AI Code Refactor Suggester for Legacy Systems
Automate the identification of refactoring opportunities in legacy codebases, helping developers improve maintainability and performance without manual review.
The idea in one paragraph
This tool analyzes legacy code from GitHub repositories and uses AI to suggest refactoring improvements. It identifies patterns for optimization, suggests cleaner code, and can even generate preliminary pull requests or Jira tickets.
Tools you'll use
Step-by-step playbook
- 1
Develop code analysis AI
Train a custom AI model (or fine-tune an existing LLM like ChatGPT) to understand code structure, identify anti-patterns, and suggest improvements for specific languages.
- 2
Integrate with GitHub
Build an integration using the GitHub API to allow users to connect their repositories and feed code for analysis.
- 3
Build suggestion dashboard
Create a dashboard (e.g., with Bubble) where users can view AI-generated refactoring suggestions, explanations, and estimated impact.
- 4
Implement Jira/PR creation
Add functionality to automatically generate Jira tickets or draft pull requests based on accepted refactoring suggestions.
- 5
Beta test with developers
Recruit a small group of developers working with legacy systems to beta test the tool and gather feedback for refinement.
Frequently asked questions
What programming languages will be supported?
Initially, we will focus on one or two widely used languages like Java or Python, with plans to expand based on demand.
How does it handle complex enterprise setups?
The tool will be designed with secure access and granular permissions, allowing it to integrate into enterprise environments while respecting security protocols.
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