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Section: Application Domains

Automated theorem proving

Automated theorem proving has traditionally focused on classical first-order logic, but non-classical logics are increasingly becoming important in the specification and analysis of software. Most type systems are based on (possibly second-order) propositional intuitionistic logic, for example, while resource-sensitive and concurrent systems are most naturally expressed in linear logic.

The members of the Parsifal team have a strong expertise in the design and implementation of performant automated reasoning systems for such non-classical logics. In particular, the Linprover suite of provers  [34] continue to be the fastest automated theorem provers for propositional and first-order linear logic.

Any non-trivial specification, of course, will involve theorems that are simply too complicated to prove automatically. It is therefore important to design semi-automated systems that allow the user to give high level guidance, while at the same time not having to write every detail of the formal proofs. High level proof languages in fact serve a dual function – they are more readily comprehended by human readers, and they tend to be more robust with respect to maintenance and continued evolution of the systems. Members of the Parsifal team, in association with other INRIA teams and Microsoft Research, have been building a heterogeneous semi-automatic proof system for verifying distributed algorithms  [36] .

On a more foundational level, the team has been developing many new insights into the structure of proofs and the proof search spaces. Two directions, in particular, present tantalizing possibilities:

  • The concept of multi-focusing  [37] can be used to expose concurrency in computational behavior, which can in turn be exploited to prune areas of the proof search space that explore irrelevant interleavings of concurrent actions.

  • The use of bounded search, where the bounds can be shown to be complete by meta-theoretic analysis, can be used to circumvent much of the non-determinism inherent in resource-sensitive logics such as linear logic. The lack of proofs of a certain bound can then be used to justify the presence or absence of properties of the encoded computations.

Much of the theoretical work on automated reasoning has been motivated by examples and implementations, and the Parsifal team intends to continue to devote significant effort in these directions.