Formal Compiler Implementation in a Logical Framework

The task of designing and implementing a compiler can be a difficult and error-prone process. In this paper, we present a new approach based on the use of higher-order abstract syntax and term rewriting in a logical framework. All program transformations, from parsing to code generation, are cleanly isolated and specified as term rewrites. This has several advantages. The correctness of the compiler depends solely on a small set of rewrite rules that are written in the language of formal mathematics. In addition, the logical framework guarantees the preservation of scoping, and it automates many frequently-occurring tasks including substitution and rewriting strategies. As we show, compiler development in a logical framework can be easier than in a general-purpose language like ML, in part because of automation, and also because the framework provides extensive support for examination, validation, and debugging of the compiler transformations. The paper is organized around a case study, using the MetaPRL logical framework to compile an ML-like language to Intel x86 assembly. We also present a scoped formalization of x86 assembly in which all registers are immutable

Abstracting Syntax

Binding is a fundamental part of language specification, yet it is both difficult and tedious to get right. In previous work, we argued that an approach based on locally nameless representation and a particular style for defining inductive relations can provide a portable, transparent, lightweight methodology to define the semantics of binding. Although the binding infrastructure required by this approach is straightforward to develop, it leads to duplicated effort and code as the number of binding forms in a language increases. In this paper, we critically compare a spectrum of approaches that attempt to ameliorate this tedium by unifying the treatment of variables and binding. In particular, we compare our original methodology with two alternative ideas: First, we define variable binding in the object language via variable binding in a reusable library. Second, we present a novel approach that collapses the syntactic categories of the object language together, permitting variables to be shared between them. Our main contribution is a careful characterization of the benefits and drawbacks of each approach. In particular, we use multiple solutions to the POPLMARK challenge in the Coq proof assistant to point out specic consequences with respect to the size of the binding infrastructure, transparency of the definitions, impact to the metatheory of the object language, and adequacy of the object language encoding

Process Migration and Transactions Using a Novel Intermediate Language

[no abstract

Formal Component-Based Semantics

One of the proposed solutions for improving the scalability of semantics of programming languages is Component-Based Semantics, introduced by Peter D. Mosses. It is expected that this framework can also be used effectively for modular meta theoretic reasoning. This paper presents a formalization of Component-Based Semantics in the theorem prover Coq. It is based on Modular SOS, a variant of SOS, and makes essential use of dependent types, while profiting from type classes. This formalization constitutes a contribution towards modular meta theoretic formalizations in theorem provers. As a small example, a modular proof of determinism of a mini-language is developed.Comment: In Proceedings SOS 2011, arXiv:1108.279

Mechanized Metatheory for the Masses: The \u3cb\u3ePOPLMARK\u3c/b\u3e Challenge

How close are we to a world where every paper on programming languages is accompanied by an electronic appendix with machinechecked proofs? We propose an initial set of benchmarks for measuring progress in this area. Based on the metatheory of System F, a typed lambda-calculus with second-order polymorphism, subtyping, and records, these benchmarks embody many aspects of programming languages that are challenging to formalize: variable binding at both the term and type levels, syntactic forms with variable numbers of components (including binders), and proofs demanding complex induction principles. We hope that these benchmarks will help clarify the current state of the art, provide a basis for comparing competing technologies, and motivate further research

Needle & knot : binder boilerplate tied up

To lighten the burden of programming language mechanization, many approaches have been developed that tackle the substantial boilerplate which arises from variable binders. Unfortunately, the existing approaches are limited in scope. They typically do not support complex binding forms (such as multi-binders) that arise in more advanced languages, or they do not tackle the boilerplate due to mentioning variables and binders in relations. As a consequence, the human mechanizer is still unnecessarily burdened with binder boilerplate and discouraged from taking on richer languages. This paper presents Knot, a new approach that substantially extends the support for binder boilerplate. Knot is a highly expressive language for natural and concise specification of syntax with binders. Its meta-theory constructively guarantees the coverage of a considerable amount of binder boilerplate for well-formed specifications, including that for well-scoping of terms and context lookups. Knot also comes with a code generator, Needle, that specializes the generic boilerplate for convenient embedding in COQ and provides a tactic library for automatically discharging proof obligations that frequently come up in proofs of weakening and substitution lemmas of type-systems. Our evaluation shows, that Needle & Knot significantly reduce the size of language mechanizations (by 40% in our case study). Moreover, as far as we know, Knot enables the most concise mechanization of the POPLmark Challenge (1a + 2a) and is two-thirds the size of the next smallest. Finally, Knot allows us to mechanize for instance dependentlytyped languages, which is notoriously challenging because of dependent contexts and mutually-recursive sorts with variables

The Quiet Revolution and the Family: Gender Composition of Tertiary Education and Early Fertility Patterns

It is well known that highly 'female' fields of study in tertiary education are characterized by higher fertility. However, existing work does not disentangle the selection-causality nexus. We use variation in gender composition of fields of study implied by the recent expansion of tertiary education in 19 European countries and a difference-in-differences research design, to show that the share of women on study peer groups affects early fertility levels only little. Early fertility by endogamous couples, i.e., by tertiary graduates from the same field of study, declines for women and increases for men with the share of women in the group, but non-endogamous fertility almost fully compensates for these effects, consistent with higher early fertility in highly 'female' fields of study being driven by selection of family-oriented students into these fields. We also show that the EU-wide level of gender segregation across fields of study has not changed since 2000

The psychological science accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data