[PR #200] Add E2E Test for Rebase Scenario with Mixed Authorship #318

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opened 2026-03-02 04:13:17 +03:00 by kerem · 0 comments

kerem commented

2026-03-02 04:13:17 +03:00

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Original Pull Request: https://github.com/git-ai-project/git-ai/pull/200

State: closed
Merged: Yes

Overview

This PR adds a comprehensive end-to-end test that verifies git-ai correctly preserves AI and human authorship attribution when rebasing a feature branch with mixed authorship onto a diverged main branch.

What This Test Covers

The test simulates a realistic development workflow:

Initial Setup: Creates a common ancestor commit with an app.py file containing clearly separated sections
Feature Branch Development:
- Creates a feature branch from the common ancestor
- Adds a commit with mixed authorship (human adds function signature, AI adds implementation logic)
- Uses git-ai checkpoint to track both human and AI contributions
Main Branch Divergence:
- Main branch moves forward with 3 new commits
- All commits modify the same app.py file in different sections
- Adds utility functions in the "Utility functions section"
Rebase Operation: Rebases the feature branch onto the updated main branch
Verification: Ensures authorship attribution is preserved after rebase

Key Verifications

The test validates:

✅ Stats Preservation: AI and human contribution stats match before and after rebase
✅ Blame Integrity: git-ai blame correctly shows both AI (mock_ai) and human (Test User) authorship after rebase
✅ Content Preservation: All changes from both branches are present in the final file
✅ Branch Structure: Feature branch is properly rebased on top of main's commits
✅ Line-level Attribution: Fine-grained authorship tracking at the line level survives the rebase

Why This Matters

Rebasing is a common Git operation that can be problematic for authorship tracking systems. This test ensures that git-ai's authorship attribution:

Survives complex Git operations like rebase
Correctly handles conflicts and file modifications in the same file across branches
Maintains accurate AI vs. human contribution metrics through branch operations
Provides reliable data for AI usage analytics and attribution

Run the test with:

bats tests/e2e/user-scenarios.bats -f "rebase feature branch with mixed authorship"

Or run the full E2E test suite:

task test:e2e

**Original Pull Request:** https://github.com/git-ai-project/git-ai/pull/200 **State:** closed **Merged:** Yes --- ## Overview This PR adds a comprehensive end-to-end test that verifies git-ai correctly preserves AI and human authorship attribution when rebasing a feature branch with mixed authorship onto a diverged main branch. ## What This Test Covers The test simulates a realistic development workflow: 1. **Initial Setup**: Creates a common ancestor commit with an `app.py` file containing clearly separated sections 2. **Feature Branch Development**: - Creates a feature branch from the common ancestor - Adds a commit with mixed authorship (human adds function signature, AI adds implementation logic) - Uses `git-ai checkpoint` to track both human and AI contributions 3. **Main Branch Divergence**: - Main branch moves forward with 3 new commits - All commits modify the same `app.py` file in different sections - Adds utility functions in the "Utility functions section" 4. **Rebase Operation**: Rebases the feature branch onto the updated main branch 5. **Verification**: Ensures authorship attribution is preserved after rebase ## Key Verifications The test validates: - ✅ **Stats Preservation**: AI and human contribution stats match before and after rebase - ✅ **Blame Integrity**: `git-ai blame` correctly shows both AI (`mock_ai`) and human (`Test User`) authorship after rebase - ✅ **Content Preservation**: All changes from both branches are present in the final file - ✅ **Branch Structure**: Feature branch is properly rebased on top of main's commits - ✅ **Line-level Attribution**: Fine-grained authorship tracking at the line level survives the rebase ## Why This Matters Rebasing is a common Git operation that can be problematic for authorship tracking systems. This test ensures that git-ai's authorship attribution: - Survives complex Git operations like rebase - Correctly handles conflicts and file modifications in the same file across branches - Maintains accurate AI vs. human contribution metrics through branch operations - Provides reliable data for AI usage analytics and attribution Run the test with: ```bash bats tests/e2e/user-scenarios.bats -f "rebase feature branch with mixed authorship" ``` Or run the full E2E test suite: ```bash task test:e2e ```