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Laaksonen, Antti.

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Guide to competitive programming = learning and improving algorithms through contests /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Guide to competitive programming/ by Antti Laaksonen.
Reminder of title:	learning and improving algorithms through contests /
Author:	Laaksonen, Antti.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	xv, 309 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Programming Techniques -- Efficiency -- Sorting and Searching -- Data Structures -- Dynamic Programming -- Graph Algorithms -- Algorithm Design Topics -- Range Queries -- Tree Algorithms -- Mathematics -- Advanced Graph Algorithms -- Geometry -- String Algorithms -- Additional Topics -- Appendix A: Mathematical Background.
Contained By:	Springer eBooks
Subject:	Computer programming. -
Online resource:	https://doi.org/10.1007/978-3-030-39357-1
ISBN:	9783030393571

Guide to competitive programming = learning and improving algorithms through contests /
Laaksonen, Antti.

Guide to competitive programminglearning and improving algorithms through contests /[electronic resource] :by Antti Laaksonen. - Second edition. - Cham :Springer International Publishing :2020. - xv, 309 p. :ill., digital ;24 cm. - Undergraduate topics in computer science,1863-7310. - Undergraduate topics in computer science..

Introduction -- Programming Techniques -- Efficiency -- Sorting and Searching -- Data Structures -- Dynamic Programming -- Graph Algorithms -- Algorithm Design Topics -- Range Queries -- Tree Algorithms -- Mathematics -- Advanced Graph Algorithms -- Geometry -- String Algorithms -- Additional Topics -- Appendix A: Mathematical Background.

Building on what already is the most comprehensive introduction to competitive programming, this enhanced new textbook features new material on advanced topics, such as calculating Fourier transforms, finding minimum cost flows in graphs, and using automata in string problems. Critically, the text accessibly describes and shows how competitive programming is a proven method of implementing and testing algorithms, as well as developing computational thinking and improving both programming and debugging skills. Topics and features: Introduces dynamic programming and other fundamental algorithm design techniques, and investigates a wide selection of graph algorithms Compatible with the IOI Syllabus, yet also covering more advanced topics, such as maximum flows, Nim theory, and suffix structures Surveys specialized algorithms for trees, and discusses the mathematical topics that are relevant in competitive programming Reviews the features of the C++ programming language, and describes how to create efficient algorithms that can quickly process large data sets Discusses sorting algorithms and binary search, and examines a selection of data structures of the C++ standard library Covers such advanced algorithm design topics as bit-parallelism and amortized analysis, and presents a focus on efficiently processing array range queries Describes a selection of more advanced topics, including square-root algorithms and dynamic programming optimization Fully updated, expanded and easy to follow, this core textbook/guide is an ideal reference for all students needing to learn algorithms and to practice for programming contests. Knowledge of programming basics is assumed, but previous background in algorithm design or programming contests is not necessary. With its breadth of topics, examples and references, the book is eminently suitable for both beginners and more experienced readers alike. Dr. Antti Laaksonen has worked as a teacher and researcher at the University of Helsinki and Aalto University, Finland.

ISBN: 9783030393571

Standard No.: 10.1007/978-3-030-39357-1doiSubjects--Topical Terms:

527209
Computer programming.

LC Class. No.: QA76.6 / .L335 2020

Dewey Class. No.: 005.1

Guide to competitive programming = learning and improving algorithms through contests /
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245 1 0 $a Guide to competitive programming $h [electronic resource] : $b learning and improving algorithms through contests / $c by Antti Laaksonen.
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260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xv, 309 p. : $b ill., digital ; $c 24 cm.
490 1 $a Undergraduate topics in computer science, $x 1863-7310
505 0 $a Introduction -- Programming Techniques -- Efficiency -- Sorting and Searching -- Data Structures -- Dynamic Programming -- Graph Algorithms -- Algorithm Design Topics -- Range Queries -- Tree Algorithms -- Mathematics -- Advanced Graph Algorithms -- Geometry -- String Algorithms -- Additional Topics -- Appendix A: Mathematical Background.
520 $a Building on what already is the most comprehensive introduction to competitive programming, this enhanced new textbook features new material on advanced topics, such as calculating Fourier transforms, finding minimum cost flows in graphs, and using automata in string problems. Critically, the text accessibly describes and shows how competitive programming is a proven method of implementing and testing algorithms, as well as developing computational thinking and improving both programming and debugging skills. Topics and features: Introduces dynamic programming and other fundamental algorithm design techniques, and investigates a wide selection of graph algorithms Compatible with the IOI Syllabus, yet also covering more advanced topics, such as maximum flows, Nim theory, and suffix structures Surveys specialized algorithms for trees, and discusses the mathematical topics that are relevant in competitive programming Reviews the features of the C++ programming language, and describes how to create efficient algorithms that can quickly process large data sets Discusses sorting algorithms and binary search, and examines a selection of data structures of the C++ standard library Covers such advanced algorithm design topics as bit-parallelism and amortized analysis, and presents a focus on efficiently processing array range queries Describes a selection of more advanced topics, including square-root algorithms and dynamic programming optimization Fully updated, expanded and easy to follow, this core textbook/guide is an ideal reference for all students needing to learn algorithms and to practice for programming contests. Knowledge of programming basics is assumed, but previous background in algorithm design or programming contests is not necessary. With its breadth of topics, examples and references, the book is eminently suitable for both beginners and more experienced readers alike. Dr. Antti Laaksonen has worked as a teacher and researcher at the University of Helsinki and Aalto University, Finland.
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