test results manager."""
    return test_results

# Hook for collecting test results
@pytest.hookimpl(tryfirst=True, hookwrapper=True)
def pytest_runtest_makereport(item, call):
    """Pytest hook to collect test results."""
    # Execute all other hooks to obtain the report object
    outcome = yield
    rep = outcome.get_result()

    # We're only interested in the call outcome
    if rep.when == "call":
        if hasattr(item, "callspec") and "implementation" in item.callspec.params:
            # Get implementation name and module
            impl_name, _ = item.callspec.params["implementation"]

            # Get test name
            test_name = item.nodeid.split("::")[-1]

            # Record result
            if rep.passed:
                test_results.record_result(impl_name, test_name, True)
            elif rep.failed:
                error_msg = str(rep.longrepr) if rep.longrepr else "Test failed"
                test_results.record_result(impl_name, test_name, False, error_msg)
            elif rep.skipped:
                skip_reason = rep.longrepr[2] if rep.longrepr else "Test skipped"
                test_results.record_skip(impl_name, test_name, skip_reason)

# Hook to save results at the end of testing
@pytest.hookimpl(trylast=True)
def pytest_sessionfinish(session, exitstatus):
    """Save test results at the end of the test session."""
    test_results.save_results()

import os
import sys
import glob
import re
import importlib.util
import traceback
import types
from typing import Dict, List, Optional, Any, Tuple

class TestUtils:
    @staticmethod
    def discover_implementation_files(directory: str = None) -> List[str]:
        """Find all implementation files in the current sandbox directory."""
        if directory is None:
            directory = os.path.dirname(os.path.abspath(__file__))

        patterns = [
            r'modified_code\d+\.py',
            r'new_code\d+\.py',
            # r'original_code\.py',
            r'implementation\d*\.py'
        ]

        pattern = re.compile('|'.join(f'({p})' for p in patterns))
        implementations = []

        for file_path in glob.glob(os.path.join(directory, '*.py')):
            if pattern.search(os.path.basename(file_path)):
                implementations.append(file_path)

        # Sort files numerically
        def sort_key(path):
            filename = os.path.basename(path)
            match = re.search(r'(\d+)', filename)
            return int(match.group(1)) if match else 0

        return sorted(implementations, key=sort_key)

    @staticmethod
    def create_mock_module(file_path: str, module_name: str, error_info: str) -> types.ModuleType:
        """Create a mock module that contains error information but can still be tested."""
        # Create a new module object
        mock_module = types.ModuleType(module_name)

        # Add basic attributes
        mock_module.__file__ = file_path
        mock_module.__name__ = module_name
        mock_module.__display_name__ = module_name
        mock_module.__error__ = error_info

        # Add a dummy function that can be detected by test functions
        def dummy_function(*args, **kwargs):
            return f"Error in module: {error_info}"

        setattr(mock_module, "implementation_error", dummy_function)

        return mock_module

    @staticmethod
    def load_module(file_path: str, module_name: Optional[str] = None) -> Any:
        """
        Safely load a module from a file path with proper error handling.
        If the module has errors, return a mock module that can still be tested.
        """
        if module_name is None:
            module_name = os.path.basename(file_path).replace('.py', '')

        # Create a unique module name to avoid conflicts
        sandbox_id = os.path.basename(os.path.dirname(file_path))
        unique_module_name = f"{sandbox_id}_{module_name}"

        try:
            # First, try to read the file to check for syntax errors
            with open(file_path, 'r') as f:
                source_code = f.read()

            # Check for syntax errors by compiling the code
            try:
                compiled = compile(source_code, file_path, 'exec')
            except SyntaxError as e:
                error_msg = f"Syntax error: {str(e)}"
                print(f"Syntax error in {file_path}: {e}")
                print(f"  Line {e.lineno}, column {e.offset}: {e.text}")
                return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

            # Create the module spec
            spec = importlib.util.spec_from_file_location(unique_module_name, file_path)
            if spec is None or spec.loader is None:
                error_msg = f"Could not create spec for {file_path}"
                print(f"Error: {error_msg}")
                return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

            # Create the module object
            module = importlib.util.module_from_spec(spec)
            sys.modules[unique_module_name] = module

            # Special handling for execution errors
            try:
                # Execute the module code in a safe way
                spec.loader.exec_module(module)
                # Store the original name for reference
                module.__display_name__ = module_name
                return module
            except Exception as e:
                error_msg = f"Runtime error: {str(e)}"
                traceback_str = traceback.format_exc()
                print(f"Error executing module {file_path}: {e}")
                print(traceback_str)

                # Create a partial module that contains what we loaded before the error
                mock_module = TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

                # Copy any attributes that might have been defined before the error
                for attr_name in dir(module):
                    if not attr_name.startswith('__'):
                        try:
                            setattr(mock_module, attr_name, getattr(module, attr_name))
                        except Exception:
                            pass  # Skip attributes that can't be copied

                return mock_module

        except FileNotFoundError as e:
            error_msg = f"File not found: {str(e)}"
            print(f"Error: {error_msg}")
            return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)
        except Exception as e:
            error_msg = f"Unexpected error: {str(e)}"
            print(f"Error loading module {file_path}: {e}")
            return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

