488 research outputs found

    Computer-Assisted Program Reasoning Based on a Relational Semantics of Programs

    Full text link
    We present an approach to program reasoning which inserts between a program and its verification conditions an additional layer, the denotation of the program expressed in a declarative form. The program is first translated into its denotation from which subsequently the verification conditions are generated. However, even before (and independently of) any verification attempt, one may investigate the denotation itself to get insight into the "semantic essence" of the program, in particular to see whether the denotation indeed gives reason to believe that the program has the expected behavior. Errors in the program and in the meta-information may thus be detected and fixed prior to actually performing the formal verification. More concretely, following the relational approach to program semantics, we model the effect of a program as a binary relation on program states. A formal calculus is devised to derive from a program a logic formula that describes this relation and is subject for inspection and manipulation. We have implemented this idea in a comprehensive form in the RISC ProgramExplorer, a new program reasoning environment for educational purposes which encompasses the previously developed RISC ProofNavigator as an interactive proving assistant.Comment: In Proceedings THedu'11, arXiv:1202.453

    On Formal Specification of Maple Programs

    Full text link
    This paper is an example-based demonstration of our initial results on the formal specification of programs written in the computer algebra language MiniMaple (a substantial subset of Maple with slight extensions). The main goal of this work is to define a verification framework for MiniMaple. Formal specification of MiniMaple programs is rather complex task as it supports non-standard types of objects, e.g. symbols and unevaluated expressions, and additional functions and predicates, e.g. runtime type tests etc. We have used the specification language to specify various computer algebra concepts respective objects of the Maple package DifferenceDifferential developed at our institute

    Distributed Maple: parallel computer algebra in networked environments

    Get PDF
    AbstractWe describe the design and use of Distributed Maple, an environment for executing parallel computer algebra programs on multiprocessors and heterogeneous clusters. The system embeds kernels of the computer algebra system Maple as computational engines into a networked coordination layer implemented in the programming language Java. On the basis of a comparatively high-level programming model, one may write parallel Maple programs that show good speedups in medium-scaled environments. We report on the use of the system for the parallelization of various functions of the algebraic geometry library CASA and demonstrate how design decisions affect the dynamic behaviour and performance of a parallel application. Numerous experimental results allow comparison of Distributed Maple with other systems for parallel computer algebra

    Coalgebraic Operational Semantics for an Imperative Language

    Get PDF
    Operational semantics is a known and popular semantic method for describing the execution of programs in detail. The traditional definition of this method defines each step of a program as a transition relation. We present a new approach on how to define operational semantics as a coalgebra over a category of configurations. Our approach enables us to deal with a program that is written in a small but real imperative language containing also the common program constructs as input and output statements, and declarations. A coalgebra enables to define operational semantics in a uniform way and it describes the behavior of the programs. The state space of our coalgebra consists of the configurations modeling the actual states; the morphisms in a base category of the coalgebra are the functions defining particular steps during the program's executions. Polynomial endofunctor determines this type of systems. Another advantage of our approach is its easy implementation and graphical representation, which we illustrate on a simple program
    • …
    corecore