Antti Laaksonen – författare

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++ programminglanguage, 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.

This 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 algorithmsCompatible with the IOI Syllabus, yet also covering more advanced topics, such as maximum flows, Nim theory, and suffix structuresProvides advice for students aiming for the IOI contestSurveys specialized algorithms for trees, and discusses the mathematical topics that are relevant in competitive programmingExamines the use of the Python language in competitive programmingDiscusses sorting algorithms and binary search, and examines a selection of data structures of the C++ standard libraryExplores how GenAI will impact on the future of the fieldCovers such advanced algorithm design topics as bit-parallelism and amortized analysis, and presents a focus on efficiently processing array range queriesDescribes a selection of more advanced topics, including square-root algorithms and dynamic programming optimizationFully 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.

This 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 algorithmsCompatible with the IOI Syllabus, yet also covering more advanced topics, such as maximum flows, Nim theory, and suffix structuresProvides advice for students aiming for the IOI contestSurveys specialized algorithms for trees, and discusses the mathematical topics that are relevant in competitive programmingExamines the use of the Python language in competitive programmingDiscusses sorting algorithms and binary search, and examines a selection of data structures of the C++ standard libraryExplores how GenAI will impact on the future of the fieldCovers such advanced algorithm design topics as bit-parallelism and amortized analysis, and presents a focus on efficiently processing array range queriesDescribes 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.

Generative AI has changed the landscape of programming. How can AI tools be used effectively and safely, and what is the role of human programmers now?This unique textbook/guide is a comprehensive introduction to using generative AI in programming. Based on both practical experience and scientific studies, it shows how AI tools can be applied effectively to programmers’ tasks—such as information retrieval, code generation, test creation, and code analysis. The book explores both the new possibilities and the risks of using generative AI, emphasizing the importance of programmers’ expertise: Whereas AI tools can make programmers more productive, their use may also lead to serious problems. The book also addresses how learning and teaching programming are evolving in the era of generative AI.Topics and features:Explains how large language models work under the hood, and how this affects their abilities and limitationsIncludes a wealth of practical examples of using AI tools in a variety of programming languagesOffers advice on how to build effective prompts for tasks such as generating professional code and learning new programming languagesExplores recent scientific literature on using generative AI in software development and programming educationShows how generative AI connects to the history of programming, including developments in programming paradigms and abstractionsThis textbook is an ideal guide for students and programmers wishing to understand the role of generative AI in programming, as well as to learn both how to use AI tools in practice and the theory behind them. The book assumes basic programming knowledge, but no prior experience with AI tools is necessary. It is suitable both for beginners learning programming and for experienced programmers looking to update their skills.

Generative AI has changed the landscape of programming. How can AI tools be used effectively and safely, and what is the role of human programmers now?This unique textbook/guide is a comprehensive introduction to using generative AI in programming. Based on both practical experience and scientific studies, it shows how AI tools can be applied effectively to programmers’ tasks—such as information retrieval, code generation, test creation, and code analysis. The book explores both the new possibilities and the risks of using generative AI, emphasizing the importance of programmers’ expertise: Whereas AI tools can make programmers more productive, their use may also lead to serious problems. The book also addresses how learning and teaching programming are evolving in the era of generative AI.Topics and features:Explains how large language models work under the hood, and how this affects their abilities and limitationsIncludes a wealth of practical examples of using AI tools in a variety of programming languagesOffers advice on how to build effective prompts for tasks such as generating professional code and learning new programming languagesExplores recent scientific literature on using generative AI in software development and programming educationShows how generative AI connects to the history of programming, including developments in programming paradigms and abstractionsThis textbook is an ideal guide for students and programmers wishing to understand the role of generative AI in programming, as well as to learn both how to use AI tools in practice and the theory behind them. The book assumes basic programming knowledge, but no prior experience with AI tools is necessary. It is suitable both for beginners learning programming and for experienced programmers looking to update their skills.