    @classmethod
    def load_all_implementations(cls, directory: str = None) -> Dict[str, Any]:
        """Load all implementation files in the directory, including those with errors."""
        if directory is None:
            directory = os.path.dirname(os.path.abspath(__file__))

        implementations = {}

        implementation_files = cls.discover_implementation_files(directory)
        if not implementation_files:
            print("WARNING: No implementation files found. Check your file naming patterns.")

        for file_path in implementation_files:
            module_name = os.path.basename(file_path).replace('.py', '')
            module = cls.load_module(file_path, module_name)

            # Always add the module, even if it has errors
            implementations[module_name] = module

            if hasattr(module, '__error__'):
                print(f"Loaded with errors: {module_name} - {module.__error__}")
            else:
                print(f"Successfully loaded: {module_name}")

        return implementations

class TestResultsManager:
    def __init__(self):
        self.results = {}
        self.sandbox_name = os.path.basename(os.path.dirname(os.path.abspath(__file__)))

    def record_result(self, impl_name: str, test_name: str, passed: bool,
                     error_msg: Optional[str] = None) -> None:
        """Record a test result for an implementation."""
        if impl_name not in self.results:
            self.results[impl_name] = {"passed": 0, "failed": 0, "skipped": 0, "errors": []}

        if passed:
            self.results[impl_name]["passed"] += 1
        else:
            self.results[impl_name]["failed"] += 1
            if error_msg:
                self.results[impl_name]["errors"].append({
                    "test": test_name,
                    "error": error_msg
                })

    def record_skip(self, impl_name: str, test_name: str,
                   reason: Optional[str] = None) -> None:
        """Record a skipped test for an implementation."""
        if impl_name not in self.results:
            self.results[impl_name] = {"passed": 0, "failed": 0, "skipped": 0, "errors": []}

        self.results[impl_name]["skipped"] += 1
        if reason:
            self.results[impl_name]["errors"].append({
                "test": test_name,
                "error": f"SKIPPED: {reason}"
            })

    def get_winner(self) -> Tuple[Optional[int], Dict]:
        """Determine the winner based on test results."""
        winner = None
        max_passed = -1

        for impl_name, results in self.results.items():
            if impl_name == "original_code":
                continue  # Skip original code when determining winner

            if results["passed"] > max_passed:
                max_passed = results["passed"]
                winner = impl_name
            # Break ties by looking at failure count
            elif results["passed"] == max_passed and winner is not None:
                if results["failed"] < self.results[winner]["failed"]:
                    winner = impl_name

        # Convert winner to numeric index if possible
        winner_index = -1
        if winner and re.match(r'modified_code\d+', winner):
            try:
                winner_index = int(re.search(r'(\d+)', winner).group(1))
            except (AttributeError, ValueError):
                pass

        return winner_index, self.results

    def save_results(self, filename: str = "test_results.json") -> None:
        """Save test results to a JSON file."""
        import json

        winner_index, results = self.get_winner()

        # Check if all tests were skipped
        all_skipped = all(
            stats["skipped"] == stats["passed"] + stats["failed"] + stats["skipped"]
            for impl_name, stats in results.items()
            if impl_name != "original_code"
        )

        output = {
            "winner": winner_index,
            "all_skipped": all_skipped,
            "results": {
                name: {
                    "passed": stats["passed"],
                    "failed": stats["failed"],
                    "skipped": stats["skipped"],
                    "total": stats["passed"] + stats["failed"] + stats["skipped"]
                }
                for name, stats in results.items()
                if not name.startswith("_")  # Skip internal items
            }
        }

        with open(filename, "w") as f:
            json.dump(output, f, indent=2)

        print(f"Test results saved to {filename}")

        return output


import random

def roll_dice(num_rolls):
    """Rolls a six-sided die a specified number of times and returns the frequencies of each outcome.

    Args:
        num_rolls: The number of times to roll the die.

    Returns:
        A dictionary where keys are the numbers 1-6 (representing the die faces) and values are their frequencies.  Returns an empty dictionary if num_rolls is not a positive integer.

    Raises:
        TypeError: if num_rolls is not an integer.
        ValueError: if num_rolls is not positive.

