You're probably using ChatGPT for code snippets. But the real revolution in software maintenance isn't writing new code—it's automating the tedious, risky work of refactoring and vulnerability patching.
Technical debt and security flaws are huge bottlenecks. Traditional tools are too rigid to handle real-world complexity. Enter specialized Large Language Models (LLMs).
The LLM Code Maintenance Revolution is Here:
Monoliths to Clean Architecture: See how a structured prompt guided an LLM to decompose a 2,400-line payment method into clean, Strategy Pattern classes, reducing complexity by 90%.
Agent-Based Refactoring: Learn about frameworks like MANTRA, which use multi-agent collaboration (Developer Agent + Reviewer Agent) and self-repair loops to hit an 82.8% success rate on complex refactorings—blowing raw GPT out of the water.
Zero-Day Patching: Discover how systems like LLMPatch leverage ensemble validation and semantics-aware scoping to automatically generate patches for real-world security vulnerabilities, even succeeding against 7 out of 11 unknown zero-days.
LLMs aren't just writing code; they're becoming specialized engines that understand and improve your code at a fundamental, architectural level.
Ready to go beyond console.log('Hello World')?
If you want to integrate these high-impact AI capabilities into your dev workflow—and learn the structured prompting techniques required—don't miss the full deep dive!
Click here to read the full article: https://finetunednews.com/articles/2025-11-13-boost-code-quality-llms-for-refactoring-and-patching
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