Abstract. We present a novel counterexample generator for the interactive theorem prover Isabelle based on a compiler that synthesizes test data generators for functional programming languages (e.g. ML, Haskell) from specifications in Isabelle. In contrast to naive type-based test data generators, the smart generators take the preconditions into account and only generate tests that fulfill the preconditions. The smart generators are constructed by a compiler that reformulates the preconditions as logic programs and analyzes them with an enriched mode inference. From this inference, the compiler can construct the desired generators in the functional programming language. Applying these test data generators reduces the number of tests significantly and enables us to find errors in specifications where naive random and exhaustive testing fail. 1

the date of receipt and acceptance should be inserted later Abstract We present a solution to the PoplMark challenge designed by Aydemir et al., which has as a goal the formalization of the meta-theory of System F<:. The formalization is carried out in the theorem prover Isabelle/HOL using an encoding based on de Bruijn indices. We start with a relatively simple formalization covering only the basic features of System F<:, and explain how it can be extended to also cover records and more advanced binding constructs. We also discuss different styles of formalizing the evaluation relation, and how this choice influences executability of the specification. 1

We present a novel counterexample generator for the interactive theorem prover Isabelle based on a compiler that synthesizes test data generators for functional programming languages (e.g. Standard ML, OCaml) from specifications in Isabelle. In contrast to naive type-based test data generators, the smart generators take the preconditions into account and only generate tests that fulfill the preconditions. The smart generators are constructed by a compiler that reformulates the preconditions as logic programs and analyzes them by an enriched mode inference. From this inference, the compiler can construct the desired generators in the functional programming language. These test data generators are applied to find errors in specifications, as we show in a case study of a hotel key card system.

Abstract. Considerable effort has gone into the techniques of extracting executable code from formal specifications and animating them. We show how to apply these techniques to the large JinjaThreads formalisation. It models a substantial subset of multithreaded Java source and bytecode in Isabelle/HOL and focuses on proofs and modularity whereas code generation was of little concern in its design. Employing Isabelle’s code generation facilities, we obtain a verified Java interpreter that is sufficiently efficient for running small Java programs. To this end, we present refined implementations for common notions such as the reflexive transitive closure and Russell’s definite description operator. From our experience, we distill simple guidelines on how to develop future formalisations with executability in mind. 1