    """
    if not isinstance(num_rolls, int):
        raise TypeError("Number of rolls must be an integer.")
    if num_rolls <= 0:
        raise ValueError("Number of rolls must be positive.")

    frequencies = {i: 0 for i in range(1, 7)}  # Initialize frequencies for each face (1-6)
    for _ in range(num_rolls):
        roll = random.randint(1, 6)  # Simulate a die roll
        frequencies[roll] += 1
    return frequencies

if __name__ == "__main__":
    num_rolls = 10000
    try:
        results = roll_dice(num_rolls)
        print(f"Frequencies of die rolls after {num_rolls} rolls:")
        for face, frequency in results.items():
            print(f"Face {face}: {frequency} times")

    except (TypeError, ValueError) as e:
        print(f"Error: {e}")

Instruction: give the result as percentage

import pytest
import random
from unittest.mock import patch, mock_open
import inspect
import re
import types
import builtins

def test_roll_dice_returns_percentages(implementation):
    """Test that roll_dice now returns percentages instead of frequencies."""
    impl_name, module = implementation

    # Mock random.randint to control dice roll outcomes
    with patch('random.randint', side_effect=[1, 2, 3, 4, 5, 6]):
        result = module.roll_dice(6)

        # Check if values are percentages (should sum to 100%)
        total_percentage = sum(result.values())
        assert abs(total_percentage - 100.0) < 0.01, f"Percentages should sum to 100%, got {total_percentage}"

        # Each value should be a percentage (here 16.67% for equal distribution)
        for face, percentage in result.items():
            assert abs(percentage - 16.67) < 0.1, f"Expected ~16.67% for each face, got {percentage}% for face {face}"

def test_roll_dice_percentage_calculation(implementation):
    """Test that percentages are calculated correctly."""
    impl_name, module = implementation

    # Mock 10 rolls with known outcomes: 1 appears 5 times, 2 appears 3 times, rest appear once or none
    mock_rolls = [1, 1, 1, 1, 1, 2, 2, 2, 3, 4]

    with patch('random.randint', side_effect=mock_rolls):
        result = module.roll_dice(10)

        # Check specific percentages
        assert abs(result[1] - 50.0) < 0.01, f"Expected 50% for face 1, got {result[1]}%"
        assert abs(result[2] - 30.0) < 0.01, f"Expected 30% for face 2, got {result[2]}%"
        assert abs(result[3] - 10.0) < 0.01, f"Expected 10% for face 3, got {result[3]}%"
        assert abs(result[4] - 10.0) < 0.01, f"Expected 10% for face 4, got {result[4]}%"
        assert abs(result[5] - 0.0) < 0.01, f"Expected 0% for face 5, got {result[5]}%"
        assert abs(result[6] - 0.0) < 0.01, f"Expected 0% for face 6, got {result[6]}%"

def test_roll_dice_error_handling(implementation):
    """Test that error handling is preserved."""
    impl_name, module = implementation

    # Test with non-integer input
    with pytest.raises(TypeError):
        module.roll_dice("10")

    # Test with non-positive integer
    with pytest.raises(ValueError):
        module.roll_dice(0)

    with pytest.raises(ValueError):
        module.roll_dice(-5)

def test_large_number_of_rolls(implementation):
    """Test that with a large number of rolls, percentages converge to expected values."""
    impl_name, module = implementation

    # With many rolls and uniform distribution, each face should be close to 16.67%
    result = module.roll_dice(10000)

    # Each face should be approximately 16.67% with some tolerance
    for face in range(1, 7):
        assert 15.0 <= result[face] <= 18.5, f"Face {face} percentage ({result[face]}%) too far from expected 16.67%"

def test_small_number_of_rolls(implementation):
    """Test with a very small number of rolls."""
    impl_name, module = implementation

    # With only one roll, the rolled face should be 100% and others 0%
    with patch('random.randint', return_value=3):  # Always roll a 3
        result = module.roll_dice(1)

        assert result[3] == 100.0, f"With one roll of 3, face 3 should be 100%, got {result[3]}%"
        for face in [1, 2, 4, 5, 6]:
            assert result[face] == 0.0, f"With one roll of 3, face {face} should be 0%, got {result[face]}%"

import pytest
import os
import sys
import json
from typing import Dict, List, Optional, Any

# Import from local test_utils.py in the same directory
from test_utils import TestUtils, TestResultsManager

# Load all implementations in the current sandbox
implementations = TestUtils.load_all_implementations()
test_results = TestResultsManager()

@pytest.fixture(scope="session")
def sandbox_dir():
    """Fixture to provide the sandbox directory path."""
    return os.path.dirname(os.path.abspath(__file__))

@pytest.fixture(scope="session")
def sandbox_name():
    """Fixture to provide the sandbox name."""
    return os.path.basename(os.path.dirname(os.path.abspath(__file__)))

@pytest.fixture(scope="session")
def all_implementations():
    """Fixture to provide all implementations as a dictionary."""
    return implementations

@pytest.fixture(params=list(implementations.items()))
def implementation(request):
    """Fixture to provide each implementation to tests one at a time."""
    return request.param

@pytest.fixture(scope="session")
def results_manager():
    """Fixture to provide access to the test results manager."""
    return test_results

# Hook for collecting test results
@pytest.hookimpl(tryfirst=True, hookwrapper=True)
def pytest_runtest_makereport(item, call):
    """Pytest hook to collect test results."""
    # Execute all other hooks to obtain the report object
    outcome = yield
    rep = outcome.get_result()

