scholarly journals Syntax and operational semantics of a probabilistic programming language with scopes

2016 ◽  
Vol 74 ◽  
pp. 46-57 ◽  
Author(s):  
Peter D. Bruza
Keyword(s):  
Programming Language ◽  
Operational Semantics ◽  
Probabilistic Programming

scholarly journals From Interpreter to Logic Engine by Defunctionalization

2003 ◽  
Vol 10 (25) ◽  
Author(s):  
Dariusz Biernacki ◽  
Olivier Danvy
Keyword(s):  
Logic Programming ◽  
Programming Language ◽  
Operational Semantics ◽  
Lambda Calculus ◽  
Transition System ◽  
Abstract Machine ◽  
Logic Programming Language ◽  
Delimited Continuations ◽  
Simple Logic ◽  
Control Operators

Starting from a continuation-based interpreter for a simple logic programming language, propositional Prolog with cut, we derive the corresponding logic engine in the form of an abstract machine. The derivation originates in previous work (our article at PPDP 2003) where it was applied to the lambda-calculus. The key transformation here is Reynolds's defunctionalization that transforms a tail-recursive, continuation-passing interpreter into a transition system, i.e., an abstract machine. Similar denotational and operational semantics were studied by de Bruin and de Vink in previous work (their article at TAPSOFT 1989), and we compare their study with our derivation. Additionally, we present a direct-style interpreter of propositional Prolog expressed with control operators for delimited continuations.<br /><br />Superseded by BRICS-RS-04-5.

FIRST-CLASS CONTEXTS IN ML

2000 ◽  
Vol 11 (01) ◽  
pp. 65-87
Author(s):  
MASATOMO HASHIMOTO
Keyword(s):  
Programming Language ◽  
Operational Semantics ◽  
Type System ◽  
Type Inference ◽  
Inference Algorithm ◽  
Hole Filling ◽  
Dynamic Binding ◽  
Polymorphic Type ◽  
Open Program ◽  
Program Modules

This paper develops an ML-style programming language with first-class contexts i.e. expressions with holes. The crucial operation for contexts is hole-filling. Filling a hole with an expression has the effect of dynamic binding or macro expansion which provides the advanced feature of manipulating open program fragments. Such mechanisms are useful in many systems including distributed/mobile programming and program modules. If we can treat a context as a first-class citizen in a programming language, then we can manipulate open program fragments in a flexible and seamless manner. A possibility of such a programming language was shown by the theory of simply typed context calculus developed by Hashimoto and Ohori. This paper extends the simply typed system of the context calculus to an ML-style polymorphic type system, and gives an operational semantics and a sound and complete type inference algorithm.

scholarly journals αCheck: A mechanized metatheory model checker

2017 ◽  
Vol 17 (3) ◽  
pp. 311-352 ◽  
Author(s):  
JAMES CHENEY ◽  
ALBERTO MOMIGLIANO
Keyword(s):  
Programming Language ◽  
Dual Problem ◽  
State Of The Art ◽  
Operational Semantics ◽  
Type Systems ◽  
Model Checker ◽  
Formal Systems ◽  
Current State ◽  
Fully Automatic ◽  
Nominal Logic

AbstractThe problem of mechanically formalizing and proving metatheoretic properties of programming language calculi, type systems, operational semantics, and related formal systems has received considerable attention recently. However, the dual problem of searching for errors in such formalizations has attracted comparatively little attention. In this article, we present αCheck, a bounded model checker for metatheoretic properties of formal systems specified using nominal logic. In contrast to the current state of the art for metatheory verification, our approach is fully automatic, does not require expertise in theorem proving on the part of the user, and produces counterexamples in the case that a flaw is detected. We present two implementations of this technique, one based onnegation-as-failureand one based onnegation elimination, along with experimental results showing that these techniques are fast enough to be used interactively to debug systems as they are developed.

scholarly journals Baby Modula-3 and a theory of objects

1994 ◽  
Vol 4 (2) ◽  
pp. 249-283 ◽  
Author(s):  
Martin Abadi
Keyword(s):  
Programming Language ◽  
Formal Semantics ◽  
Operational Semantics ◽  
Object Oriented ◽  
Denotational Semantics ◽  
Object Oriented Programming ◽  
The Core ◽  
Functional Object ◽  
Oriented Programming Language

AbstractBaby Modula-3 is a small, functional, object-oriented programming language. It is intended as a vehicle for explaining the core of Modula-3 from a biased perspective: Baby Modula-3 includes the main features of Modula-3 related to objects, but not much else. To the theoretician, Baby Modula-3 provides a tractable, concrete example of an object-oriented language, and we use it to study the formal semantics of objects. Baby Modula-3 is defined with a structured operational semantics and with a set of static type rules. A denotational semantics guarantees the soundness of this definition.

scholarly journals Correctness of Sequential Monte Carlo Inference for Probabilistic Programming Languages

2021 ◽  
pp. 404-431
Author(s):  
Daniel Lundén ◽  
Johannes Borgström ◽  
David Broman
Keyword(s):  
Monte Carlo ◽  
Programming Languages ◽  
Sequential Monte Carlo ◽  
Fundamental Problem ◽  
Operational Semantics ◽  
Correctness Proof ◽  
Probabilistic Programming ◽  
Inference Problems ◽  
Large Numbers ◽  
Open Question

AbstractProbabilistic programming is an approach to reasoning under uncertainty by encoding inference problems as programs. In order to solve these inference problems, probabilistic programming languages (PPLs) employ different inference algorithms, such as sequential Monte Carlo (SMC), Markov chain Monte Carlo (MCMC), or variational methods. Existing research on such algorithms mainly concerns their implementation and efficiency, rather than the correctness of the algorithms themselves when applied in the context of expressive PPLs. To remedy this, we give a correctness proof for SMC methods in the context of an expressive PPL calculus, representative of popular PPLs such as WebPPL, Anglican, and Birch. Previous work have studied correctness of MCMC using an operational semantics, and correctness of SMC and MCMC in a denotational setting without term recursion. However, for SMC inference—one of the most commonly used algorithms in PPLs as of today—no formal correctness proof exists in an operational setting. In particular, an open question is if the resample locations in a probabilistic program affects the correctness of SMC. We solve this fundamental problem, and make four novel contributions: (i) we extend an untyped PPL lambda calculus and operational semantics to include explicit resample terms, expressing synchronization points in SMC inference; (ii) we prove, for the first time, that subject to mild restrictions, any placement of the explicit resample terms is valid for a generic form of SMC inference; (iii) as a result of (ii), our calculus benefits from classic results from the SMC literature: a law of large numbers and an unbiased estimate of the model evidence; and (iv) we formalize the bootstrap particle filter for the calculus and discuss how our results can be further extended to other SMC algorithms.

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