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The algorithmic analysis of hybrid systems

by R. Alur, C. Courcoubetis, N. Halbwachs , T. A. Henzinger, P.-H. Ho, X. Nicollin , A. Olivero , J. Sifakis , S. Yovine - THEORETICAL COMPUTER SCIENCE , 1995
"... We present a general framework for the formal specification and algorithmic analysis of hybrid systems. A hybrid system consists of a discrete program with an analog environment. We model hybrid systems as nite automata equipped with variables that evolve continuously with time according to dynamica ..."
Abstract - Cited by 778 (71 self) - Add to MetaCart
to dynamical laws. For verification purposes, we restrict ourselves to linear hybrid systems, where all variables follow piecewise-linear trajectories. We provide decidability and undecidability results for classes of linear hybrid systems, and we show that standard program-analysis techniques can be adapted

Program Analysis and Specialization for the C Programming Language

by Lars Ole Andersen , 1994
"... Software engineers are faced with a dilemma. They want to write general and wellstructured programs that are flexible and easy to maintain. On the other hand, generality has a price: efficiency. A specialized program solving a particular problem is often significantly faster than a general program. ..."
Abstract - Cited by 629 (0 self) - Add to MetaCart
. However, the development of specialized software is time-consuming, and is likely to exceed the production of today’s programmers. New techniques are required to solve this so-called software crisis. Partial evaluation is a program specialization technique that reconciles the benefits of generality

A comparison of document clustering techniques

by Michael Steinbach, George Karypis, Vipin Kumar - In KDD Workshop on Text Mining , 2000
"... This paper presents the results of an experimental study of some common document clustering techniques: agglomerative hierarchical clustering and K-means. (We used both a “standard” K-means algorithm and a “bisecting ” K-means algorithm.) Our results indicate that the bisecting K-means technique is ..."
Abstract - Cited by 613 (27 self) - Add to MetaCart
This paper presents the results of an experimental study of some common document clustering techniques: agglomerative hierarchical clustering and K-means. (We used both a “standard” K-means algorithm and a “bisecting ” K-means algorithm.) Our results indicate that the bisecting K-means technique

The JPEG still picture compression standard

by Gregory K. Wallace - Communications of the ACM , 1991
"... This paper is a revised version of an article by the same title and author which appeared in the April 1991 issue of Communications of the ACM. For the past few years, a joint ISO/CCITT committee known as JPEG (Joint Photographic Experts Group) has been working to establish the first international c ..."
Abstract - Cited by 1138 (0 self) - Add to MetaCart
compression standard for continuous-tone still images, both grayscale and color. JPEG’s proposed standard aims to be generic, to support a wide variety of applications for continuous-tone images. To meet the differing needs of many applications, the JPEG standard includes two basic compression methods, each

Usability Analysis of Visual Programming Environments: a `cognitive dimensions' framework

by T. R. G. Green, M. Petre - JOURNAL OF VISUAL LANGUAGES AND COMPUTING , 1996
"... The cognitive dimensions framework is a broad-brush evaluation technique for interactive devices and for non-interactive notations. It sets out a small vocabulary of terms designed to capture the cognitively-relevant aspects of structure, and shows how they can be traded off against each other. T ..."
Abstract - Cited by 514 (13 self) - Add to MetaCart
. The purpose of this paper is to propose the framework as an evaluation technique for visual programming environments. We apply it to two commercially-available dataflow languages (with further examples from other systems) and conclude that it is effective and insightful; other HCI-based evaluation

Pin: building customized program analysis tools with dynamic instrumentation

by Chi-keung Luk, Robert Cohn, Robert Muth, Harish Patil, Artur Klauser, Geoff Lowney, Steven Wallace, Vijay Janapa Reddi, Kim Hazelwood - IN PLDI ’05: PROCEEDINGS OF THE 2005 ACM SIGPLAN CONFERENCE ON PROGRAMMING LANGUAGE DESIGN AND IMPLEMENTATION , 2005
"... Robust and powerful software instrumentation tools are essential for program analysis tasks such as profiling, performance evaluation, and bug detection. To meet this need, we have developed a new instrumentation system called Pin. Our goals are to provide easy-to-use, portable, transparent, and eff ..."
Abstract - Cited by 991 (35 self) - Add to MetaCart
Robust and powerful software instrumentation tools are essential for program analysis tasks such as profiling, performance evaluation, and bug detection. To meet this need, we have developed a new instrumentation system called Pin. Our goals are to provide easy-to-use, portable, transparent

Comparison of Broadcasting Techniques for Mobile Ad Hoc Networks

by Brad Williams, Tracy Camp - MOBIHOC'02 , 2002
"... Network wide broadcasting in Mobile Ad Hoc Networks provides important control and route establishment functionality for a number of unicast and multicast protocols. Considering its wide use as a building block for other network layer protocols, the MANET community needs to standardize a single meth ..."
Abstract - Cited by 519 (4 self) - Add to MetaCart
Network wide broadcasting in Mobile Ad Hoc Networks provides important control and route establishment functionality for a number of unicast and multicast protocols. Considering its wide use as a building block for other network layer protocols, the MANET community needs to standardize a single

Thumbs up? Sentiment Classification using Machine Learning Techniques

by Bo Pang, Lillian Lee, Shivakumar Vaithyanathan - IN PROCEEDINGS OF EMNLP , 2002
"... We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, we find that standard machine learning techniques definitively outperform human-produced baselines. However, the three mac ..."
Abstract - Cited by 1101 (7 self) - Add to MetaCart
We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, we find that standard machine learning techniques definitively outperform human-produced baselines. However, the three

DART: Directed automated random testing

by Patrice Godefroid, Nils Klarlund, Koushik Sen - In Programming Language Design and Implementation (PLDI , 2005
"... We present a new tool, named DART, for automatically testing software that combines three main techniques: (1) automated extraction of the interface of a program with its external environment using static source-code parsing; (2) automatic generation of a test driver for this interface that performs ..."
Abstract - Cited by 843 (42 self) - Add to MetaCart
techniques constitute Directed Automated Random Testing,or DART for short. The main strength of DART is thus that testing can be performed completely automatically on any program that compiles – there is no need to write any test driver or harness code. During testing, DART detects standard errors

Data cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-totals

by Jim Gray, Adam Bosworth, Andrew Layman, Don Reichart, Hamid Pirahesh , 1996
"... Abstract. Data analysis applications typically aggregate data across many dimensions looking for anomalies or unusual patterns. The SQL aggregate functions and the GROUP BY operator produce zero-dimensional or one-dimensional aggregates. Applications need the N-dimensional generalization of these op ..."
Abstract - Cited by 860 (11 self) - Add to MetaCart
in more complex non-procedural data analysis programs. The cube operator treats each of the N aggregation attributes as a dimension of N-space. The aggregate of a particular set of attribute values is a point in this space. The set of points forms an N-dimensional cube. Super-aggregates are computed
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