Books like Algorithmics by David Harel

A concise, practitioner‑oriented guide that introduces machine learning concepts, methods and real‑world applications—equipped with case studies and ready‑to‑implement algorithms.

In Distributed Algorithms, Nancy Lynch provides a blueprint for designing, implementing, and analyzing distributed algorithms. She directs her book at a wide audience, including students, programmers, system designers and researchers. Distributed Algorithms contains the most significant algorithms and impossibility results in the area, all in a simple automata-theoretic setting. The algorithms are proved correct, and their complexity is analyzed according to precisely defined complexity measures. The problems covered include resource allocation, communication, consensus among distributed processes, data consistency, deadlock detection, leader election, global snapshots, and many others. The material is organized according to the system model - first by the timing model and then by the interprocess communication mechanism. The material on system models is isolated in separate chapters for easy reference. The presentation is completely rigorous, yet is intuitive enough for immediate comprehension. This book familiarizes readers with important problems, algorithms, and impossibility results in the area: readers can then recognize the problems when they arise in practice, apply the algorithms to solve them, and use the impossibility results to determine whether problems are unsolvable. The book also provides readers with the basic mathematical tools for designing new algorithms and proving new impossibility results. In addition, it teaches readers how to reason carefully about distributed algorithms - to model them formally, devise precise specifications for their required behavior, prove their correctness, and evaluate their performance with realistic measures.

Algorithms by Robert Sedgewick surveys fundamental computer algorithms and data structures, outlining their design, analysis, and implementation in modern programming languages.

An accessible guide to computer algorithms, explaining concepts, design, and evaluation with minimal math, and covering sorting, searching, graph problems, string algorithms, cryptography, data compression, and computational limits.

Algorithm Design introduces classic and modern algorithmic techniques through real‑world problems, guiding students to formulate, analyze, and solve problems by applying appropriate design principles in a clear, direct style.