Dynamic data race detection is a program analysis technique for detecting errors provoked by undesired interleavings of concurrent threads. A primary challenge when designing efficient race detection algorithms is to achieve manageable space requirements. State of the art algorithms

The application of volume rendering techniques to the display of surfaces from sampled scalar functions of three spatial dimensions is explored. Fitting of geometric primitives to the sampled data is not required. Images are formed by directly shading each sample and projecting it onto

A highly efficient recursive algorithm for edge detection is presented. Using Canny's design [1], we show that a solution to his precise formulation of detection and localization for an infinite extent filter leads to an optimal operator in one dimension, which can be efficiently implemented

We present a new method for dynamically detecting potential data races in multithreaded programs. Our method improves on the state of the art in accuracy, in usability, and in overhead. We improve accuracy by combining two previously known race detection techniques — lockset-based detection

Ensuring the correctness of multithreaded programs is difficult, due to the potential for unexpected and nondeterministic interactions between threads. Previous work addressed this problem by devising tools for detecting race conditions, a situation where two threads simultaneously access the same

was what preceded the mask more similar graphically? To which of two probe words was it more similar semantically? As word-mask stimulus onset asynchrony (SOA) was re-duced, subjects reached chance performance on the detection, graphic, and semantic decisions in that order. In Experiment 2, subjects again

ideas from both Lipton’s theory of reduction and earlier dynamic race detectors such as Eraser. Experimental results demonstrate that this dynamic atomicity analysis is effective for detecting errors due to unintended interactions between threads. In addition, the majority of methods in our benchmarks

Abstract Race detection algorithms for multi-threaded programs using thecommon lock-based synchronization idiom must correlate locks with the memory locations they guard. The heart of a proof ofrace freedom is showing that if two locks are distinct, then the memory locations they guard are also

This article presents a static race-detection analysis for multithreaded shared-memory programs, focusing on the Java programming language. The analysis is based on a type system that captures many common synchronization patterns. It supports classes with internal synchronization, classes

distinct cortical areas associated with each of these specific executive processes. Two cortical systems, one involving right prefrontal and parietal areas and the second regions of the cingulate, underlay inhibitory control. The involvement of these two systems was predicated upon the difficulty