Property Testing Current Research and Surveys
Property Testing is the study of super-fast (randomized) algorithms for approximate decision making. These algorithms are given direct access to items of a huge data set, and determine, whether this data set has some predetermined (global) property or is
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Editorial Board David Hutchison Lancaster University, UK Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M. Kleinberg Cornell University, Ithaca, NY, USA Alfred Kobsa University of California, Irvine, CA, USA Friedemann Mattern ETH Zurich, Switzerland John C. Mitchell Stanford University, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel Oscar Nierstrasz University of Bern, Switzerland C. Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen TU Dortmund University, Germany Madhu Sudan Microsoft Research, Cambridge, MA, USA Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Gerhard Weikum Max Planck Institute for Informatics, Saarbruecken, Germany
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Oded Goldreich (Ed.)
Property Testing Current Research and Surveys
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Volume Editor Oded Goldreich Weizmann Institute of Science Faculty of Mathematics and Computer Science 76100 Rehovot, Israel E-mail: [email protected]
Library of Congress Control Number: 2010936638 CR Subject Classification (1998): F.2, I.2, F.1, I.3.5, H.3, G.2 LNCS Sublibrary: SL 1 – Theoretical Computer Science and General Issues ISSN ISBN-10 ISBN-13
0302-9743 3-642-16366-1 Springer Berlin Heidelberg New York 978-3-642-16366-1 Springer Berlin Heidelberg New York
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Preface
Property testing is the study of super-fast (randomized) algorithms for approximate decision making. These algorithms are given direct access to items of a huge data set, and determine whether this data set has some predetermined (global) property or is far from having this property. Remarkably, this approximate decision is made by accessing a small portion of the data set. Property testing has been a subject of intensive research in the last couple of decades, with hundreds of studies conducted in it and in closely related areas. Indeed, property testing is closely related to probabilistically checkable proofs (PCPs), and is related to coding theory, combinatorics, statistics, computational learning theory, computational geometry, and more. The current volume provides a taste of the area of property testing. It grew out of a mini-workshop on property
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