This book is about the creation and analysis of efficient data structures. It covers:

the primitive node structure;

structure; asymptotic notation for mathematically discussing performance characteristics;

for mathematically discussing performance characteristics; built-in arrays ;

; list structures built from either nodes or arrays;

built from either nodes or arrays; iterators as an abstract model of enumerating the items in a sequence;

as an abstract model of enumerating the items in a sequence; stacks and queues for computing with last-in/first-out and first-in/first-out orderings;

and for computing with last-in/first-out and first-in/first-out orderings; binary and general tree structures for searching or representing hierarchical relationships;

structures for searching or representing hierarchical relationships; min and max heaps for representing ordering based on priorities;

for representing ordering based on priorities; graph structures for representing more general relationships between data elements;

structures for representing more general relationships between data elements; hash tables for the efficient retrieval of strings and other objects; and finally

for the efficient retrieval of strings and other objects; and finally trade-offs between the structures, and strategies for picking the most appropriate ones.

To understand the material in this book you should be comfortable enough in a programming language to be capable of working with and writing your own variables, arithmetic expressions, if-else conditions, loops, subroutines (also known as functions), pointers (also known as references or object handles), structures (also known as records or classes), simple input and output, and simple recursion.

Because many different languages approach the construction of data structures differently, we use pseudo-code so that you can translate the code into your own language.

Table of Chapters [ edit ]

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This book is intentionally kept narrow-in-focus in order to make contributions easier (because then the end-goal is clearer). This book is part one of a series of three computer science textbooks on algorithms, continuing on to the techniques of algorithms in Algorithms and ending with Advanced Data Structures and Algorithms. If you would like to contribute a topic not already listed in any of the three books try putting it in the Advanced book, which is more eclectic in nature. Or, if you think the topic is fundamental, you can go to either the Algorithms or the Data Structures discussion page and make a proposal.

Additionally, implementations of the data structures (in either Ada, C, C#, Perl, Python, Java, Ruby, or Scheme) as an appendix are welcome.

References [ edit ]

[Aho] Alfred V. Aho, Jeffrey D. Ullman, John E. Hopcroft. Data Structures and Algorithms. Addison Wesley, 1983. [CLRS] Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein. Introduction to Algorithms. McGraw-Hill, 2001. [Knuth] Donald E. Knuth. The Art of Computer Programming, Volumes 1-3. Addison-Wesley Professional, 1998. [Kishor] S.B. Kishor Data Structures, Edition 3. Das Ganu Prakashan, Nagpur, 2008. [Judith] Judith L Gersting. Mathematical Structures for Computer Science. W.H. Freeman and Company,2014.

Additionally, as an online reference to the scope of algorithms today: Dictionary of Algorithms