The R programming language is very popular for developing statistical software and data analysis, thanks to rich libraries, concise and expressive syntax, and support for interactive programming. Yet, the semantics of R is fairly complex, contains many subtle corner cases, and is not formally specified. This makes it difficult to reason about R programs. In this work, we develop a big-step operational semantics for R in the form of an interpreter written in the Coq proof assistant. We ensure the trustworthiness of the formalization by introducing a monadic encoding that allows the Coq interpreter, CoqR, to be in direct visual correspondence with the reference R interpreter, GNU R. Additionally, we provide a testing framework that supports systematic comparison of CoqR and GNU R. In its current state, CoqR covers the nucleus of the R language as well as numerous additional features, making it pass a significant number of realistic test cases from the GNU R and FastR projects. To exercise the formal specification, we prove in Coq the preservation of memory invariants in selected parts of the interpreter. This work is an important first step towards a robust environment for formal verification of R programs. CCS Concepts • Theory of computation → Denotational semantics; • Software and its engineering → Application specific development environments;

GraphQL is a novel language for specifying and querying web APIs, allowing clients to flexibly and efficiently retrieve data of interest. The GraphQL language specification is unfortunately only available in prose, making it hard to develop robust formal results for this language. Recently, Hartig and Pérez proposed a formal semantics for GraphQL in order to study the complexity of GraphQL queries. The semantics is however not mechanized and leaves certain key aspects unverified. We present GraphCoQL, the first mechanized formalization of GraphQL, developed in the Coq proof assistant. GraphCoQL covers the schema definition DSL, query definitions, validation of both schema and queries, as well as the semantics of queries over a graph data model. We illustrate the application of GraphCoQL by formalizing the key query transformation and interpretation techniques of Hartig and Pérez, and proving them correct, after addressing some imprecisions and minor issues. We hope that GraphCoQL can serve as a solid formal baseline for both language design and verification efforts for GraphQL. CCS Concepts• Information systems → Web services; Query languages; • Theory of computation → Semantics and reasoning.

No abstract