04412nam a22005535i 4500 978-3-031-61794-2 DE-He213 20251030112841.0 cr nn 008mamaa 240807s2024 sz | s |||| 0|eng d 9783031617942 978-3-031-61794-2 10.1007/978-3-031-61794-2 doi QA76.6-76.66 UM bicssc COM051000 bisacsh UM thema Laaksonen, Antti. author. aut http://id.loc.gov/vocabulary/relators/aut 82008 Guide to Competitive Programming [electronic resource] : Learning and Improving Algorithms Through Contests / by Antti Laaksonen. 3rd ed. 2024. Cham : Springer International Publishing : Imprint: Springer, 2024. XVIII, 349 p. 287 illus., 65 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Undergraduate Topics in Computer Science, 2197-1781 1. 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. Building 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. Computer programming. Algorithms. 58677 Programming languages (Electronic computers). 66206 Education Data processing. Programming Techniques. 65517 Algorithms. 58677 Programming Language. 66208 Computers and Education. SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031617935 Printed edition: 9783031617959 Undergraduate Topics in Computer Science, 2197-1781 66494 https://doi.org/10.1007/978-3-031-61794-2 ZDB-2-SCS ZDB-2-SXCS 62290 62290