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PHP 7 Data Structures and Algorithms

PHP 7 Data Structures and Algorithms

By : Rahman
5 (2)
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PHP 7 Data Structures and Algorithms

PHP 7 Data Structures and Algorithms

5 (2)
By: Rahman

Overview of this book

PHP has always been the the go-to language for web based application development, but there are materials and resources you can refer to to see how it works. Data structures and algorithms help you to code and execute them effectively, cutting down on processing time significantly. If you want to explore data structures and algorithms in a practical way with real-life projects, then this book is for you. The book begins by introducing you to data structures and algorithms and how to solve a problem from beginning to end using them. Once you are well aware of the basics, it covers the core aspects like arrays, listed lists, stacks and queues. It will take you through several methods of finding efficient algorithms and show you which ones you should implement in each scenario. In addition to this, you will explore the possibilities of functional data structures using PHP and go through advanced algorithms and graphs as well as dynamic programming. By the end, you will be confident enough to tackle both basic and advanced data structures, understand how they work, and know when to use them in your day-to-day work
Table of Contents (14 chapters)
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What is a heap?

By definition, a heap is a specialized tree data structure that supports a heap property. A heap property is defined in such a way that the root of a heap structure will be either smaller or larger than its child nodes. If the parent node is greater than the child nodes, then it is known as max-heap and if the parent node is smaller than the child nodes then it is known as min-heap. The following figure shows an example of max-heap:

If we look at the root node, the value 100 is greater than the two child nodes 19 and 36. Similarly for 19, the value is greater than 17 and 3. It applies the same rule for 36 and 17. As we can see from the tree structure, the tree is not completely sorted or ordered. But the important fact is we can always find the maximum or minimum at the root of the tree, which can be very efficient for many use cases.

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