    # We're only interested in the call outcome
    if rep.when == "call":
        if hasattr(item, "callspec") and "implementation" in item.callspec.params:
            # Get implementation name and module
            impl_name, _ = item.callspec.params["implementation"]

            # Get test name
            test_name = item.nodeid.split("::")[-1]

            # Record result
            if rep.passed:
                test_results.record_result(impl_name, test_name, True)
            elif rep.failed:
                error_msg = str(rep.longrepr) if rep.longrepr else "Test failed"
                test_results.record_result(impl_name, test_name, False, error_msg)
            elif rep.skipped:
                skip_reason = rep.longrepr[2] if rep.longrepr else "Test skipped"
                test_results.record_skip(impl_name, test_name, skip_reason)

# Hook to save results at the end of testing
@pytest.hookimpl(trylast=True)
def pytest_sessionfinish(session, exitstatus):
    """Save test results at the end of the test session."""
    test_results.save_results()

import os
import sys
import glob
import re
import importlib.util
import traceback
import types
from typing import Dict, List, Optional, Any, Tuple

class TestUtils:
    @staticmethod
    def discover_implementation_files(directory: str = None) -> List[str]:
        """Find all implementation files in the current sandbox directory."""
        if directory is None:
            directory = os.path.dirname(os.path.abspath(__file__))

        patterns = [
            r'modified_code\d+\.py',
            r'new_code\d+\.py',
            r'original_code\.py',
            r'implementation\d*\.py'
        ]

        pattern = re.compile('|'.join(f'({p})' for p in patterns))
        implementations = []

        for file_path in glob.glob(os.path.join(directory, '*.py')):
            if pattern.search(os.path.basename(file_path)):
                implementations.append(file_path)

        # Sort files numerically
        def sort_key(path):
            filename = os.path.basename(path)
            match = re.search(r'(\d+)', filename)
            return int(match.group(1)) if match else 0

        return sorted(implementations, key=sort_key)

    @staticmethod
    def create_mock_module(file_path: str, module_name: str, error_info: str) -> types.ModuleType:
        """Create a mock module that contains error information but can still be tested."""
        # Create a new module object
        mock_module = types.ModuleType(module_name)

        # Add basic attributes
        mock_module.__file__ = file_path
        mock_module.__name__ = module_name
        mock_module.__display_name__ = module_name
        mock_module.__error__ = error_info

        # Add a dummy function that can be detected by test functions
        def dummy_function(*args, **kwargs):
            return f"Error in module: {error_info}"

        setattr(mock_module, "implementation_error", dummy_function)

        return mock_module

    @staticmethod
    def load_module(file_path: str, module_name: Optional[str] = None) -> Any:
        """
        Safely load a module from a file path with proper error handling.
        If the module has errors, return a mock module that can still be tested.
        """
        if module_name is None:
            module_name = os.path.basename(file_path).replace('.py', '')

        # Create a unique module name to avoid conflicts
        sandbox_id = os.path.basename(os.path.dirname(file_path))
        unique_module_name = f"{sandbox_id}_{module_name}"

        try:
            # First, try to read the file to check for syntax errors
            with open(file_path, 'r') as f:
                source_code = f.read()

            # Check for syntax errors by compiling the code
            try:
                compiled = compile(source_code, file_path, 'exec')
            except SyntaxError as e:
                error_msg = f"Syntax error: {str(e)}"
                print(f"Syntax error in {file_path}: {e}")
                print(f"  Line {e.lineno}, column {e.offset}: {e.text}")
                return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

            # Create the module spec
            spec = importlib.util.spec_from_file_location(unique_module_name, file_path)
            if spec is None or spec.loader is None:
                error_msg = f"Could not create spec for {file_path}"
                print(f"Error: {error_msg}")
                return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

            # Create the module object
            module = importlib.util.module_from_spec(spec)
            sys.modules[unique_module_name] = module

            # Special handling for execution errors
            try:
                # Execute the module code in a safe way
                spec.loader.exec_module(module)
                # Store the original name for reference
                module.__display_name__ = module_name
                return module
            except Exception as e:
                error_msg = f"Runtime error: {str(e)}"
                traceback_str = traceback.format_exc()
                print(f"Error executing module {file_path}: {e}")
                print(traceback_str)

                # Create a partial module that contains what we loaded before the error
                mock_module = TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

                # Copy any attributes that might have been defined before the error
                for attr_name in dir(module):
                    if not attr_name.startswith('__'):
                        try:
                            setattr(mock_module, attr_name, getattr(module, attr_name))
                        except Exception:
                            pass  # Skip attributes that can't be copied

                return mock_module

        except FileNotFoundError as e:
            error_msg = f"File not found: {str(e)}"
            print(f"Error: {error_msg}")
            return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)
        except Exception as e:
            error_msg = f"Unexpected error: {str(e)}"
            print(f"Error loading module {file_path}: {e}")
            return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

