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001 978-3-030-39357-1
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008 200508s2020 sz | s |||| 0|eng d
020 _a9783030393571
_9978-3-030-39357-1
024 7 _a10.1007/978-3-030-39357-1
_2doi
050 4 _aQA76.6-76.66
072 7 _aUM
_2bicssc
072 7 _aCOM051000
_2bisacsh
072 7 _aUM
_2thema
082 0 4 _a005.11
_223
100 1 _aLaaksonen, Antti.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aGuide to Competitive Programming
_h[electronic resource] :
_bLearning and Improving Algorithms Through Contests /
_cby Antti Laaksonen.
250 _a2nd ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2020.
300 _aXV, 309 p. 287 illus., 65 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aUndergraduate Topics in Computer Science,
_x2197-1781
505 0 _aIntroduction -- 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 _aBuilding 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 Reviewsthe 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.
650 0 _aComputer programming.
650 0 _aAlgorithms.
650 0 _aProgramming languages (Electronic computers).
650 0 _aEducation
_xData processing.
650 1 4 _aProgramming Techniques.
650 2 4 _aAlgorithms.
650 2 4 _aProgramming Language.
650 2 4 _aComputers and Education.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030393564
776 0 8 _iPrinted edition:
_z9783030393588
830 0 _aUndergraduate Topics in Computer Science,
_x2197-1781
856 4 0 _uhttps://doi.org/10.1007/978-3-030-39357-1
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c184783
_d184783