Developers use LLMs like ChatGPT mainly for knowledge acquisition and code generation at the detailed design level, reporting benefits such as better technology selection and early flaw detection alongside limitations like lengthy outputs, incorrect code, and hallucinations.
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AI IDEs with structured guidance can produce functional large-scale code but frequently introduce design flaws such as duplication, complexity, and principle violations that risk long-term maintainability.
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Using LLMs in Software Design: An Empirical Study of GitHub and A Practitioner Survey
Developers use LLMs like ChatGPT mainly for knowledge acquisition and code generation at the detailed design level, reporting benefits such as better technology selection and early flaw detection alongside limitations like lengthy outputs, incorrect code, and hallucinations.
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Beyond Functional Correctness: Design Issues in AI IDE-Generated Large-Scale Projects
AI IDEs with structured guidance can produce functional large-scale code but frequently introduce design flaws such as duplication, complexity, and principle violations that risk long-term maintainability.