Focusing on the fundamentals of data organization and retrieval, this textbook introduces essential algorithms and techniques for solving algorithmic problems, particularly in the context of modern parallel processing. It balances theoretical concepts with practical applications, covering a range of topics from basic data structures like arrays and linked lists to advanced graph algorithms and optimization strategies. The authors also address contemporary issues such as algorithm engineering and memory hierarchies, reflecting the shift towards performance-critical applications in teaching algorithms.
Algorithms are central to nontrivial computer applications, making algorithmics a vital area of computer science. Every computer scientist and programmer should be familiar with essential algorithmic tools, including data organization and retrieval structures, commonly used algorithms, and techniques for modeling and solving algorithmic problems. This concise introduction targets students and professionals with programming and basic mathematical knowledge. Chapters cover a range of topics, such as arrays, linked lists, hash tables, sorting, priority queues, graph representation, and optimization. Algorithms are presented with clearly defined invariants and insights into contemporary trends like algorithm engineering and memory hierarchies. The authors utilize visuals, descriptive language, and high-level pseudocode, followed by efficient implementation details in languages like C++ and Java. Drawing from extensive teaching experience, the authors provide a clear presentation enriched with examples, illustrations, informal explanations, exercises, and real-world connections. Each chapter follows a consistent structure: problem motivation, key applications, simple solutions, and more advanced mathematical treatments, including theorems and proofs. Concluding sections offer insights into ongoing research, generalizations, and advanced solutions.
