#Data structures in java tutorial code#
#Data structures in java tutorial series#

MyDeque is a class that implements Deque. Note that Stack and Deque are interfaces that describe Stack and Deque ADTs. Listing 1 excerpts the Brown University paper's DequeStack class, which demonstrates the Adapter pattern. Throw new Object pop() throws StackEmptyException Return void push(Object Object top() throws StackEmptyException Using the Adapter pattern for stacks and queues (DequeStack.java) public class DequeStack implements Stackĭeque D // holds the elements of the stack

#Data structures in java tutorial code#

The demonstration code is shown in Listing 1. Among other things, the paper demonstrates that the Adapter pattern is useful for designing stacks and queues. A Brown University paper surveys several design patterns that are useful for designing high-quality data structures. It's become fairly common to use design patterns to introduce university students to data structures.

#Data structures in java tutorial series#

This series will help you better understand this framework.

The Java Collections Framework supports many kinds of container-oriented data structures and associated algorithms. Data structures and algorithms in Java Collections I refer to this latter category of data structures as containers.Īs well as being aggregates, all of the data structures we'll look at in this series are containers. For example, an array can store primitive values or object references. In contrast, some data structures exist as generic storage vessels for other data structures. Instances of an Employee class are data structures that exist to describe various employees, for instance. Many data structures are designed to describe various entities. Examples include the data structures derived from the previously mentioned Employee, Vehicle, Array, and List ADTs. ContainersĪnything from which data items are stored and retrieved could be considered a data structure. I refer to these data structures as aggregates.Īll of the data structures we'll look at in this series are aggregates. For example, an array can store multiple data items in its various slots, and an object can store multiple data items via its fields. Many data structures are capable of storing multiple data items. I refer to such data structures as primitives. The simplest kind of data structure stores single data items for example, a variable that stores a Boolean value or a variable that stores an integer.

All data structures can be classified as primitives or aggregates, and some are classified as containers. There are many kinds of data structures, ranging from single variables to arrays or linked lists of objects containing multiple fields. (You'll be introduced to arrays in Part 2, and linked lists in Part 3.) Classifying data structures

Appending a value to the end of the listĭata structures that can implement the List ADT include fixed-size and dynamically sized one-dimensional arrays and singly-linked lists.

Basic operations supported by the List ADT include: Each element in this collection has its own position and duplicate elements are allowed.

Consider the List ADT (also known as the Sequence ADT), which describes an ordered collection of elements that share a common type. In contrast, a data structure is a concrete implementation of one or more ADTs, similar to how Java classes implement interfaces.Įxamples of ADTs include Employee, Vehicle, Array, and List. It's like a Java interface, which is a data type that's disconnected from any implementation.

Mathematical model for data types where a data type is defined by its behavior (semantics) from the point of view of a user of the data, specifically in terms of possible values, possible operations on data of this type, and the behavior of these operations.Īn ADT doesn't care about the memory representation of its values or how its operations are implemented.