Ambiguity resolution is a central problem in language comprehension. Lexical and syntactic ambiguities are standardly assumed to involve different types of knowledge representations and be resolved by different mechanisms. An alternative account is provided in which both types of ambiguity derive

interest in applying model checking to software. For infinite-state systems like software, abstraction is even more critical. Techniques for abstracting software are a prerequisite to making software model checking a reality. We present the first algorithm to automatically construct a predicate abstraction

We present a new approach to proving type soundness for Hindley/Milner-style polymorphic type systems. The keys to our approach are (1) an adaptation of subject reduction theorems from combinatory logic to programming languages, and (2) the use of rewriting techniques for the specification

The model of abstract interpretation of programs developed by Cousot and Cousot [2nd ISOP, 1976], Cousot and Cousot [POPL 1977] and Cousot [PhD thesis 1978] is applied to the static determination of linear equality or inequality invariant relations among numerical variables of programs.

This paper proposes a new theory of the relationship between the sentence processing mechanism and the available computational resources. This theory -- the Syntactic Prediction Locality Theory (SPLT) -- has two components: an integration cost component and a component for the memory cost

We present a new symbolic execution tool, KLEE, capable of automatically generating tests that achieve high coverage on a diverse set of complex and environmentally-intensive programs. We used KLEE to thoroughly check all 89 stand-alone programs in the GNU COREUTILS utility suite, which form

are given, and a tentative implementation !s described Alternative structures for programs are shown, and a possible initial phase for an automatic or semiautomatic program manipulation system is lndmated KEY WORDS AND PHRASES program transformation, program mampulatlon, optimization, recursion CR

We present an automatic iterative abstraction-refinement methodology in which the initial abstract model is generated by an automatic analysis of the control structures in the program to be verified. Abstract models may admit erroneous (or "spurious") counterexamples. We devise new

is automatic and unsupervised in both training and application: senses are induced from a corpus without labeled training insta,nces or other external knowledge sources. The paper demonstrates good performance of context-group discrimination for a sample of natural and artificial ambiguous words

We present a system for identifying the semantic relationships, or semantic roles, filled by constituents of a sentence within a semantic frame. Various lexical and syntactic features are derived from parse trees and used to derive statistical classifiers from hand-annotated training data. 1