Developing provably sound type systems is a non-trivial task which, as of today, typically requires expert skills in formal methods and a considerable amount of time. Our Veritas [3] project aims at providing support for the development of soundness proofs of type systems and efficient type checker implementations from type system specifications. To this end, we investigate how to best automate typical steps within type soundness proofs. In this paper, we focus on progress proofs for type systems of domain-specific languages. As a running example for such a type system, we model a subset SQL and augment it with a type system. We compare two different approaches for automating proof steps of the progress proofs for this type system against each other: firstly, our own tool Veritas, which translates proof goals and specifications automatically to TPTP [13] and calls Vampire [8] on them, and secondly, the programming language Dafny [6], which translates proof goals and specifications to the intermediate verification language Boogie 2 [5] and calls the SMT solver Z3 [9] on them. We find that Vampire and Dafny are equally well-suited for automatically proving simple steps within progress proofs.@en

Computer science has seen much progress in the area of automated verification in the last decades. Yet, there are many domains where abstract strategies for verifying standard properties are well-understood by domain experts, but still not automated to a satisfactory degree. One example for such a domain are type soundness proofs. Being able to express domain-specific verification strategies using domain-specific terminology and concepts can help to narrow down this gap toward more automated verification. We present the requirements, design, and implementation of a configurable verification infrastructure that allows for expressing domain knowledge about proofs and for interfacing with existing automated theorem provers and solvers to verify individual proof steps. As an application scenario for our infrastructure, we present the development of a standard type soundness proof for a typed subset of SQL. @en

Computer science has seen much progress in the area of automated verification in the last decades. Yet, there are many domains where abstract strategies for verifying standard properties are well-understood by domain experts, but still not automated to a satisfactory degree. One example for such a domain are type soundness proofs. Being able to express domain-specific verification strategies using domain-specific terminology and concepts can help to narrow down this gap toward more automated verification. We present the requirements, design, and implementation of a configurable verification infrastructure that allows for expressing domain knowledge about proofs and for interfacing with existing automated theorem provers and solvers to verify individual proof steps. As an application scenario for our infrastructure, we present the development of a standard type soundness proof for a typed subset of SQL. @en

Exploration of language specifications helps to discover errors and inconsistencies early during the development of a programming language. We propose exploration of language specifications via application of existing automated first-order theorem provers (ATPs). To this end, we translate language specifications and exploration tasks to first-order logic, which many ATPs accept as input. However, there are several different strategies for compiling a language specification to first-order logic, and even small variations in the translation may have a large impact on the time it takes ATPs to find proofs. In this paper, we first present a systematic empirical study on how to best compile language specifications to first-order logic such that existing ATPs can solve typical exploration tasks efficiently. We have developed a compiler product line that implements 36 different compilation strategies and used it to feed language specifications to 4 existing first-order theorem provers. As benchmarks, we developed language specifications for typed SQL and for a Questionnaire Language (QL), with 50 exploration goals each. Our study empirically confirms that the choice of a compilation strategy greatly influences prover performance in general and shows which strategies are advantageous for prover performance. Second, we extend our empirical study with 4 domain-specific strategies for axiom selection and find that axiom selection does not influence prover performance in our benchmark specifications.@en

Exploration of language specifications helps to discover errors and inconsistencies early during the development of a programming language. We propose exploration of language specifications via application of existing automated first-order theorem provers (ATPs). To this end, we translate language specifications and exploration tasks to first-order logic, which many ATPs accept as input. However, there are several different strategies for compiling a language specification to first-order logic, and even small variations in the translation may have a large impact on the time it takes ATPs to find proofs. In this paper, we present a systematic empirical study on how to best compile language specifications to first-order logic such that existing ATPs can solve typical exploration tasks efficiently. We have developed a compiler product line that implements 36 different compilation strategies and used it to feed language specifications to 4 existing first-order theorem provers. As a benchmark, we developed a language specification for typed SQL with 50 exploration goals. Our study empirically confirms that the choice of a compilation strategy in general greatly influences prover performance and shows which strategies are advantageous for prover performance.@en