arXiv subjects

Dimitrios J. Economou

Publications and source records attributed to Dimitrios J. Economou.

4 recordsLinked to original sources

arXiv2023

Focusing on Refinement Typing

We present a logically principled foundation for systematizing, in a way that works with any computational effect and evaluation order, SMT constraint generation seen in refinement type systems for functional programming languages. By carefully combining a focalized variant of call-by-push-value, bidirectional typing, and our novel technique of value-determined indexes, our system generates solvable SMT constraints without existential (unification) variables. We design a polarized subtyping relation allowing us to prove our logically focused typing algorithm is sound, complete, and decidable. We prove type soundness of our declarative system with respect to an elementary domain-theoretic denotational semantics. Type soundness implies, relatively simply, the total correctness and logical consistency of our system. The relative ease with which we obtain both algorithmic and semantic results ultimately stems from the proof-theoretic technique of focalization.

cs.PL↗

arXiv2018

Prestige drives epistemic inequality in the diffusion of scientific ideas

The spread of ideas in the scientific community is often viewed as a competition, in which good ideas spread further because of greater intrinsic fitness, and publication venue and citation counts correlate with importance and impact. However, relatively little is known about how structural factors influence the spread of ideas, and specifically how where an idea originates might influence how it spreads. Here, we investigate the role of faculty hiring networks, which embody the set of researcher transitions from doctoral to faculty institutions, in shaping the spread of ideas in computer science, and the importance of where in the network an idea originates. We consider comprehensive data on the hiring events of 5032 faculty at all 205 Ph.D.-granting departments of computer science in the U.S. and Canada, and on the timing and titles of 200,476 associated publications. Analyzing five popular research topics, we show empirically that faculty hiring can and does facilitate the spread of ideas in science. Having established such a mechanism, we then analyze its potential consequences using epidemic models to simulate the generic spread of research ideas and quantify the impact of where an idea originates on its longterm diffusion across the network. We find that research from prestigious institutions spreads more quickly and completely than work of similar quality originating from less prestigious institutions. Our analyses establish the theoretical trade-offs between university prestige and the quality of ideas necessary for efficient circulation. Our results establish faculty hiring as an underlying mechanism that drives the persistent epistemic advantage observed for elite institutions, and provide a theoretical lower bound for the impact of structural inequality in shaping the spread of ideas in science.

cs.SI↗

arXiv2018

Fungi: Typed incremental computation with names

Incremental computations attempt to exploit input similarities over time, reusing work that is unaffected by input changes. To maximize this reuse in a general-purpose programming setting, programmers need a mechanism to identify dynamic allocations (of data and subcomputations) that correspond over time. We present Fungi, a typed functional language for incremental computation with names. Unlike prior general-purpose languages for incremental computing, Fungi's notion of names is formal, general, and statically verifiable. Fungi's type-and-effect system permits the programmer to encode (program-specific) local invariants about names, and to use these invariants to establish global uniqueness for their composed programs, the property of using names correctly. We prove that well-typed Fungi programs respect global uniqueness. We derive a bidirectional version of the type and effect system, and we have implemented a prototype of Fungi in Rust. We apply Fungi to a library of incremental collections, showing that it is expressive in practice.

cs.PL↗

arXiv2017

Refinement types for precisely named cache locations

Many programming language techniques for incremental computation employ programmer-specified names for cached information. At runtime, each name identifies a "cache location" for a dynamic data value or a sub-computation; in sum, these cache location choices guide change propagation and incremental (re)execution. We call a cache location name precise when it identifies at most one value or subcomputation; we call all other names imprecise, or ambiguous. At a minimum, cache location names must be precise to ensure that change propagation works correctly; yet, reasoning statically about names in incremental programs remains an open problem. As a first step, this paper defines and solves the precise name problem, where we verify that incremental programs with explicit names use them precisely. To do so, we give a refinement type and effect system, and prove it sound (every well-typed program uses names precisely). We also demonstrate that this type system is expressive by verifying example programs that compute over efficient representations of incremental sequences and sets. Beyond verifying these programs, our type system also describes their dynamic naming strategies, e.g., for library documentation purposes.

cs.PL↗