177 research outputs found

    Static Application-Level Race Detection in STM Haskell using Contracts

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    Writing concurrent programs is a hard task, even when using high-level synchronization primitives such as transactional memories together with a functional language with well-controlled side-effects such as Haskell, because the interferences generated by the processes to each other can occur at different levels and in a very subtle way. The problem occurs when a thread leaves or exposes the shared data in an inconsistent state with respect to the application logic or the real meaning of the data. In this paper, we propose to associate contracts to transactions and we define a program transformation that makes it possible to extend static contract checking in the context of STM Haskell. As a result, we are able to check statically that each transaction of a STM Haskell program handles the shared data in a such way that a given consistency property, expressed in the form of a user-defined boolean function, is preserved. This ensures that bad interference will not occur during the execution of the concurrent program.Comment: In Proceedings PLACES 2013, arXiv:1312.2218. [email protected]; [email protected]

    A Symbolic Execution Algorithm for Constraint-Based Testing of Database Programs

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    In so-called constraint-based testing, symbolic execution is a common technique used as a part of the process to generate test data for imperative programs. Databases are ubiquitous in software and testing of programs manipulating databases is thus essential to enhance the reliability of software. This work proposes and evaluates experimentally a symbolic ex- ecution algorithm for constraint-based testing of database programs. First, we describe SimpleDB, a formal language which offers a minimal and well-defined syntax and seman- tics, to model common interaction scenarios between pro- grams and databases. Secondly, we detail the proposed al- gorithm for symbolic execution of SimpleDB models. This algorithm considers a SimpleDB program as a sequence of operations over a set of relational variables, modeling both the database tables and the program variables. By inte- grating this relational model of the program with classical static symbolic execution, the algorithm can generate a set of path constraints for any finite path to test in the control- flow graph of the program. Solutions of these constraints are test inputs for the program, including an initial content for the database. When the program is executed with respect to these inputs, it is guaranteed to follow the path with re- spect to which the constraints were generated. Finally, the algorithm is evaluated experimentally using representative SimpleDB models.Comment: 12 pages - preliminary wor

    Offline Specialisation in Prolog Using a Hand-Written Compiler Generator

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    The so called "cogen approach" to program specialisation, writing a compiler generator instead of a specialiser, has been used with considerable success in partial evaluation of both functional and imperative languages. This paper demonstrates that the "cogen" approach is also applicable to the specialisation of logic programs (called partial deduction when applied to pure logic programs) and leads to effective specialisers. Moreover, using good binding-time annotations, the speed-ups of the specialised programs are comparable to the speed-ups obtained with online specialisers. The paper first develops a generic approach to offline partial deduction and then a specific offline partial deduction method, leading to the offline system LIX for pure logic programs. While this is a usable specialiser by itself, its specialisation strategy is used to develop the "cogen" system LOGEN. Given a program, a specification of what inputs will be static, and an annotation specifying which calls should be unfolded, LOGEN generates a specialised specialiser for the program at hand. Running this specialiser with particular values for the static inputs results in the specialised program. While this requires two steps instead of one, the efficiency of the specialisation process is improved in situations where the same program is specialised multiple times. The paper also presents and evaluates an automatic binding-time analysis that is able to derive the annotations. While the derived annotations are still suboptimal compared to hand-crafted ones, they enable non-expert users to use the LOGEN system in a fully automated way Finally, LOGEN is extended so as to directly support a large part of Prolog's declarative and non-declarative features and so as to be able to perform so called mixline specialisations. In mixline specialisation some unfolding decisions depend on the outcome of tests performed at specialisation time instead of being hardwired into the specialiser

    Anti-Unification of Unordered Goals

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    Anti-unification in logic programming refers to the process of capturing common syntactic structure among given goals, computing a single new goal that is more general called a generalization of the given goals. Finding an arbitrary common generalization for two goals is trivial, but looking for those common generalizations that are either as large as possible (called largest common generalizations) or as specific as possible (called most specific generalizations) is a non-trivial optimization problem, in particular when goals are considered to be unordered sets of atoms. In this work we provide an in-depth study of the problem by defining two different generalization relations. We formulate a characterization of what constitutes a most specific generalization in both settings. While these generalizations can be computed in polynomial time, we show that when the number of variables in the generalization needs to be minimized, the problem becomes NP-hard. We subsequently revisit an abstraction of the largest common generalization when anti-unification is based on injective variable renamings, and prove that it can be computed in polynomially bounded time

    Predicate Anti-unification in (Constraint) Logic Programming

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    The concept of anti-unification refers to the process of determining the most specific generalization (msg) of two or more input program objects. In the domain of logic programming, anti-unification has primarily been investigated for computing msgs of tree-like program structures such as terms, atoms, and goals (the latter typically seen as ordered sequences). In this work, we study the anti-unification of whole predicate definitions. We provide a definition of a predicate generalization that allows to characterize the problem of finding the most specific generalization of two predicates as a (computationally hard) search problem. The complexity stems from the fact that a correspondence needs to be constructed between (1) some of the arguments of each of the predicates, (2) some of the clauses in each of the predicate's definitions, and (3) some of the body atoms in each pair of associated clauses. We propose a working algorithm that simultaneously computes these correspondences in a greedy manner. While our algorithm does not necessarily compute the most specific generalization, we conjecture that it allows to compute, in general, a sufficiently good generalization in an acceptable time

    Towards modular binding-time analysis for first-order Mercury

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    AbstractIn this paper, we describe work in progress on binding-time analysis (BTA) for a first-order subset of Mercury. BTA is the core part of any off-line specialisation system. We formulate BTA by constraint normalisation, enabling the analysis to be performed efficiently and in a modular way.The authors wish to thank Danny De Schreye and Karel De Vlaminck for their continuous interest in this work. They also wish to thank anonymous referees for valuable comments which helped to improve the current paper

    Moulinog:A generator of random student assignments written in prolog

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