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.

This book constitutes the refereed proceedings of the 5th Workshop on Algorithm Engineering, WAE 2001, held in Aarhus, Denmark, in August 2001. The 15 revised full papers presented were carefully reviewed and selected from 25 submissions. Among the topics addressed are implementation, experimental testing, and fine-tuning of discrete algorithms; novel use of discrete algorithms in other disciplines; empirical research on algorithms and data structures; and methodological issues regarding the process of converting user requirements into efficient algorithmic solutions and implemenations.

Algorithm Engineering is a methodology for algorithmic research that combines theory with implementation and experimentation in order to obtain better algorithms with high practical impact. Traditionally, the study of algorithms was dominated by mathematical (worst-case) analysis. In Algorithm Engineering, algorithms are also implemented and experiments conducted in a systematic way, sometimes resembling the experimentation processes known from fields such as biology, chemistry, or physics. This helps in counteracting an otherwise growing gap between theory and practice.

This volume contains the papers accepted for the 4th Workshop on Algorithm Engineering (WAE 2000) held in Saarbruc ̈ ken, Germany, during 5–8 September 2000, together with the abstract of the invited lecture given by Karsten Weihe. The Workshop on Algorithm Engineering covers research on all aspects of the subject. The goal is to present recent research results and to identify and explore directions for future research. Previous meetings were held in Venice (1997), Saarbruc ̈ ken (1998), and London (1999). Papers were solicited describing original research in all aspects of algorithm engineering, including: – Development of software repositories and platforms which allow the use of and experimentation with e?cient discrete algorithms. – Novel uses of discrete algorithms in other disciplines and the evaluation of algorithms for realistic environments. – Methodological issues including standards in the context of empirical - search on algorithms and data structures. – Methodological issues regarding the process of converting user requirements into e?cient algorithmic solutions and implementations. The program committee accepted 16 from a total of 30 submissions. The program committee meeting was conducted electronically. The criteria for sel- tion were originality, quality, and relevance to the subject area of the workshop. Considerable e?ort was devoted to the evaluation of the submissions and to p- viding the authors with feedback. Each submission was reviewed by at least four program committee members (assisted by subreferees). A special issue of the ACM Journal of Experimental Algorithmics will be devoted to selected papers from WAE 2000.

Compact DFA representation for fast regular expression search / Gonzalo Navarro / - The Max-Shift algorithm for approximate string matching / Costas S. Iliopoulos / - Fractal matrix multiplication : a case study on portability of cache performance / Gianfranco Bilardi / - Experiences with the design and implementation of space-efficient deques / Jyrki Katajainen / - Designing and implementing a general purpose halfedge data structure / Hervé Brönnimann / - Optimised predecessor data structures for internal memory / Naila Rahman / - An adaptable and expensible geometry kernel / Susan Hert / - Efficient resource allocation with noisy functions / Arne Andersson / - Improving the efficiency of branch and bound algorithms for the simple plant location problem / Boris Goldengorin / - Exploiting partial knowledge of satisfying assignments / Kazuo Iwama / - Using PRAM algorithms on a uniform-memory-access shared-memory architecture / David A. Bader / - An experimental study of basic communicat ...

This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Algorithmic Engineering and Experimentation, ALENEX'99, held in Baltimore, Maryland, USA, in January 1999. The 20 revised full papers presented were carefully selected from a total of 42 submissions during two rounds of reviewing and improvement. The papers are organized in sections on combinatorial algorithms, computational geometry, software and applications, algorithms for NP-hard problems, and data structures.

Algorithm engineering allows computer engineers to produce a computational machine that will execute an algorithm as efficiently and cost-effectively as possible given a set of constraints, such as minimal performance or the availability of technology. Addressing algorithm engineering in a parallel setting, regular array syntheses offer powerful computation and embody best practice, but often face the criticism that they are applicable only to restricted classes of algorithms. Algorithm Engineering for Integral and Dynamic Problems reviews the basic principles of regular array synthesis and shows how to extend its use into classes of algorithms traditionally viewed to be beyond its domain of application. The author discusses the transformation of the initial algorithm specification into a specification with data dependencies of increased regularity in order to obtain corresponding regular arrays by direct application of the standard mapping techniques. The book includes a review of the basic principles of regular array synthesis followed by applications of these techniques to well-known algorithms, concluding with numerous case studies to illustrate the methods. Researchers and practitioners in algorithm engineering will find that this text significantly extends their understanding of the applications of regular array synthesis and regular array processors beyond the traditionally narrow field of relevance.

There are many textbooks on algorithms focusing on big-O notation and basic design principles. This book offers a unique approach to taking the design and analyses to the level of predictable practical efficiency, discussing core and classic algorithmic problems that arise in the development of big data applications, and presenting elegant solutions of increasing sophistication and efficiency. Solutions are analyzed within the classic RAM model, and the more practically significant external-memory model that allows one to perform I/O-complexity evaluations. Chapters cover various data types, including integers, strings, trees, and graphs, algorithmic tools such as sampling, sorting, data compression, and searching in dictionaries and texts, and lastly, recent developments regarding compressed data structures. Algorithmic solutions are accompanied by detailed pseudocode and many running examples, thus enriching the toolboxes of students, researchers, and professionals interested in effective and efficient processing of big data.

One of Springer’s renowned Major Reference Works, this awesome achievement provides a comprehensive set of solutions to important algorithmic problems for students and researchers interested in quickly locating useful information. This first edition of the reference focuses on high-impact solutions from the most recent decade, while later editions will widen the scope of the work. All entries have been written by experts, while links to Internet sites that outline their research work are provided. The entries have all been peer-reviewed. This defining reference is published both in print and on line.

This Festschrift volume, published in honor of Kurt Mehlhorn on the occasion of his 60th birthday, contains 28 papers written by his former Ph.D. students and colleagues as well as by his former Ph.D. advisor, Bob Constable. The volume's title is a translation of the title of Kurt Mehlhorn's first book, "Effiziente Algorithmen", published by Teubner-Verlag in 1977. This Festschrift demonstrates how the field of algorithmics has developed and matured in the decades since then. The papers included in this volume are organized in topical sections on models of computation and complexity; sorting and searching; combinatorial optimization with applications; computational geometry and geometric graphs; and algorithm engineering, exactness and robustness.