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020 _a9783319098876
040 _dWaSeSS
_beng
_dEG-ScBUE
082 0 4 _222
_a005.1
_bVRA
100 1 _aVrajitoru, Dana.
245 1 0 _aPractical analysis of algorithms /
_cDana Vrajitoru, William Knight.
260 _aCham :
_bSpringer,
_cc.2014.
300 _axii, 466 p. :
_bill. ;
_c24 cm.
490 0 _aUndergraduate Topics in Computer Science,
_x1863-7310
504 _aIncludes bibliographical references and index.
505 0 _aIntroduction -- Mathematical Preliminaries -- Fundamental Notations in Analysis of Algorithms -- Recurrence Relations -- Deterministic Analysis of Algorithms -- Algorithms and Probabilities -- Finite Graph Algorithms -- Appendix: Probability Theory.
506 _aAvailable on campus and off campus with authorized login.
520 _aAnalysis of algorithms plays an essential role in the education and training of any serious programmer preparing to deal with real world applications. Practical Analysis of Algorithms introduces the essential concepts of algorithm analysis required by core undergraduate and graduate computer science courses, in addition to providing a review of the fundamental mathematical notions necessary to understand these concepts. Throughout the text, the explanations are aimed at the level of understanding of a typical upper-level student, and are accompanied by detailed examples and classroom-tested exercises. Topics and features: Includes numerous fully-worked examples and step-by-step proofs, assuming no strong mathematical background Describes the foundation of the analysis of algorithms theory in terms of the big-Oh, Omega, and Theta notations Examines recurrence relations, a very important tool used in the analysis of algorithms Discusses the concepts of basic operation, traditional loop counting, and best case and worst case complexities Reviews various algorithms of a probabilistic nature, and uses elements of probability theory to compute the average complexity of algorithms such as Quicksort Introduces a variety of classical finite graph algorithms, together with an analysis of their complexity Provides an appendix on probability theory, reviewing the major definitions and theorems used in the book This clearly-structured and easy-to-read textbook/reference applies a unique, practical approach suitable for professional short courses and tutorials, as well as for students of computer science. Dr. Dana Vrajitoru is an Associate Professor of Computer Science at Indiana University South Bend, IN, USA. Dr. William Knight is an Emeritus Associate Professor at the same institution.
650 7 _aComputer algorithms.
_2BUEsh
_910553
650 0 _aLogic design
_xAnalysis.
_93913
651 _2BUEsh
653 _bCOMSCI
_cMay2018
700 1 _aKnight, William.
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319098876
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