Skip to product information
1 of 1
Regular price £59.67 GBP
Regular price £78.99 GBP Sale price £59.67 GBP
Sale Sold out
Free UK Shipping

Freshly Printed - allow 6 days lead

Introduction to Property Testing

An extensive and authoritative introduction to property testing, the study of super-fast algorithms for analyzing large quantities of data.

Oded Goldreich (Author)

9781107194052, Cambridge University Press

Hardback, published 23 November 2017

468 pages
25.9 x 18.2 x 3 cm, 0.99 kg

'Overall, the book is an excellent and comprehensive read. The range of topics discussed in this book is sufficient to attract many students to use it as reference. It can definitely be used as a reference to an advanced undergraduate level course or a beginning graduate level course.' Sarvagya Upadhyay, SIGACT News

Property testing is concerned with the design of super-fast algorithms for the structural analysis of large quantities of data. The aim is to unveil global features of the data, such as determining whether the data has a particular property or estimating global parameters. Remarkably, it is possible for decisions to be made by accessing only a small portion of the data. Property testing focuses on properties and parameters that go beyond simple statistics. This book provides an extensive and authoritative introduction to property testing. It provides a wide range of algorithmic techniques for the design and analysis of tests for algebraic properties, properties of Boolean functions, graph properties, and properties of distributions.

1. The main themes
2. Testing lineriality
3. Low degree tests
4. Testing monotonicity
5. Testing dictatorships, juntas, and monomials
6. Testing by implicit sampling
7. Lower bounds techniques
8. Testing graph properties in the dense graph model
9. Testing graph properties in the bounded-degree graph model
10. Testing graph properties in the general graph model
11. Testing properties of distributions
12. Ramifications and related topics
13. Locally testable codes and proofs.

Subject Areas: Algorithms & data structures [UMB]

View full details