Developers using AI assistants exhibit more stable emotions and greater focus on code creation, evaluation, and verification, captured in a new four-dimensional S-IASE model from retrospective labeling of screen recordings, surveys, and interviews.
Glassman, Peter Groenwegen, Sumit Gulwani, Austin Z
5 Pith papers cite this work, alongside 5 external citations. Polarity classification is still indexing.
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Vulnsage, a multi-agent framework, generates 34.64% more exploits than prior tools and verified 146 zero-day vulnerabilities in real-world open-source libraries.
LightGBM with team-level features outperforms a bank's existing rule-based change risk process on a one-year dataset while using SHAP for regulatory explainability.
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A Multi-Agent Framework for Automated Exploit Generation with Constraint-Guided Comprehension and Reflection
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