def find_incremental_memory_leak():
    allocation_size = 1
    increment_size = 1024

    while True:
        try:
            # Attempt to allocate memory.
            memory_block = bytearray(allocation_size)

            # Simulate program logic to check for errors
            program_working_correctly = simulate_program_logic(memory_block)

            if not program_working_correctly:
                print(f"Program failed at allocation size: {allocation_size}")
                break

            # Increase allocation size for next iteration.
            allocation_size += increment_size

        except MemoryError:
            # A memory error indicates a potential leak
            print(f"MemoryError at allocation size: {allocation_size}")
            break

        except Exception as e:
            # Handles any other exception during execution.
            print(f"Exception at allocation size {allocation_size}: {e}")
            break

    return allocation_size

def simulate_program_logic(memory_block):
    # Simulates program operations and error checks.
    try:
        # Example operation: access an element in the bytearray.
        index = len(memory_block) // 2
        _ = memory_block[index]

        # Simulate a more complex operation that might cause an issue.
        for i in range(100):
            memory_block[i % len(memory_block)] = i % 256

        # Introduce a potential error (e.g., out-of-bounds access).
        # This is intentionally commented out; uncomment to simulate an error.
        # _ = memory_block[len(memory_block) + 1]

        return True  # Program is working correctly
    except IndexError:
        # Memory access is wrong
        return False
    except Exception:
        # Unexpected state, return false
        return False

# Example usage (can be commented out for testing)
if __name__ == "__main__":
    leaking_size = find_incremental_memory_leak()
    print(f"Suspected leaking size: {leaking_size}")

def find_memory_leaks(memory_measurements, code_sections):
    leaking_sections = []
    for i in range(1, len(memory_measurements)):
        # Check for sustained memory increases.
        if memory_measurements[i] > memory_measurements[i - 1]:
            current_code_section = code_sections[i]
            leaking_sections.append(current_code_section)

    return leaking_sections

def identify_leaking_code(leaking_sections):
    # Identify common code sections during leaks.
    suspect_code = set(leaking_sections)
    return suspect_code

def analyze_memory_leak(suspect_code):
    # Use tools and techniques to find leaks.
    for section in suspect_code:
        print(f"Analyzing code section: {section}")
        # Simulate automated memory leak detection
        if "memory allocation" in section and "memory deallocation" not in section:
            # We've found a potential leak, confirm it.
            print(f"Potential memory leak found in section: {section}")
            return section
        else:
            print("No memory leaks detected.")
    return None

def fix_memory_leak(code_section):
    # Free memory allocated by the code.
    if code_section:
        print(f"Fixing memory leak in section: {code_section}")
        fixed_code = code_section.replace("memory allocation", "memory deallocation")
        print(f"Fixed code: {fixed_code}")
        return fixed_code

    else:
        print("No code section provided to fix.")
        return None

if __name__ == '__main__':
    # Example usage:
    memory_measurements = [100, 105, 110, 115, 115, 120]
    code_sections = [
        "initialization",
        "data processing with memory allocation",
        "data processing with memory allocation",
        "report generation",
        "report generation",
        "data processing with memory allocation"
    ]

    leaking_sections = find_memory_leaks(memory_measurements, code_sections)
    suspect_code = identify_leaking_code(leaking_sections)
    # Identify code that consistently runs when memory increases
    leaking_code_section = analyze_memory_leak(suspect_code)

    # Now fix the memory leak.
    fixed_code = fix_memory_leak(leaking_code_section)