this paper we reconsider the foundations of modal logic, following MartinL of's methodology of distinguishing judgments from propositions [ML85]. We give constructive meaning explanations for necessity (2) and possibility (3). This exercise yields a simple and uniform system of natural deduction for intuitionistic modal logic which does not exhibit anomalies found in other proposals. We also give a new presentation of lax logic [FM97] and find that it is already contained in modal logic, using the decomposition of the lax modality fl A as

How canweintegrate interaction into a purely declarative language? This tutorial describes a solution to this problem based on a monad. The solution has been implemented in the functional language Haskell and the declarative language Escher. Comparisons are given to other approaches to interaction based on synchronous streams, continuations, linear logic, and side effects.

this paper is to marry effects to monads, writing T for a computation that yields a value in and may have effects delimited by oe. Now we have that ( is

Our results formalize and confirm a folklore theorem about traditional bindingtime analysis, namely that CPS has a positive effect on binding times. What may be more surprising is that the benefit does not arise from a standard refinement of program analysis, as, for instance, duplicating continuations.

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Higher-order program transformations raise new challenges for proving properties of their output, since they resist traditional, rst-order proof techniques. In this work, we consider (1) the \one-pass" continuationpassing style (CPS) transformation, which is second-order, and (2) the occurrences of parameters of continuations in its output. To this end, we specify the one-pass CPS transformation relationally and we use the proof technique of logical relations.

One of the flagship applications of partial evaluation is compilation and compiler generation. However, partial evaluation is usually expressed as a source-to-source transformation for high-level languages, whereas realistic compilers produce object code. We close this gap by composing a partial evaluator with a compiler by automatic means. Our work is a successful application of several meta-computation techniques to build the system, both in theory and in practice. The composition is an application of deforestation or fusion. The result is a run-time code generation system built from existing components. Its applications are numerous. For example, it allows the language designer to perform interpreter-based experiments with a source-to-source version of the partial evaluator before building a realistic compiler which generates object code automatically.

The shift and reset operators, proposed by Danvy and Filinski, are powerful control primitives for capturing delimited continuations. Delimited continuation is a similar concept as the standard (unlimited) continuation, but it represents part of the rest of the computation, rather than the whole rest of computation. In the literature, the semantics of shift and reset has been given by a CPS-translation only. This paper gives a direct axiomatization of calculus with shift and reset, namely, we introduce a set of equations, and prove that it is sound and complete with respect to the CPS-translation. We also introduce a calculus with control operators which is as expressive as the calculus with shift and reset, has a sound and complete axiomatization, and is conservative over Sabry and Felleisen's theory for first-class continuations.

As probabilistic computations play an increasing role in solving various problems, researchers have designed probabilistic languages which treat probability distributions as primitive datatypes. Most probabilistic languages, however, focus only on discrete distributions and have limited expressive power. This paper presents a probabilistic language, called λ○, whose expressive power is beyond discrete distributions. Rich expressiveness of λ ○ is due to its use of sampling functions, i.e., mappings from the unit interval (0.0, 1.0] to probability domains, in specifying probability distributions. As such, λ ○ enables programmers to formally express and reason about sampling methods developed in simulation theory. The use of λ ○ is demonstrated with three applications in robotics: robot localization, people tracking, and robotic mapping. All experiments have been carried out with real robots.