Abstract:Package managers are legion. Every programming language and operating system has its own solution, each with subtly different semantics for dependency resolution. This fragmentation prevents multilingual projects from expressing precise dependencies across language ecosystems; it leaves external system and hardware dependencies implicit and unversioned; it obscures security vulnerabilities that lie in the full dependency graph. We present the \textit{Package Calculus}, a formalism for dependency resolution that unifies the core semantics of diverse package managers. Through a series of formal reductions, we show how this core is expressive enough to model the diversity that real-world package managers employ in their dependency expression languages. By using the Package Calculus as the intermediate representation of dependencies, we enable translation between distinct package managers and resolution across ecosystems.
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And finally, be transparent about it. Candidates deserve to know how AI is being used in your evaluation process — which tools are involved, what they're measuring, and how those results factor into decisions. Beyond just being the ethical baseline, transparency actually tends to improve the candidate experience. People are generally a lot more comfortable with AI evaluation when they understand what's going on, rather than feeling like they're being judged by some invisible black box.
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