Abstract The KeY tool is a state-of-the-art deductive program verifier for the Java language. Its verification engine is based on a sequent calculus for dynamic logic, realizing forward symbolic execution of the target program, whereby all symbolic paths through a program are explored. Method contracts make verification scalable. KeY combines auto-active and fine-grained proof interaction, which is possible both at the level of the verification target and its specification, as well as at the level of proof rules and program logic. This makes KeY well-suited for teaching program verification, but also permits proof debugging at the source code level. The latter made it possible to verify some of the most complex Java code to date. The article provides a self-contained introduction to the working principles and the practical usage of KeY for anyone with basic knowledge in logic and formal methods.

Type systems and modern type checkers can be used very successfully to obtain formal correctness guarantees with little specification overhead. However, type systems in practical scenarios have to trade precision for decidability and scalability. Tools for deductive verification, on the other hand, can prove general properties in more cases than a typical type checker can, but they do not scale well. We present a method to complement the scalability of expressive type systems with the precision of deductive program verification approaches. This is achieved by translating the type uses whose correctness the type checker cannot prove into assertions in a specification language, which can be dealt with by a deductive verification tool. Type uses whose correctness the type checker can prove are instead turned into assumptions to aid the verification tool in finding a proof.Our novel approach is introduced both conceptually for a simple imperative language, and practically by a concrete implementation for the Java programming language. The usefulness and power of our approach has been evaluated by discharging known false positives from a real-world program and by a small case study.