Bibliotex, 2019. — 290 p. Algorithms are very important in computer Science. The best criteria of the algorithm make sure that the computer will perform in the best possible manner of a given task. In cases where efficiency matters a proper algorithm is important to be used. An algorithm is important in optimizing a computer program according to the available resources....
Poorav Publications, 2025. — 228 p. Welcome to “Mastering Algorithms and Data Structures”, a comprehensive guide designed to bridge the gap between theoretical concepts and practical application in the realm of Computer Science. This book is crafted for students, professionals, and enthusiasts who aspire to understand and master the intricacies of algorithms and Data Structures...
Steven J. Rosenberg, 2024. — 121 p. Algorithms: Beginnings. Algorithm: a definition. Time- and Space-Complexity. The Counting Principle. Stacks and Queues. The Stack ADT. The Queue ADT. Big-O and Asymptotic Complexity. Big-O Notation. Asymptotic Complexity. Asymptotic Complexity and Limits. State Analysis. State Analysis. Example: Sudoku Solver. Graphs. The Graph Data Type....
Leanpub, 2024. — 139 p. A concise, illustrated guide to algorithms and data structures, perfect for coding interviews, classes, or self-study. Covers key concepts, from fundamentals to graphs, trees, sorting, and search techniques. This book is a concise and illustrated guide for anyone who wants to brush up on their fundamentals in the context of coding interviews, Computer...
Red Globe Press, 2003. — 287 p. What will be the next revolution in software technology to follow XML and generics? Whatever it may be, it is likely to come from functional programming, where many of the key ideas of the last decade originated. In this textbook, the leading researchers of the field take you on a tour of the current hot topics in functional programming, with...
De Gruyter, 2020. — 450 p. — ISBN: 9783110595574. The systematic description starts with basic theory and applications of different kinds of data structures, including storage structures and models. It also explores data processing methods such as sorting, indexing, and search technologies. Due to its numerous exercises, the book is a helpful reference for graduate students,...
CompreQuest Books, 2024. — 372 p. — (Programming Models). Unlock the Future of Software Development: Declarative Programming. Are you tired of wrestling with complex, error-prone code? Ready to revolutionize your approach to software development? Dive into the world of declarative programming and discover a simpler, more efficient way to build robust, logic-based programs....
CompreQuest Books, 2024. — 328 p. — (Programming Models). Discover the Algorithmic Revolution: Procedural Programming Unveiled. Unearth the Essence of Algorithmic Mastery. Embark on a transformative journey into the heart of procedural programming with "Procedural Programming: Unleashing Algorithmic Power." This book commands your attention as it unravels the foundational...
Massachusetts Institute of Technology (MIT), 2009. — 171 p. This course covers a collection of geometric techniques that apply broadly in modern algorithm design. Spectral Graph Theory. Linear algebra review, adjacency, and Laplacian matrices associated with a graph, for example, Laplacians. Properties of the Laplacian, positive semidefinite matrices, spectra of common graphs,...
Universita di Pisa, 2020. — 259 p. Prologo. A warm-up! A cubic-time algorithm. A quadratic-time algorithm. A linear-time algorithm. Another linear-time algorithm. Few interesting variants. Random Sampling. Disk model and known sequence length. Streaming model and known sequence length. Streaming model and unknown sequence length. List Ranking. The pointer-jumping technique....
Singapore: World Scientific Publishing Company, 2022. — 399 p. — (Lecture Notes Series On Computing, 16). — ISBN: 9811252971. This book is an introduction to the field of parallel algorithms and the underpinning techniques to realize parallelization. The emphasis is on designing algorithms within the timeless and abstract context of a high-level programming language. The focus...
Cs.illinois.edu, 2015. — 514 p. These are lecture notes that I wrote for various algorithms classes at the University of Illinois at Urbana-Champaign, which I have taught on average once a year since January 1999. The most recent revision of these notes (or nearly so) is available online, along with a near-complete archive of all my past homework and exams. Whenever I teach an...
5th Edition. — Jones & Bartlett Learning, 2015. — 676 p. — ISBN: 1284049191, 9781284049190. Foundations of Algorithms, Fifth Edition offers a well-balanced presentation of algorithm design, complexity analysis of algorithms, and computational complexity. Ideal for any computer science student with a background in college algebra and discrete structures, the text presents...
Wiley-ISTE, 2022. — 304 p. — ISBN: 978-1-78630-891-7. Data structures and algorithms is a fundamental course in Computer Science, which enables learners across any discipline to develop the much-needed foundation of efficient programming, leading to better problem-solving in their respective disciplines. Most of the well-known textbooks/monographs on this subject have discussed...
Wiley-ISTE, 2022. — 304 p. — ISBN: 978-1-78630-891-7. Data structures and algorithms is a fundamental course in Computer Science, which enables learners across any discipline to develop the much-needed foundation of efficient programming, leading to better problem-solving in their respective disciplines. Most of the well-known textbooks/monographs on this subject have discussed...
London: Wiley-ISTE, 2023. — 356 p. Hash Tables. Dictionaries. Hash table structure. Hash functions. Building hash functions. Linear open addressing. Operations on linear open-addressed hash tables. Performance analysis. Other collision resolution techniques with open addressing. Chaining. Operations on chained hash tables. Performance analysis. Applications. Representation of a...
London: Wiley-ISTE, 2023. — 284 p. History of algorithms. Definition, structure, and properties of algorithms. Definition. Structure and properties. Development of an algorithm. Data structures and algorithms. Data structures – definition and classification. Abstract data types. Classification. Algorithm design techniques. Organization of the book. Analysis of Algorithms. The...
Springer Cham, 2022. — 513 p. — eBook ISBN: 978-3-031-17043-0. With approximately 2500 problems, this book provides a collection of practical problems on the basic and advanced data structures, design, and analysis of algorithms. To make this book suitable for self-instruction, about one-third of the algorithms are supported by solutions, and hints and comments support some...