000 03832nam a22004935i 4500
001 978-3-540-77978-0
003 DE-He213
005 20161121230719.0
007 cr nn 008mamaa
008 100301s2008 gw | s |||| 0|eng d
020 _a9783540779780
_9978-3-540-77978-0
024 7 _a10.1007/978-3-540-77978-0
_2doi
050 4 _aQA76.6-76.66
072 7 _aUM
_2bicssc
072 7 _aCOM051000
_2bisacsh
082 0 4 _a005.11
_223
100 1 _aMehlhorn, Kurt.
_eauthor.
245 1 0 _aAlgorithms and Data Structures
_h[electronic resource] :
_bThe Basic Toolbox /
_cby Kurt Mehlhorn, Peter Sanders.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2008.
300 _aXII, 300 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aAppetizer: 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.
520 _aAlgorithms 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.
650 0 _aComputer science.
650 0 _aComputer programming.
650 0 _aData structures (Computer science).
650 0 _aAlgorithms.
650 0 _aComputers.
650 1 4 _aComputer Science.
650 2 4 _aProgramming Techniques.
650 2 4 _aAlgorithm Analysis and Problem Complexity.
650 2 4 _aData Structures.
650 2 4 _aComputing Methodologies.
700 1 _aSanders, Peter.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783540779773
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-540-77978-0
912 _aZDB-2-SCS
950 _aComputer Science (Springer-11645)
999 _c502880
_d502880