04066nam a22004695i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001700153072001500170072002300185072001400208100007900222245013700301250001800438264007500456300006800531336002600599337002600625338003600651347002400687490005700711505035700768520201301125650002603138650001603164650005003180650003203230650002803262650001603290650002603306650002903332710003403361773002603395776003603421776003603457830005703493856004603550978-3-031-61794-2DE-He21320251030112841.0cr nn 008mamaa240807s2024    sz |    s    |||| 0|eng d  a97830316179427 a10.1007/978-3-031-61794-22doi 4aQA76.6-76.66 7aUM2bicssc 7aCOM0510002bisacsh 7aUM2thema1 aLaaksonen, Antti.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut10aGuide to Competitive Programmingh[electronic resource] :bLearning and Improving Algorithms Through Contests /cby Antti Laaksonen.  a3rd ed. 2024. 1aCham :bSpringer International Publishing :bImprint: Springer,c2024.  aXVIII, 349 p. 287 illus., 65 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aUndergraduate Topics in Computer Science,x2197-17810 a1. Introduction -- 2. Programming Techniques -- 3. Efficiency -- 4. Sorting and Searching -- 5. Data Structures -- 6. Dynamic Programming -- 7. Graph Algorithms -- 8. Algorithm Design Topics -- 9. Range Queries -- 10. Tree Algorithms -- 11. Mathematics -- 12. Advanced Graph Algorithms -- 13. Geometry -- 14. String Algorithms -- 15. Additional Topics.  aBuilding on what already is the most comprehensive introduction to competitive programming, this new edition now introduces Python’s use in the field and looks into how Generative A.I. (GenAI) will affect its future. 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 Provides advice for students aiming for the IOI contest Surveys specialized algorithms for trees, and discusses the mathematical topics that are relevant in competitive programming Examines the use of the Python language in competitive programming Discusses sorting algorithms and binary search, and examines a selection of data structures of the C++ standard library Explores how GenAI will impact on the future of the field 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. 0aComputer programming. 0aAlgorithms. 0aProgramming languages (Electronic computers). 0aEducationxData processing.14aProgramming Techniques.24aAlgorithms.24aProgramming Language.24aComputers and Education.2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303161793508iPrinted edition:z9783031617959 0aUndergraduate Topics in Computer Science,x2197-178140uhttps://doi.org/10.1007/978-3-031-61794-2