    @classmethod
    def load_all_implementations(cls, directory: str = None) -> Dict[str, Any]:
        """Load all implementation files in the directory, including those with errors."""
        if directory is None:
            directory = os.path.dirname(os.path.abspath(__file__))

        implementations = {}

        implementation_files = cls.discover_implementation_files(directory)
        if not implementation_files:
            print("WARNING: No implementation files found. Check your file naming patterns.")

        for file_path in implementation_files:
            module_name = os.path.basename(file_path).replace('.py', '')
            module = cls.load_module(file_path, module_name)

            # Always add the module, even if it has errors
            implementations[module_name] = module

            if hasattr(module, '__error__'):
                print(f"Loaded with errors: {module_name} - {module.__error__}")
            else:
                print(f"Successfully loaded: {module_name}")

        return implementations

class TestResultsManager:
    def __init__(self):
        self.results = {}
        self.sandbox_name = os.path.basename(os.path.dirname(os.path.abspath(__file__)))

    def record_result(self, impl_name: str, test_name: str, passed: bool,
                     error_msg: Optional[str] = None) -> None:
        """Record a test result for an implementation."""
        if impl_name not in self.results:
            self.results[impl_name] = {"passed": 0, "failed": 0, "skipped": 0, "errors": []}

        if passed:
            self.results[impl_name]["passed"] += 1
        else:
            self.results[impl_name]["failed"] += 1
            if error_msg:
                self.results[impl_name]["errors"].append({
                    "test": test_name,
                    "error": error_msg
                })

    def record_skip(self, impl_name: str, test_name: str,
                   reason: Optional[str] = None) -> None:
        """Record a skipped test for an implementation."""
        if impl_name not in self.results:
            self.results[impl_name] = {"passed": 0, "failed": 0, "skipped": 0, "errors": []}

        self.results[impl_name]["skipped"] += 1
        if reason:
            self.results[impl_name]["errors"].append({
                "test": test_name,
                "error": f"SKIPPED: {reason}"
            })

    def get_winner(self) -> Tuple[Optional[int], Dict]:
        """Determine the winner based on test results."""
        winner = None
        max_passed = -1

        for impl_name, results in self.results.items():
            if impl_name == "original_code":
                continue  # Skip original code when determining winner

            if results["passed"] > max_passed:
                max_passed = results["passed"]
                winner = impl_name
            # Break ties by looking at failure count
            elif results["passed"] == max_passed and winner is not None:
                if results["failed"] < self.results[winner]["failed"]:
                    winner = impl_name

        # Convert winner to numeric index if possible
        winner_index = -1
        if winner and re.match(r'modified_code\d+', winner):
            try:
                winner_index = int(re.search(r'(\d+)', winner).group(1))
            except (AttributeError, ValueError):
                pass

        return winner_index, self.results

    def save_results(self, filename: str = "test_results.json") -> None:
        """Save test results to a JSON file."""
        import json

        winner_index, results = self.get_winner()

        # Check if all tests were skipped
        all_skipped = all(
            stats["skipped"] == stats["passed"] + stats["failed"] + stats["skipped"]
            for impl_name, stats in results.items()
            if impl_name != "original_code"
        )

        output = {
            "winner": winner_index,
            "all_skipped": all_skipped,
            "results": {
                name: {
                    "passed": stats["passed"],
                    "failed": stats["failed"],
                    "skipped": stats["skipped"],
                    "total": stats["passed"] + stats["failed"] + stats["skipped"]
                }
                for name, stats in results.items()
                if not name.startswith("_")  # Skip internal items
            }
        }

        with open(filename, "w") as f:
            json.dump(output, f, indent=2)

        print(f"Test results saved to {filename}")

        return output


import numpy as np
from pathlib import Path
from typing import List

INPUT_FILE_PATH = Path('./input.txt')
EXAMPLE_FILE_PATH = Path('./example_in.txt')

def parse_input_file(file_path: Path) -> List[str]:
    """Read and parse input file into list of strings."""
    return file_path.read_text().splitlines()

def calculate_distances(array1: np.ndarray, array2: np.ndarray) -> int:
    """Calculate sum of absolute differences between sorted arrays."""
    # Sort arrays for optimal matching
    sorted1 = np.sort(array1)
    sorted2 = np.sort(array2)

    # Calculate absolute differences and sum
    return np.sum(np.abs(sorted1 - sorted2))

def main():
    # Use example file for testing, comment out for real input
    file_path = EXAMPLE_FILE_PATH
    #file_path = INPUT_FILE_PATH

    # Parse input and convert to numpy arrays
    lines = parse_input_file(file_path)
    cols = np.array([line.split("   ") for line in lines], dtype=int).T

    # Calculate and print result
    result = calculate_distances(cols[0], cols[1])
    print(f"Sum of distances: {result}")
if __name__ == "__main__":
    main()

Instruction: remove comments

import pytest
import ast
import inspect
import numpy as np
from pathlib import Path
import tempfile
import importlib.util
import io
import sys
from typing import List, Tuple, Any

def test_code_has_no_comments(implementation):
    """Test that the implementation has removed comments from the code."""
    impl_name, module = implementation

