The author team that established its reputation nearly twenty years ago with Fundamentals of Computer Algorithms offers this new title, available in both pseudocode and C++ versions. Ideal for junior/senior level courses in the analysis of algorithms, this well-researched text takes a theoretical approach to the subject, creating a basis for more in-depth study and providing opportunities for hands-on learning. Emphasizing design technique, the text uses exciting, state-of-the-art examples to illustrate design strategies.

A friendly introduction to the most useful algorithms written in simple, intuitive English The revised and updated second edition of Essential Algorithms, offers an accessible introduction to computer algorithms. The book contains a description of important classical algorithms and explains when each is appropriate. The author shows how to analyze algorithms in order to understand their behavior and teaches techniques that the can be used to create new algorithms to meet future needs. The text includes useful algorithms such as: methods for manipulating common data structures, advanced data structures, network algorithms, and numerical algorithms. It also offers a variety of general problem-solving techniques. In addition to describing algorithms and approaches, the author offers details on how to analyze the performance of algorithms. The book is filled with exercises that can be used to explore ways to modify the algorithms in order to apply them to new situations. This updated edition of Essential Algorithms: Contains explanations of algorithms in simple terms, rather than complicated math Steps through powerful algorithms that can be used to solve difficult programming problems Helps prepare for programming job interviews that typically include algorithmic questions Offers methods can be applied to any programming language Includes exercises and solutions useful to both professionals and students Provides code examples updated and written in Python and C# Essential Algorithms has been updated and revised and offers professionals and students a hands-on guide to analyzing algorithms as well as the techniques and applications. The book also includes a collection of questions that may appear in a job interview. The book’s website will include reference implementations in Python and C# (which can be easily applied to Java and C++).

Implementations, as well as interesting, real-world examples of each data structure and algorithm, are shown in the text. Full source code appears on the accompanying disk.

Using C, this book develops the concepts and theory of data structures and algorithm analysis in a gradual, step-by-step manner, proceeding from concrete examples to abstract principles. Standish covers a wide range of both traditional and contemporary software engineering topics. The text also includes an introduction to object-oriented programming using C++. By introducing recurring themes such as levels of abstraction, recursion, efficiency, representation and trade-offs, the author unifies the material throughout. Mathematical foundations can be incorporated at a variety of depths, allowing the appropriate amount of math for each user.

These are my lecture notes from CS681: Design and Analysis of Algo rithms, a one-semester graduate course I taught at Cornell for three consec utive fall semesters from '88 to '90. The course serves a dual purpose: to cover core material in algorithms for graduate students in computer science preparing for their PhD qualifying exams, and to introduce theory students to some advanced topics in the design and analysis of algorithms. The material is thus a mixture of core and advanced topics. At first I meant these notes to supplement and not supplant a textbook, but over the three years they gradually took on a life of their own. In addition to the notes, I depended heavily on the texts • A. V. Aho, J. E. Hopcroft, and J. D. Ullman, The Design and Analysis of Computer Algorithms. Addison-Wesley, 1975. • M. R. Garey and D. S. Johnson, Computers and Intractibility: A Guide to the Theory of NP-Completeness. w. H. Freeman, 1979. • R. E. Tarjan, Data Structures and Network Algorithms. SIAM Regional Conference Series in Applied Mathematics 44, 1983. and still recommend them as excellent references.

A practical guide to implementing algorithms in C++. Have you been looking for a C++ book that not only talks about some of the most popular algorithms of today, but also implements them? Then look no further. This book presents algorithms from a practical point of view, clearly explaining how the algorithms work, as well as fully implementing them in C++. Written to the intermediate C++ programmer, this book covers a wide range of subjects, from sorting and searching algorithms, to graph traversal algorithms, hashing algorithms, priority queues, finite state machines, and "algorithmic generators," a unique, object-oriented way of implementing algorithms. Includes theory and practice, with emphasis on practice. Builds from the basics to the most advanced techniques. Backs each algorithm with full source code provided on disk-no misleading code fragments. Includes high quality code, written specifically for C++, and not simply ported from some other language. All code fully tested in Borland and Microsoft versions of C++.