## Techniques for Testing & Debugging This section outlines the fundamental techniques used to find, analyze, and fix errors (*bugs*) in code, and to systematically verify that code functions as intended. ### 3.3.1 Debugging *Debugging* is the systematic process of finding and resolving defects or problems (*bugs*) within a computer program that prevent it from operating correctly. The goal is to locate the source of an error so it can be fixed, ensuring the program runs smoothly and produces the desired results. #### Simple Debugging with `print` Statements The most basic debugging method involves adding `print()` statements at critical points in the code. This allows a programmer to track the program's flow and inspect the values of variables at different stages of execution. * **Purpose**: To verify that variables, expressions, or blocks of code are behaving as expected. * **Strategy**: Place `print` statements where important calculations or value updates occur. Label the output for clarity. **Example: Finding a Bug in Matrix Transpose** The following code attempts to transpose a matrix but contains a bug. `print` statements are added to diagnose the issue. *Original Buggy Code Snippet (from text):* The bug is on line 8: `new_row.append(matrix[col][row]])` should be `new_row.append(matrix[row][col])`. The print statements help identify that the values being appended are incorrect. *Corrected Code with Diagnostic `print` Statements:* ```python matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] transpose = [] # The bug was in this line: new_row.append(matrix[col][row]]) # It should be: new_row.append(matrix[row][col]) # The print statements below would help find this. for col in range(len(matrix[0])): new_row = [] print(f'Print-1 Outer Loop Start: new_row is {new_row}') for row in range(len(matrix)): # This is the line that needs fixing value_to_append = matrix[row][col] print(f'Print-2 Inner Loop: Appending matrix[{row}][{col}] which is {value_to_append}') new_row.append(value_to_append) print(f'Print-3 Outer Loop End: new_row is {new_row}') transpose.append(new_row) print("\nFinal Transposed Matrix:") for row in transpose: print(row) ``` #### Advanced Debugging with IDE Tools Modern *Integrated Development Environments* (IDEs) like Visual Studio or REPLIT provide sophisticated debugging tools that offer more control than `print` statements. * **Breakpoints**: A marker placed on a line of code that intentionally pauses the program's execution at that point. This allows the developer to inspect the program's state (e.g., variable values) at a specific moment. * **Watchpoints**: A tool that monitors the value of a specific variable or expression. The developer can "watch" how a variable changes as they step through the code line by line from a breakpoint. ### 3.3.2 Python Unit Test *Unit testing* is a software testing method where individual units or components of a program are tested in isolation to ensure they work correctly. Python's built-in `unittest` framework (and simpler assertion-based tests) facilitates this. * **Process**: For a function you write, you write a corresponding *test function* that calls the original function with various inputs and checks if the output is correct. * **Assertions**: The `assert` statement is used to verify a condition. If the condition is `True`, the program continues. If it is `False`, it raises an `AssertionError`, immediately indicating that a test has failed. **Example: Testing an `add()` function** This code defines a simple `add` function and a `test_add` function to verify its correctness with different inputs (test cases). ```python # Function to be tested def add(a, b): return a + b # Test function def test_add(): # Test case 1: Positive numbers result = add(2, 3) assert result == 5, f"Test failed: Expected 5 but got {result}" # Test case 2: Zeroes result = add(0, 0) assert result == 0, f"Test failed: Expected 0 but got {result}" # Test case 3: Positive and negative numbers result = add(-1, 1) assert result == 0, f"Test failed: Expected 0 but got {result}" print("All tests passed!") # Run the test function test_add() ``` #### Combining Unit Testing and Debugging When a unit test fails, breakpoints can be used within the test function to investigate the cause of the failure. By placing a breakpoint on the failing `assert` line and adding the `result` variable to a watchpoint, a developer can see the exact incorrect value that caused the test to fail. ### Additional Testing Techniques While the curriculum focuses on debugging and unit testing, it is important to distinguish between manual and automated verification methods.