    # Get the source code
    source_code = inspect.getsource(module)

    # Parse the source code
    tree = ast.parse(source_code)

    # Check for comments in the AST
    comment_count = 0
    for node in ast.walk(tree):
        # Check if there are any comment nodes
        if (
            isinstance(node, ast.Expr)
            and isinstance(node.value, ast.Constant)
            and isinstance(node.value.value, str)
        ):
            if node.value.value.strip().startswith("#"):
                comment_count += 1

    # Assert that there are no comments in the code
    assert comment_count == 0, f"Implementation {impl_name} still contains comments"

def test_docstrings_removed(implementation):
    """Test that docstrings have been removed from functions."""
    impl_name, module = implementation

    # Check for docstrings in module functions
    for name, obj in inspect.getmembers(module, inspect.isfunction):
        assert (
            obj.__doc__ is None
        ), f"Function {name} in {impl_name} still has a docstring"

def test_functionality_preserved(implementation):
    """Test that the core functionality works correctly."""
    impl_name, module = implementation

    # Create temporary test input files
    with tempfile.TemporaryDirectory() as temp_dir:
        temp_path = Path(temp_dir)

        # Create example input file
        example_path = temp_path / "example_in.txt"
        with open(example_path, "w") as f:
            f.write("1   4\n2   3\n5   7\n")

        # Patch the paths in the module
        original_example_path = module.EXAMPLE_FILE_PATH
        module.EXAMPLE_FILE_PATH = example_path

        try:
            # Use monkeypatching to capture stdout
            captured_output = io.StringIO()
            original_stdout = sys.stdout
            sys.stdout = captured_output

            # Run the main function
            module.main()

            # Get the output
            output = captured_output.getvalue()

            # Verify the expected result (1 + 2 + 5 sorted vs 4 + 3 + 7 sorted = |1-3| + |2-4| + |5-7| = 6)
            assert (
                "Sum of distances: 6" in output
            ), f"Implementation {impl_name} produced incorrect output: {output}"

        finally:
            # Restore stdout and module paths
            sys.stdout = original_stdout
            module.EXAMPLE_FILE_PATH = original_example_path

def test_calculate_distances_function(implementation):
    """Test that the calculate_distances function works correctly."""
    impl_name, module = implementation

    # Test cases
    test_cases = [
        (np.array([1, 2, 3]), np.array([1, 2, 3]), 0),
        (np.array([1, 2, 3]), np.array([4, 5, 6]), 9),
        (
            np.array([1, 5, 2]),
            np.array([7, 3, 4]),
            6,
        ),  # Tests sorting: [1,2,5] vs [3,4,7]
        (np.array([]), np.array([]), 0),
    ]

    for array1, array2, expected in test_cases:
        result = module.calculate_distances(array1, array2)
        assert (
            result == expected
        ), f"Implementation {impl_name} failed for arrays {array1} and {array2}"

def test_parse_input_file(implementation):
    """Test that the parse_input_file function works correctly."""
    impl_name, module = implementation

    with tempfile.NamedTemporaryFile(mode="w+") as temp_file:
        # Write test data
        temp_file.write("1   4\n2   3\n5   7\n")
        temp_file.flush()

        # Test the function
        result = module.parse_input_file(Path(temp_file.name))
        assert result == [
            "1   4",
            "2   3",
            "5   7",
        ], f"Implementation {impl_name} failed to parse input file correctly"

def test_main_uses_example_file(implementation):
    """Test that main uses the example file path."""
    impl_name, module = implementation

    # Get the source code of the main function
    main_source = inspect.getsource(module.main)

    # Parse the source code
    tree = ast.parse(main_source)

    # Check for assignment to file_path
    example_file_used = False
    for node in ast.walk(tree):
        if isinstance(node, ast.Assign):
            for target in node.targets:
                if isinstance(target, ast.Name) and target.id == "file_path":
                    if (
                        isinstance(node.value, ast.Name)
                        and node.value.id == "EXAMPLE_FILE_PATH"
                    ):
                        example_file_used = True

    assert (
        example_file_used
    ), f"Implementation {impl_name} doesn't use EXAMPLE_FILE_PATH"

def test_code_structure_preserved(implementation):
    """Test that the basic code structure is preserved."""
    impl_name, module = implementation

    # Check that required functions exist
    assert hasattr(
        module, "parse_input_file"
    ), f"Implementation {impl_name} missing parse_input_file function"
    assert hasattr(
        module, "calculate_distances"
    ), f"Implementation {impl_name} missing calculate_distances function"
    assert hasattr(module, "main"), f"Implementation {impl_name} missing main function"

    # Check that constants are defined
    assert hasattr(
        module, "INPUT_FILE_PATH"
    ), f"Implementation {impl_name} missing INPUT_FILE_PATH constant"
    assert hasattr(
        module, "EXAMPLE_FILE_PATH"
    ), f"Implementation {impl_name} missing EXAMPLE_FILE_PATH constant"

import pytest
import os
import sys
import json
from typing import Dict, List, Optional, Any

