Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.

  • Apple
  • Android
  • Windows Phone
  • Android

To get the free app, enter your email address or mobile phone number.

A Guide to Experimental Algorithmics 1st Edition

5 out of 5 stars 1 customer review
ISBN-13: 978-0521173018
ISBN-10: 0521173019
Why is ISBN important?
This bar-code number lets you verify that you're getting exactly the right version or edition of a book. The 13-digit and 10-digit formats both work.
Scan an ISBN with your phone
Use the Amazon App to scan ISBNs and compare prices.
Have one to sell? Sell on Amazon
Buy used On clicking this link, a new layer will be open
$33.94 On clicking this link, a new layer will be open
Buy new On clicking this link, a new layer will be open
$44.35 On clicking this link, a new layer will be open
More Buying Choices
25 New from $37.44 19 Used from $33.94
Free Two-Day Shipping for College Students with Amazon Student Free%20Two-Day%20Shipping%20for%20College%20Students%20with%20Amazon%20Student

$44.35 FREE Shipping. In Stock. Ships from and sold by Amazon.com. Gift-wrap available.
click to open popover

Frequently Bought Together

  • A Guide to Experimental Algorithmics
  • +
  • Introduction to Algorithms, 3rd Edition (MIT Press)
Total price: $110.67
Buy the selected items together

Editorial Reviews


"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. The book provides a structured process for the Design of Experiments (DOE) that is tuned to the peculiarities of experiments on algorithms and programs. The book includes dozens of guidelines (68 in all) drawn from her decades 'in the lab.' These guidelines will save the reader loads of time by making the experimental process itself more efficient. 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 Arizona

"McGeoch (Amherst College) is one of the pioneers in the field. Overall, the book is a desirable companion to algorithm analysis texts, and will greatly benefit the algorithm experimenter community. Recommended."
D. Papamichail, University of Miami for Choice Magazine

"This book provides guidelines and suggestions for performing experimental algorithmic analysis. It contains many examples and includes links to a companion Web site with code for some specific experiments (http://www.cs.amherst.edu/alglab/). The book is a good read with generally good examples, and is short enough to be easily digested."
Jeffrey Putnam, Computing Reviews

"No one is more qualified than Dr. McGeoch to discuss this subject... Overall, this is a very valuable book for every computer scientist's and programmer's bookshelf. It is useful for students and practitioners alike, and is accessible at all levels from serving as an undergraduate supplement to a basic data structures and algorithms course, to its use as the main text in a senior undergraduate to graduate course on the design of real-world algorithms. Even seasoned programmers would benefit from learning the experimental methods given in this book and may gain new insights into analyzing the performance of their algorithmic implementations. As computer architecture continues to increase in complexity with multicore and many-core processors, novel memory subsystems, new accelerators such as Intel Xeon Phi and NVIDIA's graphics processing units (GPUs), and data-intensive computing systems for Big Data problems, the book will become even more valuable for every computer scientist and programmer."
David A. Bader, Georgia Institute of Technology for INFORMS Journal on Computing

Book Description

This is a guidebook for those who want to use computational experiments to support their work in algorithm design and analysis. Numerous case studies and examples show how to apply these concepts. All the necessary concepts in computer architecture and data analysis are covered so that the book can be used by anyone who has taken a course or two in data structures and algorithms.

Interested in the Audiobook Edition?
If you’re the author, publisher, or rights holder of this book, let ACX help you produce the audiobook.Learn more.

Product Details

  • Paperback: 272 pages
  • Publisher: Cambridge University Press; 1 edition (January 30, 2012)
  • Language: English
  • ISBN-10: 0521173019
  • ISBN-13: 978-0521173018
  • Product Dimensions: 6.1 x 0.7 x 9.2 inches
  • Shipping Weight: 1.1 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #1,859,829 in Books (See Top 100 in Books)

Customer Reviews

5 star
4 star
3 star
2 star
1 star
See the customer review
Share your thoughts with other customers

Top Customer Reviews

Format: Paperback Verified Purchase
Excellent reading. This book brings the basics on algorithm experimentation and contains very important tips to perform experiments with rigor. The reading is very easy and the examples and exercises very interesting.
Comment Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback.
Sorry, we failed to record your vote. Please try again
Report abuse

Set up an Amazon Giveaway

A Guide to Experimental Algorithmics
Amazon Giveaway allows you to run promotional giveaways in order to create buzz, reward your audience, and attract new followers and customers. Learn more
This item: A Guide to Experimental Algorithmics