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Section: Partnerships and Cooperations

International Initiatives

Inria Associate Teams

RAPT

Participants : Beniamino Accattoli, Kaustuv Chaudhuri, Quentin Heath, Dale Miller, Yuting Wang.

  • Title: Applying Recent Advances in Proof Theory for Specification and Reasoning

  • Inria principal investigator: Kaustuv Chaudhuri

  • International Partner:

    • Institution: McGill University (Canada)

    • Laboratory: School of Computer Science

    • Researcher: Prof. Brigitte Pientka

  • International Partner:

    • Institution: Carnegie Mellon University (United States)

    • Laboratory: Department of Computer Science

    • Researcher: Prof. Frank Pfenning

  • International Partner:

    • Institution: University of Minnesota (United States)

    • Laboratory: Department of Computer Science and Engineering

    • Researcher: Prof. Gopalan Nadathur

  • Duration: 2011 - 2013

  • See also: http://www.lix.polytechnique.fr/~kaustuv/rapt/

  • Many aspects of computation systems, ranging from operational semantics, interaction, and various forms of static analysis, are commonly specified using inference rules, which themselves are formalized as theories in a logical framework. While such a use of logic can yield sophisticated, compact, and elegant specifications, formal reasoning about these logic specifications presents a number of difficulties. The RAPT project will address the problem of reasoning about logic specifications by bringing together three different research teams, combining their backgrounds in type theory, proof theory, and the building of computational logic systems. We plan to develop new methods for specifying computation that allow for a range of specification logics (eg, intuitionistic, linear, ordered) as well as new means to reason inductively and co-inductively with such specifications. New implementations of reasoning systems are planned that use interactive techniques for deep meta-theoretic reasoning and fully automated procedures for a range of useful theorems.

Inria International Partners

Eternal: Inria ARC

Participants : Kaustuv Chaudhuri, Dale Miller, Lutz Straßburger.

  • Title: Interactive Resource Analysis

  • webpage: http://eternal.cs.unibo.it/

  • Inria principal investigator: Dale Miller

  • Inria Partner:

    • Institution: Inria

    • Team: FOCUS

    • Researcher: Ugo Dal Lago

  • Inria Partner:

    • Institution: Inria

    • Team: pi.r2

    • Researcher: Pierre-Louis Curien

  • Duration: 2011 - 2013

  • This project aims at putting together ideas from Implicit Computational Complexity and Interactive Theorem Proving, in order to develop new methodologies for handling quantitative properties related to program resource consumption, like execution time and space. The task of verifying and certifying quantitative properties is undecidable as soon as the considered programming language gets close to a general purpose language. So, full-automatic techniques in general cannot help in classifying programs in a precise way with respect to the amount of resources used and moreover in several cases the programmer will not gain any relevant information on his programs. In particular, this is the case for all the techniques based on the study of structural constraints on the shape of programs, like many of those actually proposed in the field of implicit computational complexity. To overcome these limitations, we aim at combining the ideas developed in the linear logic approach to implicit computational complexity with the ones of interactive theorem proving, getting rid of the intrinsic limitations of the automatic techniques. In the obtained framework, undecidability will be handled through the system's user, who is asked not only to write the code, but also to drive the semi-automatic system in finding a proof for the quantitative properties of interest. In order to reduce the user effort and allow him to focus only on the critical points of the analysis, our framework will integrate implicit computational complexity techniques as automatic decision procedures for particular scenarios. Moreover, in order to be widely applicable, the modularity of the framework will permit to deal with programs written in different languages and to consider different computational resources. The kind of study proposed by this project has been almost neglected so far. Here, we aim at providing such a framework for both theoretic investigations and for testing in practice the effectiveness of the approach.