# Import from local test_utils.py in the same directory
from test_utils import TestUtils, TestResultsManager

# Load all implementations in the current sandbox
implementations = TestUtils.load_all_implementations()
test_results = TestResultsManager()

@pytest.fixture(scope="session")
def sandbox_dir():
    """Fixture to provide the sandbox directory path."""
    return os.path.dirname(os.path.abspath(__file__))

@pytest.fixture(scope="session")
def sandbox_name():
    """Fixture to provide the sandbox name."""
    return os.path.basename(os.path.dirname(os.path.abspath(__file__)))

@pytest.fixture(scope="session")
def all_implementations():
    """Fixture to provide all implementations as a dictionary."""
    return implementations

@pytest.fixture(params=list(implementations.items()))
def implementation(request):
    """Fixture to provide each implementation to tests one at a time."""
    return request.param

@pytest.fixture(scope="session")
def results_manager():
    """Fixture to provide access to the test results manager."""
    return test_results

# Hook for collecting test results
@pytest.hookimpl(tryfirst=True, hookwrapper=True)
def pytest_runtest_makereport(item, call):
    """Pytest hook to collect test results."""
    # Execute all other hooks to obtain the report object
    outcome = yield
    rep = outcome.get_result()

    # We're only interested in the call outcome
    if rep.when == "call":
        if hasattr(item, "callspec") and "implementation" in item.callspec.params:
            # Get implementation name and module
            impl_name, _ = item.callspec.params["implementation"]

            # Get test name
            test_name = item.nodeid.split("::")[-1]

            # Record result
            if rep.passed:
                test_results.record_result(impl_name, test_name, True)
            elif rep.failed:
                error_msg = str(rep.longrepr) if rep.longrepr else "Test failed"
                test_results.record_result(impl_name, test_name, False, error_msg)
            elif rep.skipped:
                skip_reason = rep.longrepr[2] if rep.longrepr else "Test skipped"
                test_results.record_skip(impl_name, test_name, skip_reason)

# Hook to save results at the end of testing
@pytest.hookimpl(trylast=True)
def pytest_sessionfinish(session, exitstatus):
    """Save test results at the end of the test session."""
    test_results.save_results()

import os
import sys
import glob
import re
import importlib.util
import traceback
import types
from typing import Dict, List, Optional, Any, Tuple

class TestUtils:
    @staticmethod
    def discover_implementation_files(directory: str = None) -> List[str]:
        """Find all implementation files in the current sandbox directory."""
        if directory is None:
            directory = os.path.dirname(os.path.abspath(__file__))

        patterns = [
            r'modified_code\d+\.py',
            r'new_code\d+\.py',
            r'original_code\.py',
            r'implementation\d*\.py'
        ]

        pattern = re.compile('|'.join(f'({p})' for p in patterns))
        implementations = []

        for file_path in glob.glob(os.path.join(directory, '*.py')):
            if pattern.search(os.path.basename(file_path)):
                implementations.append(file_path)

        # Sort files numerically
        def sort_key(path):
            filename = os.path.basename(path)
            match = re.search(r'(\d+)', filename)
            return int(match.group(1)) if match else 0

        return sorted(implementations, key=sort_key)

    @staticmethod
    def create_mock_module(file_path: str, module_name: str, error_info: str) -> types.ModuleType:
        """Create a mock module that contains error information but can still be tested."""
        # Create a new module object
        mock_module = types.ModuleType(module_name)

        # Add basic attributes
        mock_module.__file__ = file_path
        mock_module.__name__ = module_name
        mock_module.__display_name__ = module_name
        mock_module.__error__ = error_info

        # Add a dummy function that can be detected by test functions
        def dummy_function(*args, **kwargs):
            return f"Error in module: {error_info}"

        setattr(mock_module, "implementation_error", dummy_function)

        return mock_module

    @staticmethod
    def load_module(file_path: str, module_name: Optional[str] = None) -> Any:
        """
        Safely load a module from a file path with proper error handling.
        If the module has errors, return a mock module that can still be tested.
        """
        if module_name is None:
            module_name = os.path.basename(file_path).replace('.py', '')

        # Create a unique module name to avoid conflicts
        sandbox_id = os.path.basename(os.path.dirname(file_path))
        unique_module_name = f"{sandbox_id}_{module_name}"

        try:
            # First, try to read the file to check for syntax errors
            with open(file_path, 'r') as f:
                source_code = f.read()

            # Check for syntax errors by compiling the code
            try:
                compiled = compile(source_code, file_path, 'exec')
            except SyntaxError as e:
                error_msg = f"Syntax error: {str(e)}"
                print(f"Syntax error in {file_path}: {e}")
                print(f"  Line {e.lineno}, column {e.offset}: {e.text}")
                return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

            # Create the module spec
            spec = importlib.util.spec_from_file_location(unique_module_name, file_path)
            if spec is None or spec.loader is None:
                error_msg = f"Could not create spec for {file_path}"
                print(f"Error: {error_msg}")
                return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

