AI-Assisted Git Bisect and Regression Hunting

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-ai-coding-AI-git-bisect-assistance-creators

1. What is the primary way AI accelerates the git bisect process?

   1. Running automated tests on every commit in the repository
   2. Replacing the need for version control entirely
   3. Ranking suspect commits by relevance before the binary search begins
   4. Automatically fixing bugs discovered during the bisect

2. Which task can an AI assistant reliably perform during regression hunting?

   1. Running the test suite on each bisect step
   2. Identifying which commits were silently flag-gated
   3. Determining the exact line of code that caused the bug
   4. Reading commit messages and ranking by relevance to a symptom

3. Why must you run each bisect step multiple times for high-noise tests?

   1. Because flaky tests produce random good/bad results that can mislead the bisect
   2. To give the AI more time to analyze the results
   3. To compile the code with different optimization flags
   4. To satisfy version control checksum requirements

4. An AI suggests a revert for a commit with large blast radius. What does 'blast radius' refer to?

   1. The physical size of the diff in kilobytes
   2. The time duration since the commit was made
   3. The number of files deleted in the commit
   4. The extent of changes across the codebase caused by the commit

5. When should you choose to fix-forward instead of reverting a buggy commit?

   1. When the commit was made more than six months ago
   2. When other commits depend on the changes and reverting would break more code
   3. When the commit message is unclear
   4. When the commit has a small blast radius

6. What information can an AI analyze to rank commit suspects?

   1. The author's GitHub profile statistics
   2. The number of pull requests merged that week
   3. Only the commit hash and timestamp
   4. Commit messages, diff stats, and CI history

7. What is regression hunting?

   1. Searching for commits that introduced a bug or broken feature
   2. Hunting for performance improvements in the codebase
   3. Locating missing documentation in a repository
   4. Finding who wrote a specific line of code

8. What does git bisect use to find the problematic commit?

   1. A random sampling approach
   2. A hash-based lookup table
   3. A linear scan of every commit
   4. A binary search algorithm

9. An AI tells you it cannot know which commits were 'silently flag-gated.' What does this mean?

   1. The commits had conditional logic that prevented bugs from manifesting in certain configurations
   2. The commits were deleted from git history
   3. The commits were made by users with private accounts
   4. The commits exceeded GitHub's file size limits

10. What is commit triage in the context of regression hunting?

    1. Organizing commits by color-coded labels in GitHub
    2. Merging duplicate commits in the history
    3. Reviewing and ranking commits by likelihood of containing a bug
    4. Deleting commits that fail automated tests

11. You run a bisect step and the result is 'bad.' What must you do next?

    1. Delete the commit immediately
    2. Run git reset to undo the bisect
    3. Revert all changes since the last good commit
    4. Mark this commit as bad and test a different commit in the range

12. Which limitation of AI in bisect requires human intervention?

    1. Reading commit messages to rank suspects
    2. Running tests to verify each bisect step
    3. Suggesting revert vs fix-forward
    4. Analyzing diffs for code complexity

13. An AI ranks commits by 'likely relevance to a symptom.' What does 'symptom' refer to in this context?

    1. The observable bug behavior or error report
    2. The number of files affected
    3. The compiler error message
    4. The commit author's reported symptoms

14. If you have 200 commits to search, and git bisect uses binary search, approximately how many steps are needed?

    1. 100 steps (half the commits)
    2. 200 steps (linear)
    3. 1 step if the AI is smart enough
    4. About 8 steps (logarithmic)

15. What does the lesson advise about using AI when you have a large commit range to bisect?

    1. Let AI randomly select commits to test instead of using binary search
    2. Use AI to narrow the range by ranking suspects before starting binary search
    3. Skip bisect entirely and use AI to directly find the bug
    4. Only use AI if the commit range is less than 50 commits