Computational experiments on algorithms can supplement theoretical analysis by showing what algorithms, implementations and speed-up methods work best for specific machines or problems. This book guides the reader through the nuts and bolts of the major experimental questions: What should I measure? What inputs should I test? How do I analyze the data? To answer these questions the book draws on ideas from algorithm design and analysis, computer systems, and statistics and data analysis. The wide-ranging discussion includes a tutorial on system clocks and CPU timers, a survey of strategies for tuning algorithms and data structures, a cookbook of methods for generating random combinatorial inputs, and a demonstration of variance reduction techniques. The book can be used by anyone who has taken a course or two in data structures and algorithms. A companion website, AlgLab (www.cs.amherst.edu/alglab) contains downloadable files, programs and tools for use in experimental projects.Read more
- Covers a wide variety of topics from diverse areas: algorithmics, data analysis, architectures and operating systems, with all necessary background
- Includes tutorial discussions with lots of case studies to illustrate concepts
- Lets readers get started producing high-quality and reliable results
Reviews & endorsements
'Catherine McGeoch is one of the founders of the field of experimental algorithmics, helping to initiate the discipline with her 1986 dissertation, 'Experimental Analysis of Algorithms'. She has been deeply involved with the development of the methodology of experimental algorithmics over the past 25 years … This book contains a breadth of advice, examples, and anecdotes, benefiting from her wealth of experience and many collaborations with other innovators in the discipline … Her advice is practical, authoritative, thoughtful, and applicable to the entire range of algorithm design, development, testing, and improvement … McGeoch's book presents a delightful dance of theoretical and experimental endeavors that in concert provide deep understanding of the algorithms that enable our information age as well as the means to the continual improvement of those fundamental algorithms.' Richard Snodgrass, University of ArizonaSee more reviews
'This book provides guidelines and suggestions for performing experimental algorithmic analysis. It contains many examples and includes links to a companion website with code for some specific experiments … The book is a good read with generally good examples, and is short enough to be easily digested.' Jeffrey Putnam, Computing Reviews
Not yet reviewed
Be the first to review
Review was not posted due to profanity×
- Date Published: June 2012
- format: Adobe eBook Reader
- isbn: 9781139211086
- contains: 78 b/w illus.
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
2. A plan of attack
3. What to measure
4. Tuning algorithms, tuning code
5. The toolbox
6. Creating analysis-friendly data
7. Data analysis.
Sorry, this resource is locked