13,733 research outputs found
The Derivation of Compositional Programs
This paper proposes a parallel programming notation and a method of reasoning about programs with the following characteristics: (1) Parallel Composition The notation provides different forms of interfaces between processes; the more restrictive the interface, the simpler the proofs of process composition. A flexible interface is that of cooperating processes with a shared address space; proofs of programs that use this interface are based on non-interference [OG76] and temporal logic [Pnu81,CM88, Lam9l]. We also propose more restrictive interfaces and specifications that allow us to use the following specificattion rule: the strongest specification of a parallel composition of processes is the conjunction of the strongest specifications of its components. This rule is helpful in deriving parallel programs. (2) Determinism A process that does not use certain primitives of the notation is guaranteed to be deterministic. Programmers who wish to prove that their programs are deterministic are relieved of this proof obligation if they restrict their programs to a certain subset of the primitives
A compositional Semantics for CHR
Constraint Handling Rules (CHR) are a committed-choice declarative language
which has been designed for writing constraint solvers. A CHR program consists
of multi-headed guarded rules which allow one to rewrite constraints into
simpler ones until a solved form is reached.
CHR has received a considerable attention, both from the practical and from
the theoretical side. Nevertheless, due the use of multi-headed clauses, there
are several aspects of the CHR semantics which have not been clarified yet. In
particular, no compositional semantics for CHR has been defined so far.
In this paper we introduce a fix-point semantics which characterizes the
input/output behavior of a CHR program and which is and-compositional, that is,
which allows to retrieve the semantics of a conjunctive query from the
semantics of its components. Such a semantics can be used as a basis to define
incremental and modular analysis and verification tools
Semantics of Input-Consuming Logic Programs
Input-consuming programs are logic programs with an additional restriction on the selectability (actually, on the resolvability) of atoms. this class of programs arguably allows to model logic programs employing a dynamic selection rule and constructs such as delay declarations: as shown also in [5], a large number of them are actually input-consuming. \ud
in this paper we show that - under some syntactic restrictions - the tex2html_wrap_inline117-semantics of a program is correct and fully abstract also for input-consuming programs. this allows us to conclude that for a large class of programs employing delay declarations there exists a model-theoretic semantics which is equivalent to the operational one
(Co-)Inductive semantics for Constraint Handling Rules
In this paper, we address the problem of defining a fixpoint semantics for
Constraint Handling Rules (CHR) that captures the behavior of both
simplification and propagation rules in a sound and complete way with respect
to their declarative semantics. Firstly, we show that the logical reading of
states with respect to a set of simplification rules can be characterized by a
least fixpoint over the transition system generated by the abstract operational
semantics of CHR. Similarly, we demonstrate that the logical reading of states
with respect to a set of propagation rules can be characterized by a greatest
fixpoint. Then, in order to take advantage of both types of rules without
losing fixpoint characterization, we present an operational semantics with
persistent. We finally establish that this semantics can be characterized by
two nested fixpoints, and we show the resulting language is an elegant
framework to program using coinductive reasoning.Comment: 17 page
Bialgebraic Semantics for Logic Programming
Bialgebrae provide an abstract framework encompassing the semantics of
different kinds of computational models. In this paper we propose a bialgebraic
approach to the semantics of logic programming. Our methodology is to study
logic programs as reactive systems and exploit abstract techniques developed in
that setting. First we use saturation to model the operational semantics of
logic programs as coalgebrae on presheaves. Then, we make explicit the
underlying algebraic structure by using bialgebrae on presheaves. The resulting
semantics turns out to be compositional with respect to conjunction and term
substitution. Also, it encodes a parallel model of computation, whose soundness
is guaranteed by a built-in notion of synchronisation between different
threads
On the Relation of Interaction Semantics to Continuations and Defunctionalization
In game semantics and related approaches to programming language semantics,
programs are modelled by interaction dialogues. Such models have recently been
used in the design of new compilation methods, e.g. for hardware synthesis or
for programming with sublinear space. This paper relates such semantically
motivated non-standard compilation methods to more standard techniques in the
compilation of functional programming languages, namely continuation passing
and defunctionalization. We first show for the linear {\lambda}-calculus that
interpretation in a model of computation by interaction can be described as a
call-by-name CPS-translation followed by a defunctionalization procedure that
takes into account control-flow information. We then establish a relation
between these two compilation methods for the simply-typed {\lambda}-calculus
and end by considering recursion
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Deriving real-time action systems with multiple time bands using algebraic reasoning
The verify-while-develop paradigm allows one to incrementally develop programs from their specifications using a series of calculations against the remaining proof obligations. This paper presents a derivation method for real-time systems with realistic constraints on their behaviour. We develop a high-level interval-based logic that provides flexibility in an implementation, yet allows algebraic reasoning over multiple granularities and sampling multiple sensors with delay. The semantics of an action system is given in terms of interval predicates and algebraic operators to unify the logics for an action system and its properties, which in turn simplifies the calculations and derivations
Naturalizing a Programming Language via Interactive Learning
Our goal is to create a convenient natural language interface for performing
well-specified but complex actions such as analyzing data, manipulating text,
and querying databases. However, existing natural language interfaces for such
tasks are quite primitive compared to the power one wields with a programming
language. To bridge this gap, we start with a core programming language and
allow users to "naturalize" the core language incrementally by defining
alternative, more natural syntax and increasingly complex concepts in terms of
compositions of simpler ones. In a voxel world, we show that a community of
users can simultaneously teach a common system a diverse language and use it to
build hundreds of complex voxel structures. Over the course of three days,
these users went from using only the core language to using the naturalized
language in 85.9\% of the last 10K utterances.Comment: 10 pages, ACL201
Bounded Expectations: Resource Analysis for Probabilistic Programs
This paper presents a new static analysis for deriving upper bounds on the
expected resource consumption of probabilistic programs. The analysis is fully
automatic and derives symbolic bounds that are multivariate polynomials of the
inputs. The new technique combines manual state-of-the-art reasoning techniques
for probabilistic programs with an effective method for automatic
resource-bound analysis of deterministic programs. It can be seen as both, an
extension of automatic amortized resource analysis (AARA) to probabilistic
programs and an automation of manual reasoning for probabilistic programs that
is based on weakest preconditions. As a result, bound inference can be reduced
to off-the-shelf LP solving in many cases and automatically-derived bounds can
be interactively extended with standard program logics if the automation fails.
Building on existing work, the soundness of the analysis is proved with respect
to an operational semantics that is based on Markov decision processes. The
effectiveness of the technique is demonstrated with a prototype implementation
that is used to automatically analyze 39 challenging probabilistic programs and
randomized algorithms. Experimental results indicate that the derived constant
factors in the bounds are very precise and even optimal for many programs
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