Mastering Algorithms with C|
von Kyle Loudon
Taschenbuch, 27. April 1999 Auf Lager.
Preis: € 37,00 (Bücher Versandkostenfrei nach D, CH und A, bei Drittanbietern gelten deren Versandbedingungen)
Written with the intermediate to advanced C programmer in mind, < I> Mastering Algorithms with C delivers a no-nonsense guide to the most common algorithms needed by real-world developers.
The highlight of the book has to be its concise and readable C functions for all the algorithms presented here, including basics like linked lists, stacks to trees, graphs, and sorting/searching algorithms. The C functions that implement these algorithms are clearly printed and remarkably easy to read. You can use this sample code directly or adapt it into your C/ C++ code.
Although mathematical concepts like Big-O notation are discussed, the authors don't get bogged down in the computer science theory surrounding algorithms. Instead, they present the most tried-and-true algorithms available today in an efficient format. Besides introducing each algorithm, they describe how each is used in computing today, along with a short demo application. Some of these samples are quite low-level, such as a virtual memory manager implemented with linked lists. Most examples are more of general interest, such as a graphing example that counts network hops.
Each section ends with questions and answers about how the algorithms work, along with references to other algorithms (both in the book and from other sources). The authors concentrate on the most useful algorithms available today and don't try to cover every available variation. Busy readers will appreciate the intelligent selection-and efficient presentation-used here.
There are a number of books on C algorithms, but < I> Master Algorithms with C is one of the most concise and immediately useful. It's a perfect choice for the working C/ C++ programmer who's in a hurry to find just the right algorithm for writing real-world code. < I>-Richard Dragan
< B> Topics covered: Algorithm efficiency, pointer basics, arrays, recursion, Big-O Notation, linked lists, stacks, queues, sets, hash tables, trees and B-trees, searching, heaps and priority queues, graphs, sorting and searching algorithms, numerical methods, data compression, Huffman coding, L Z77, data encryption, D E S, R S A, graph algorithms, minimum spanning trees, geometric algorithms, and convex hulls.