Algorithm Engineering: Bridging the Gap between Algorithm Theory and Practice

✍ Scribed by Matthias Müller-Hannemann, Stefan Schirra (auth.), Matthias Müller-Hannemann, Stefan Schirra (eds.)

Publisher: Springer-Verlag Berlin Heidelberg
Year: 2010
Tongue: English
Leaves: 527
Series: Lecture Notes in Computer Science 5971 : Theoretical Computer Science and General Issues
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Algorithms are essential building blocks of computer applications. However, advancements in computer hardware, which render traditional computer models more and more unrealistic, and an ever increasing demand for efficient solution to actual real world problems have led to a rising gap between classical algorithm theory and algorithmics in practice. The emerging discipline of Algorithm Engineering aims at bridging this gap. Driven by concrete applications, Algorithm Engineering complements theory by the benefits of experimentation and puts equal emphasis on all aspects arising during a cyclic solution process ranging from realistic modeling, design, analysis, robust and efficient implementations to careful experiments. This tutorial - outcome of a GI-Dagstuhl Seminar held in Dagstuhl Castle in September 2006 - covers the essential aspects of this process in ten chapters on basic ideas, modeling and design issues, analysis of algorithms, realistic computer models, implementation aspects and algorithmic software libraries, selected case studies, as well as challenges in Algorithm Engineering. Both researchers and practitioners in the field will find it useful as a state-of-the-art survey.

✦ Table of Contents

Front Matter....Pages -
Chapter 1. Foundations of Algorithm Engineering....Pages 1-15
Chapter 2. Modeling....Pages 16-57
Chapter 3. Selected Design Issues....Pages 58-126
Chapter 4. Analysis of Algorithms....Pages 127-193
Chapter 5. Realistic Computer Models....Pages 194-236
Chapter 6. Implementation Aspects....Pages 237-289
Chapter 7. Libraries....Pages 290-324
Chapter 8. Experiments....Pages 325-388
Chapter 9. Case Studies....Pages 389-445
Chapter 10. Challenges in Algorithm Engineering....Pages 446-453
Back Matter....Pages -

✦ Subjects

Algorithm Analysis and Problem Complexity; Mathematical Logic and Formal Languages; Software Engineering; Simulation and Modeling; Data Structures; Numeric Computing

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