6,782 research outputs found
Logical Step-Indexed Logical Relations
Appel and McAllester's "step-indexed" logical relations have proven to be a
simple and effective technique for reasoning about programs in languages with
semantically interesting types, such as general recursive types and general
reference types. However, proofs using step-indexed models typically involve
tedious, error-prone, and proof-obscuring step-index arithmetic, so it is
important to develop clean, high-level, equational proof principles that avoid
mention of step indices. In this paper, we show how to reason about binary
step-indexed logical relations in an abstract and elegant way. Specifically, we
define a logic LSLR, which is inspired by Plotkin and Abadi's logic for
parametricity, but also supports recursively defined relations by means of the
modal "later" operator from Appel, Melli\`es, Richards, and Vouillon's "very
modal model" paper. We encode in LSLR a logical relation for reasoning
relationally about programs in call-by-value System F extended with general
recursive types. Using this logical relation, we derive a set of useful rules
with which we can prove contextual equivalence and approximation results
without counting steps
CHR Grammars
A grammar formalism based upon CHR is proposed analogously to the way
Definite Clause Grammars are defined and implemented on top of Prolog. These
grammars execute as robust bottom-up parsers with an inherent treatment of
ambiguity and a high flexibility to model various linguistic phenomena. The
formalism extends previous logic programming based grammars with a form of
context-sensitive rules and the possibility to include extra-grammatical
hypotheses in both head and body of grammar rules. Among the applications are
straightforward implementations of Assumption Grammars and abduction under
integrity constraints for language analysis. CHR grammars appear as a powerful
tool for specification and implementation of language processors and may be
proposed as a new standard for bottom-up grammars in logic programming.
To appear in Theory and Practice of Logic Programming (TPLP), 2005Comment: 36 pp. To appear in TPLP, 200
An Effect System for Algebraic Effects and Handlers
We present an effect system for core Eff, a simplified variant of Eff, which
is an ML-style programming language with first-class algebraic effects and
handlers. We define an expressive effect system and prove safety of operational
semantics with respect to it. Then we give a domain-theoretic denotational
semantics of core Eff, using Pitts's theory of minimal invariant relations, and
prove it adequate. We use this fact to develop tools for finding useful
contextual equivalences, including an induction principle. To demonstrate their
usefulness, we use these tools to derive the usual equations for mutable state,
including a general commutativity law for computations using non-interfering
references. We have formalized the effect system, the operational semantics,
and the safety theorem in Twelf
Continuous Improvement Through Knowledge-Guided Analysis in Experience Feedback
Continuous improvement in industrial processes is increasingly a key element of competitiveness for industrial systems. The management of experience feedback in this framework is designed to build, analyze and facilitate the knowledge sharing among problem solving practitioners of an organization in order to improve processes and products achievement. During Problem Solving Processes, the intellectual investment of experts is often considerable and the opportunities for expert knowledge exploitation are numerous: decision making, problem solving under uncertainty, and expert configuration. In this paper, our contribution relates to the structuring of a cognitive experience feedback framework, which allows a flexible exploitation of expert knowledge during Problem Solving Processes and a reuse such collected experience. To that purpose, the proposed approach uses the general principles of root cause analysis for identifying the root causes of problems or events, the conceptual graphs formalism for the semantic conceptualization of the domain vocabulary and the Transferable Belief Model for the fusion of information from different sources. The underlying formal reasoning mechanisms (logic-based semantics) in conceptual graphs enable intelligent information retrieval for the effective exploitation of lessons learned from past projects. An example will illustrate the application of the proposed approach of experience feedback processes formalization in the transport industry sector
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