            # Create the module object
            module = importlib.util.module_from_spec(spec)
            sys.modules[unique_module_name] = module

            # Special handling for execution errors
            try:
                # Execute the module code in a safe way
                spec.loader.exec_module(module)
                # Store the original name for reference
                module.__display_name__ = module_name
                return module
            except Exception as e:
                error_msg = f"Runtime error: {str(e)}"
                traceback_str = traceback.format_exc()
                print(f"Error executing module {file_path}: {e}")
                print(traceback_str)

                # Create a partial module that contains what we loaded before the error
                mock_module = TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

                # Copy any attributes that might have been defined before the error
                for attr_name in dir(module):
                    if not attr_name.startswith('__'):
                        try:
                            setattr(mock_module, attr_name, getattr(module, attr_name))
                        except Exception:
                            pass  # Skip attributes that can't be copied

                return mock_module

        except FileNotFoundError as e:
            error_msg = f"File not found: {str(e)}"
            print(f"Error: {error_msg}")
            return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)
        except Exception as e:
            error_msg = f"Unexpected error: {str(e)}"
            print(f"Error loading module {file_path}: {e}")
            return TestUtils.create_mock_module(file_path, unique_module_name, error_msg)

    @classmethod
    def load_all_implementations(cls, directory: str = None) -> Dict[str, Any]:
        """Load all implementation files in the directory, including those with errors."""
        if directory is None:
            directory = os.path.dirname(os.path.abspath(__file__))

        implementations = {}

        implementation_files = cls.discover_implementation_files(directory)
        if not implementation_files:
            print("WARNING: No implementation files found. Check your file naming patterns.")

        for file_path in implementation_files:
            module_name = os.path.basename(file_path).replace('.py', '')
            module = cls.load_module(file_path, module_name)

            # Always add the module, even if it has errors
            implementations[module_name] = module

            if hasattr(module, '__error__'):
                print(f"Loaded with errors: {module_name} - {module.__error__}")
            else:
                print(f"Successfully loaded: {module_name}")

        return implementations

class TestResultsManager:
    def __init__(self):
        self.results = {}
        self.sandbox_name = os.path.basename(os.path.dirname(os.path.abspath(__file__)))

    def record_result(self, impl_name: str, test_name: str, passed: bool,
                     error_msg: Optional[str] = None) -> None:
        """Record a test result for an implementation."""
        if impl_name not in self.results:
            self.results[impl_name] = {"passed": 0, "failed": 0, "skipped": 0, "errors": []}

        if passed:
            self.results[impl_name]["passed"] += 1
        else:
            self.results[impl_name]["failed"] += 1
            if error_msg:
                self.results[impl_name]["errors"].append({
                    "test": test_name,
                    "error": error_msg
                })

    def record_skip(self, impl_name: str, test_name: str,
                   reason: Optional[str] = None) -> None:
        """Record a skipped test for an implementation."""
        if impl_name not in self.results:
            self.results[impl_name] = {"passed": 0, "failed": 0, "skipped": 0, "errors": []}

        self.results[impl_name]["skipped"] += 1
        if reason:
            self.results[impl_name]["errors"].append({
                "test": test_name,
                "error": f"SKIPPED: {reason}"
            })

    def get_winner(self) -> Tuple[Optional[int], Dict]:
        """Determine the winner based on test results."""
        winner = None
        max_passed = -1

        for impl_name, results in self.results.items():
            if impl_name == "original_code":
                continue  # Skip original code when determining winner

            if results["passed"] > max_passed:
                max_passed = results["passed"]
                winner = impl_name
            # Break ties by looking at failure count
            elif results["passed"] == max_passed and winner is not None:
                if results["failed"] < self.results[winner]["failed"]:
                    winner = impl_name

        # Convert winner to numeric index if possible
        winner_index = -1
        if winner and re.match(r'modified_code\d+', winner):
            try:
                winner_index = int(re.search(r'(\d+)', winner).group(1))
            except (AttributeError, ValueError):
                pass

        return winner_index, self.results

    def save_results(self, filename: str = "test_results.json") -> None:
        """Save test results to a JSON file."""
        import json

        winner_index, results = self.get_winner()

        # Check if all tests were skipped
        all_skipped = all(
            stats["skipped"] == stats["passed"] + stats["failed"] + stats["skipped"]
            for impl_name, stats in results.items()
            if impl_name != "original_code"
        )

        output = {
            "winner": winner_index,
            "all_skipped": all_skipped,
            "results": {
                name: {
                    "passed": stats["passed"],
                    "failed": stats["failed"],
                    "skipped": stats["skipped"],
                    "total": stats["passed"] + stats["failed"] + stats["skipped"]
                }
                for name, stats in results.items()
                if not name.startswith("_")  # Skip internal items
            }
        }

        with open(filename, "w") as f:
            json.dump(output, f, indent=2)

        print(f"Test results saved to {filename}")

        return output