By Catherine C. McGeoch

ISBN-10: 0521173019

ISBN-13: 9780521173018

ISBN-10: 1107001730

ISBN-13: 9781107001732

"Computational experiments on algorithms can complement theoretical research via displaying what algorithms, implementations, and speed-up tools paintings top for particular machines or difficulties. This booklet publications the reader during the nuts and bolts of the key experimental questions: What should still I degree? What inputs may still I attempt? How do I research the information? Answering those questions wishes rules from set of rules design Read more...

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If costs double as n doubles, C(n) is linear. 4. To determine whether C(n) ∈ (n log n), divide each measurement by n and check whether the result C(n)/n increments by a constant. 5. If cost quadruples each time n doubles, C(n) ∈ (n2 ). Similar rules can be worked out for other common function classes; see Sedgewick [22] for details. Doubling experiments are valuable for checking whether basic assumptions about performance are correct. For example, Bentley [5] describes a study of the qsort function implemented in the S statistical package.

If costs double as n doubles, C(n) is linear. 4. To determine whether C(n) ∈ (n log n), divide each measurement by n and check whether the result C(n)/n increments by a constant. 5. If cost quadruples each time n doubles, C(n) ∈ (n2 ). Similar rules can be worked out for other common function classes; see Sedgewick [22] for details. Doubling experiments are valuable for checking whether basic assumptions about performance are correct. For example, Bentley [5] describes a study of the qsort function implemented in the S statistical package.

They have features that are relevant to algorithm performance. • They have provable properties. • They permit controlled experiments using parameterization. 2 Experimental Design Basics 31 • They are typical of real-world application domains. • They display algorithm performance on a good variety of both applied and theoretical scenarios. • They yield insights into underlying algorithm mechanisms. Ideally, every instance should be accompanied by text explaining its provenance and properties and, when appropriate, a certificate showing a correct output (which can be used to validate new solvers).

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A guide to experimental algorithmics by Catherine C. McGeoch


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