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Beschreibung
Algorithms are at the heart of every nontrivial computer application, and algorithmics is a modern and active area of computer science. Every computer scientist and every professional programmer should know about the basic algorithmic toolbox: structures that allow efficient organization and retrieval of data, frequently used algorithms, and basic techniques for modeling, understanding and solving algorithmic problems.

This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, priority queues, sorted sequences, graph representation, graph traversal, shortest paths, minimum spanning trees, and optimization. The algorithms are presented in a modern way, with explicitly formulated invariants, and comment on recent trends such as algorithm engineering, memory hierarchies, algorithm libraries and certifying algorithms. The authors use pictures, words and high-level pseudocode to explain the algorithms, and then they present more detail on efficient implementations using real programming languages like C++ and Java.

The authors have extensive experience teaching these subjects to undergraduates and graduates, and they offer a clear presentation, with examples, pictures, informal explanations, exercises, and some linkage to the real world. Most chapters have the same basic structure: a motivation for the problem, comments on the most important applications, and then simple solutions presented as informally as possible and as formally as necessary. For the more advanced issues, this approach leads to a more mathematical treatment, including some theorems and proofs. Finally, each chapter concludes with a section on further findings, providing views on the state of research, generalizations and advanced solutions.
Algorithms are at the heart of every nontrivial computer application, and algorithmics is a modern and active area of computer science. Every computer scientist and every professional programmer should know about the basic algorithmic toolbox: structures that allow efficient organization and retrieval of data, frequently used algorithms, and basic techniques for modeling, understanding and solving algorithmic problems.

This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, priority queues, sorted sequences, graph representation, graph traversal, shortest paths, minimum spanning trees, and optimization. The algorithms are presented in a modern way, with explicitly formulated invariants, and comment on recent trends such as algorithm engineering, memory hierarchies, algorithm libraries and certifying algorithms. The authors use pictures, words and high-level pseudocode to explain the algorithms, and then they present more detail on efficient implementations using real programming languages like C++ and Java.

The authors have extensive experience teaching these subjects to undergraduates and graduates, and they offer a clear presentation, with examples, pictures, informal explanations, exercises, and some linkage to the real world. Most chapters have the same basic structure: a motivation for the problem, comments on the most important applications, and then simple solutions presented as informally as possible and as formally as necessary. For the more advanced issues, this approach leads to a more mathematical treatment, including some theorems and proofs. Finally, each chapter concludes with a section on further findings, providing views on the state of research, generalizations and advanced solutions.
Über den Autor
Peter Sanders is a professor of computer science at the Karlsruhe Institute of Technology. He is a leading researcher in the area of theoretical and experimental algorithm analysis, in particular related to efficient algorithms for parallel processing and communication in networks. He won the Gottfried Wilhelm Leibniz Prize of the German Research Foundation in 2012.

Kurt Mehlhorn has been a professor of computer science at Saarland University since 1975, and a director of the Max Planck Institute for Informatics in Saarbrücken. He was appointed a Fellow of the ACM (1999) "for important contributions in complexity theory and in the design, analysis, and practice of combinatorial and geometric algorithms." He has coauthored over 250 refereed conference papers and journal articles, in collaboration with 200 researchers. He received the Gottfried Wilhelm Leibniz Prize of the German Research Foundation in 1987 and the Konrad Zuse Medal of the German Society for Informatics in 1995.

Martin Dietzfelbinger is a professor of computer science at the Ilmenau University of Technology. His research interests include complexity theory and algorithms, in particular the design and analysis of randomized data structures and algorithms, hash functions, applications of hashing, sorting, algorithm engineering, and the complexity of parallel and distributed computation.

Roman Dementiev is a senior staff application engineer in the Intel Architecture, Graphics and Software group. He holds a Ph.D. in computer science from Saarland University. His interests include parallel algorithms, compute accelerators and processor architectures, hardware transactional memory, hardware performance and power monitoring, memory hierarchies, software libraries, and scalable software architectures.
The authors have considerable experience teaching on the topic of algorithms and working on related industrial projects.
Zusammenfassung

Includes supplementary material: [...]

Inhaltsverzeichnis
Appetizer: Integer Arithmetics.- Representing Sequences by Arrays and Linked Lists.- Hash Tables and Associative Arrays.- Sorting and Selection.- Priority Queues.- Sorted Sequences.- Graph Representation.- Graph Traversal.- Shortest Paths.- Minimum Spanning Trees.- Generic Approaches to Optimization.
Details
Erscheinungsjahr: 2010
Genre: Informatik, Mathematik, Medizin, Naturwissenschaften, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xii
300 S.
ISBN-13: 9783642096822
ISBN-10: 3642096824
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Mehlhorn, Kurt
Sanders, Peter
Hersteller: Springer
Springer-Verlag GmbH
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 235 x 155 x 17 mm
Von/Mit: Kurt Mehlhorn (u. a.)
Erscheinungsdatum: 10.11.2010
Gewicht: 0,476 kg
Artikel-ID: 107123629