Modern LLM coding assistants have evolved into tool-using agents that can read repositories, execute commands, modify infrastructure, and trigger external side effects, expanding t…
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Decision-makers in engineering, policy, economics, and operations often face trade-offs among conflicting objectives, yet method selection remains fragmented across disciplines. Th…
LLM-assisted “vibe coding” accelerates software delivery but introduces new attack surfaces beyond traditional secure SDLC risks. This project will build a practical threat model f…
Multi-objective decision support now spans classical scalarization, Pareto-evolutionary search, outranking-based multicriteria ranking, and uncertainty-aware formulations, but prac…
Multi-objective decision support is fragmented by a representation mismatch: Pareto-set methods, outranking relations, and scalarization-based methods emit different mathematical o…
AI-assisted coding systems now influence repository edits, dependency selection, and deployment decisions, which creates coupled attack surfaces spanning prompt-channel abuse, supp…