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
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
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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