A prompting method that forces GPAI models to state SE best practices before deciding reduces prompt-induced cognitive biases by 51% on average across eight tested biases.
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cs.SE 2years
2026 2representative citing papers
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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Mitigating Prompt-Induced Cognitive Biases in General-Purpose AI for Software Engineering
A prompting method that forces GPAI models to state SE best practices before deciding reduces prompt-induced cognitive biases by 51% on average across eight tested biases.
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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.