Test Failure Analysis Mindset

Establish a balanced investigative approach for all test failures encountered in this session.

Core Principle

Load and follow the standards in /python-engineering:standards-for-python-development when shared testing or quality rules from this plugin apply.

Tests are specifications - they define expected behavior. When they fail, it's a critical moment requiring balanced investigation, not automatic dismissal.

Dual Hypothesis Approach

Always consider both possibilities when a test fails:

Hypothesis A	Hypothesis B
Test expectations are incorrect	Implementation has a bug
Test is outdated	Test caught a regression
Test has wrong assumptions	Test found an edge case

Investigation Protocol

For EVERY test failure:

1. Pause and Read

• Understand what the test is trying to verify
• Read its name, comments, and assertions carefully
• Check the test's history (git blame) for context

2. Trace the Implementation

• Follow the code path that leads to the failure
• Understand actual behavior vs. expected behavior
• Check if recent changes affected this code path

3. Consider the Context

• Is this testing a documented requirement?
• Would current behavior surprise a user?
• What would be the impact of each possible fix?

4. Make a Reasoned Decision

Situation	Action
Implementation is wrong	Fix the bug
Test is wrong	Fix test AND document why
Unclear	Seek clarification before changing

5. Learn from the Failure

• What can this teach about the system?
• Should additional tests cover related cases?
• Is there a pattern being missed?

Red Flags (Dangerous Patterns)

• 🚫 Immediately changing tests to match implementation
• 🚫 Assuming implementation is always correct
• 🚫 Bulk-updating tests without individual analysis
• 🚫 Removing "inconvenient" test cases
• 🚫 Adding mock/stub workarounds instead of fixing root causes

Good Practices

• ✅ Treat each test failure as a potential bug discovery
• ✅ Document analysis in comments when fixing tests
• ✅ Write clear test names that explain intent
• ✅ When changing a test, explain why the original was wrong
• ✅ Consider adding more tests when finding ambiguity

Example Responses

Good: "I see test_user_validation is failing. Let me trace through the validation logic to understand if this is catching a real bug or if the test's expectations are incorrect."

Bad: "The test is failing so I'll update it to match what the code does."

Remember

Every test failure is an opportunity to:

• Discover and fix a bug before users do
• Clarify ambiguous requirements
• Improve system understanding
• Strengthen the test suite

The goal is NOT to make tests pass quickly. The goal IS to ensure the system behaves correctly.

Related Skills

• analyze-test-failures: Use /python-engineering:analyze-test-failures for detailed analysis of specific test failures
• comprehensive-test-review: Use /python-engineering:comprehensive-test-review for full test suite review