Developers face challenges with growing codebases and a lack of clarity on needed improvements. AI tools, like Copilot, traditionally speed up coding by suggesting code, but there is potential for AI to analyze existing code instead. By utilizing a ranking system, AI models can identify parts of the code that may become problematic due to fragile logic or inconsistent patterns. Language models, including ChatGPT, show promise in assessing code quality, providing insights that can support more efficient and focused development workflows while addressing underlying issues.
Developers are starting to look beyond AI-generated code and are asking a bigger question: can these tools help make sense of what's already written?
Some language models are learning to recognize the kinds of patterns that usually show up in well-structured, reliable code.
A ranking system could help make sense of it all by scanning the entire codebase and identifying the files most likely to create problems over time.
AI could give teams a clearer starting point by highlighting code that's structurally weak or showing signs of deeper issues, without getting distracted by surface-level styling.
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