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09 Sep 2017

Packt Publishing - Learning JavaScript Data Structures and Algorithms

Category: Tutorials
 
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Packt Publishing - Learning JavaScript Data Structures and Algorithms
 
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Packt Publishing - Learning javascript Data Structures and Algorithms
English | Size: 132.71 MB
Category: Tutorial

As businesses collect increasing amounts of vital data, the need to structure software components increases every day. Using appropriate data structures and having a good understanding of algorithm analysis is key to writing maintainable and extensible quality software, thus solving the crisis.
Learning javascript Data Structures and Algorithms will show you how to organize your code with the most appropriate data structures available to get the job done fast, and in a logical way that is easy to maintain, refactor, and test. By using effective data structures, you can take advantage of advanced algorithms, thus making your web applications more powerful and scalable. You will learn about common software engineering data structures, such as linked-lists, trees, and graphs, and get to know how to implement them in javascript. You'll also master ways to use them in various types of algorithms.
You will begin by finding out how to build on native javascript constructs, and create collections such as maps, queues, stacks, sets, graphs, and other data structures. You will then discover how to develop, analyze, and improve algorithms to search deep trees, lists, and other complex collections, as well as sorting containers of data.
This practical course will guide you through a web application development cycle using a structured and disciplined approach, focusing on accuracy and efficiency as you build quality software.
What You Will Learn
• Master existing javascript collections such as arrays, sets, and maps
• Develop abstract data types to extend javascript into a more flexible and powerful
programming language
• Grasp the basics of software engineering to differentiate yourself from undisciplined coders
• Conjure powerful algorithms to traverse dense graphs and trees in the least possible steps
• Devour the science of comparing different algorithms to choose the best one for the
respective task
• Search and sort native and custom data types through collection iterator methods
• Create complex abstract data types by reusing existing classes
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