GitLab MR Auto-Review & Risk Assessment

Target Audience

• Developers: Those working on projects hosted on GitLab who want automated code review and risk assessment.
• QA Testers: Quality assurance teams needing structured information on changes to verify in their testing processes.
• Project Managers: Individuals overseeing development projects who require a clear understanding of code changes and associated risks.
• DevOps Engineers: Professionals integrating CI/CD processes who need to ensure code quality and security before deployment.

Problem Solved

This workflow automates the review process for merge requests in GitLab, addressing the following issues:

• Manual Code Review Overhead: Reduces the time and effort required for manual code reviews by automating the extraction of diffs and analysis.
• Risk Assessment: Provides a structured risk evaluation of code changes, highlighting potential issues and their severity levels (High, Medium, Low).
• Communication Gaps: Ensures timely notifications to relevant stakeholders (developers, QA testers) about the changes and associated risks via email.

Workflow Steps

1. Trigger: The workflow is initiated manually or automatically when a merge request (MR) is created or updated in GitLab.
2. Extract Diff: Fetches the code changes (diffs) from the GitLab API for the specific MR.
3. Check for Changes: Validates whether there are any code changes in the MR before proceeding.
4. AI Analysis: Utilizes an AI agent to analyze the diff, providing a summary, risk level, recommendations, potential issues, and test cases.
5. Output Parsing: Cleans and structures the AI-generated output for clarity and usability.
6. Email Notification: Sends a detailed HTML-formatted report to a distribution list of developers and QA testers, summarizing the findings and recommendations.
7. Comment on MR: Posts the AI-generated review report as a comment on the GitLab MR for visibility.