Like hash tables, binary search trees are fast lookup data structures for organizing key value pairs and implement the data dictionary operations. In addition to providing insert, search, and delete, binary tree supports efficient querying such as finding minimum and maximum, successor, and predecessor. When using balanced binary search trees, insert and search operations have a worst-case runtime complexity of O(log n). This is a big theoretical improvement over the worst-case scenario of a hash table, which is O(n).
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Beginning Java Data Structures and Algorithms
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Beginning Java Data Structures and Algorithms
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Overview of this book
Learning about data structures and algorithms gives you a better insight on how to solve common programming problems. Most of the problems faced everyday by programmers have been solved, tried, and tested. By knowing how these solutions work, you can ensure that you choose the right tool when you face these problems.
This book teaches you tools that you can use to build efficient applications. It starts with an introduction to algorithms and big O notation, later explains bubble, merge, quicksort, and other popular programming patterns. You’ll also learn about data structures such as binary trees, hash tables, and graphs. The book progresses to advanced concepts, such as algorithm design paradigms and graph theory. By the end of the book, you will know how to correctly implement common algorithms and data structures within your applications.
Table of Contents (8 chapters)
Preface
Free Chapter
Algorithms and Complexities
Sorting Algorithms and Fundamental Data Structures
Hash Tables and Binary Search Trees
Algorithm Design Paradigms
String Matching Algorithms
Graphs, Prime Numbers, and Complexity Classes
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