This practical guide shows you how to work hands-on with a variety of storage mechanisms - including linked lists, stacks, queues, and graphs - within the constraints of the JavaScript environment. Num Pages: 246 pages, black & white illustrations, figures. BIC Classification: UMW. Category: (XV) Technical / Manuals. Dimension: 232 x 176 x 13. Weight in Grams: 416. . 2014. 1st Edition. Paperback. . . . . Books ship from the US and Ireland.

Bestandsnummer des Verk�ufers V9781449364939

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Bibliografische Details

Titel: Data Structures and Algorithms with JavaScript
Verlag: O Reilly Media
Erscheinungsjahr: 2014
Sprache: Englisch
ISBN-10: 1449364934
ISBN-13: 9781449364939
Einband: Softcover
Zustand: New

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Inhaltsangabe

As an experienced JavaScript developer moving to server-side programming, you need to implement classic data structures and algorithms associated with conventional object-oriented languages like C# and Java. This practical guide shows you how to work hands-on with a variety of storage mechanisms--including linked lists, stacks, queues, and graphs--within the constraints of the JavaScript environment.

Determine which data structures and algorithms are most appropriate for the problems you're trying to solve, and understand the tradeoffs when using them in a JavaScript program. An overview of the JavaScript features used throughout the book is also included.

This book covers:

Arrays and lists: the most common data structures
Stacks and queues: more complex list-like data structures
Linked lists: how they overcome the shortcomings of arrays
Dictionaries: storing data as key-value pairs
Hashing: good for quick insertion and retrieval
Sets: useful for storing unique elements that appear only once
Binary Trees: storing data in a hierarchical manner
Graphs and graph algorithms: ideal for modeling networks
Algorithms: including those that help you sort or search data
Advanced algorithms: dynamic programming and greedy algorithms

�ber die Autorin bzw. den Autor

Michael McMillan is an instructor of Computer Information Systems at Pulaski Technical College in North Little Rock, AR. He is also an adjunct instructor of Information Science at the University of Arkansas at Little Rock. Before moving to academia, he was a programmer/analyst for Arkansas Children's Hospital, where he worked in statistical computing and data analysis.

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