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Property testing : current research and surveys / Oded Goldreich (ed.).

By: Contributor(s): Material type: TextTextSeries: Lecture notes in computer science ; 6390. | Lecture notes in computer science. State-of-the-art survey. | LNCS sublibrary. SL 1, Theoretical computer science and general issues.Publication details: Berlin : Springer, 2010.Description: 1 online resource (xi, 358 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642163678
  • 364216367X
Subject(s): Genre/Form: Additional physical formats: Print version:: Property Testing.DDC classification:
  • 004 22
LOC classification:
  • QA76
Online resources:
Contents:
Editor's intruduction -- Surveys -- Extended abstracts.
Summary: 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. This state-of-the-art survey presents a collection of extended abstracts and surveys of leading researchers in property testing and related areas; it reflects the program of a mini-workshop on property testing that took place in January 2010 at the Institute for Computer Science (ITCS), Tsinghua University, Beijing, China. The volume contains two editor's introductions, 10 survey papers and 18 extended abstracts.
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" ... a mini-workshop on property testing that took place in January 2010 in the Institute for Computer Science (ITCS) at Tsinghua University (Beijing)"--Preface

Includes bibliographical references and index.

Print version record.

Editor's intruduction -- Surveys -- Extended abstracts.

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. This state-of-the-art survey presents a collection of extended abstracts and surveys of leading researchers in property testing and related areas; it reflects the program of a mini-workshop on property testing that took place in January 2010 at the Institute for Computer Science (ITCS), Tsinghua University, Beijing, China. The volume contains two editor's introductions, 10 survey papers and 18 extended abstracts.

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