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  • Book Overview & Buying Java 9 Data Structures and Algorithms
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Java 9 Data Structures and Algorithms

Java 9 Data Structures and Algorithms

By : Ray Chawdhuri
2.3 (3)
Buy this Book
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Java 9 Data Structures and Algorithms

Java 9 Data Structures and Algorithms

2.3 (3)
By: Ray Chawdhuri
Buy this Book

Overview of this book

Java 9 Data Structures and Algorithms covers classical, functional, and reactive data structures, giving you the ability to understand computational complexity, solve problems, and write efficient code. This book is based on the Zero Bug Bounce milestone of Java 9. We start off with the basics of algorithms and data structures, helping you understand the fundamentals and measure complexity. From here, we introduce you to concepts such as arrays, linked lists, as well as abstract data types such as stacks and queues. Next, we’ll take you through the basics of functional programming while making sure you get used to thinking recursively. We provide plenty of examples along the way to help you understand each concept. You will also get a clear picture of reactive programming, binary searches, sorting, search trees, undirected graphs, and a whole lot more!
Table of Contents (13 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Why Bother? – Basic
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1. Why Bother? – Basic
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The performance of an algorithm
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Optimization of our algorithm
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Fixing the problem with large powers
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Summary
2
2. Cogs and Pulleys – Building Blocks
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2. Cogs and Pulleys – Building Blocks
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Arrays
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Linked list
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Doubly linked list
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Circular linked list
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Summary
3
3. Protocols – Abstract Data Types
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3. Protocols – Abstract Data Types
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Stack
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Queue
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Double ended queue
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Summary
4
4. Detour – Functional Programming
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4. Detour – Functional Programming
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Recursive algorithms
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Lambda expressions in Java
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Functional data structures and monads
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The concept of a monad
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Analysis of the complexity of a recursive algorithm
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Performance of functional programming
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Summary
5
5. Efficient Searching – Binary Search and Sorting
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5. Efficient Searching – Binary Search and Sorting
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Search algorithms
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Sorting
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A problem with recursive calls
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Summary
6
6. Efficient Sorting – quicksort and mergesort
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6. Efficient Sorting – quicksort and mergesort
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quicksort
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mergesort
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Complexity of any comparison-based sorting
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The stability of a sorting algorithm
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Summary
7
7. Concepts of Tree
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7. Concepts of Tree
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A tree data structure
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The tree abstract data type
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Binary tree
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Summary
8
8. More About Search – Search Trees and Hash Tables
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8. More About Search – Search Trees and Hash Tables
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Binary search tree
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Self-balancing binary search tree
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Red-black tree
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Hash tables
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Summary
9
9. Advanced General Purpose Data Structures
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9. Advanced General Purpose Data Structures
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Priority queue ADT
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Heap
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Linked heap
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Binomial forest
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Sorting using a priority queue
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In-place heap sort
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Summary
10
10. Concepts of Graph
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10. Concepts of Graph
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What is a graph?
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The graph ADT
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Representation of a graph in memory
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Traversal of a graph
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Cycle detection
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Spanning tree and minimum spanning tree
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Finding the minimum spanning tree
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Summary
11
11. Reactive Programming
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11. Reactive Programming
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What is reactive programming?
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Producer-consumer model
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Functional way of reactive programming
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Summary
12
Index
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Index

Representation of a graph in memory

A graph can be represented mainly in three different ways: adjacency matrix, adjacency list, and incidence matrix.

Adjacency matrix

An adjacency matrix is a matrix, a table of values, where each value represents an edge and both the rows are the columns that represent the vertices. The values in a matrix can be the members of the entry. The values of the edges can be stored in the matrix itself. There could also be a special value for representing the absence of an edge. The following image shows an adjacency matrix for the graph in Figure 1, where the value of the edge represents the number of edges between the corresponding vertices:

The following things can be noted about an adjacency matrix:

  • Rows are used to represent the sources and columns to represent the targets of the edges

  • In the case of an undirected graph, the source and target are indistinguishable, so the adjacency matrix is symmetric

The following code provides an implementation of the graph ADT...

Visually different images
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