Build a Practical Define the Problem Example in Debugging and Problem Solving

Define the build target

For Define the Problem, take a small failing program or command, write exact reproduction steps, reduce it to the smallest failing case, then test one hypothesis at a time. Build the boundary case using this implementation lens: Use reproducible symptoms, logs, traces, debugger state, hypotheses, minimal changes, and repeatable verification to isolate causes instead of guessing.

Keep the Define the Problem build centered on these technical constraints: Expected versus observed behavior. Reproduction steps and inputs. Apply them through this path lens: Use reproducible symptoms, logs, traces, debugger state, hypotheses, minimal changes, and repeatable verification to isolate causes instead of guessing. Use reproducible symptoms, logs, traces, debugger state, hypotheses, minimal changes, and repeatable verification to isolate causes instead of guessing.

Implement the core behavior

Implement Define the Problem around the module artifact—a working define the problem exercise with a documented technical result—and keep the implementation specific to this path context: Use reproducible symptoms, logs, traces, debugger state, hypotheses, minimal changes, and repeatable verification to isolate causes instead of guessing.

def average(total, count):
    return total / count

cases = [(30, 3), (0, 0)]
for total, count in cases:
    try:
        print(total, count, average(total, count))
    except Exception as exc:
        print(type(exc).__name__, str(exc), {'total': total, 'count': count})

python3 reproduce.py

The normal case succeeds and the zero-count input reproduces a precise ZeroDivisionError with the failing input recorded.

practice/\n├── README.md\n├── define-the-problem-build.py\n└── evidence/\n    └── expected-result.txt

Run the complete path

Run one realistic Define the Problem case end to end and record the required evidence: the module-specific command, output, test, rendered state, query result, log, or measurement that proves the exercise worked. Interpret the result through this path context: Use reproducible symptoms, logs, traces, debugger state, hypotheses, minimal changes, and repeatable verification to isolate causes instead of guessing.

Change one meaningful condition

Modify one condition central to Define the Problem using this path context: Use reproducible symptoms, logs, traces, debugger state, hypotheses, minimal changes, and repeatable verification to isolate causes instead of guessing. Predict the new result before rerunning the same workflow.

Verify the artifact

Your deliverable is a working define the problem exercise with a documented technical result.

Common mistakes to avoid

• Changing code before reproducing.
• Describing impact without exact symptom.
• Multiple simultaneous fixes.
• Discarding logs or failing inputs.