LinuxHPC.org/Cluster Builder 1.2

Abstract Data Type

In computing, an abstract data type (ADT) is a specification of a set of data and the set of operations that can be performed on the data. Such a data type is abstract in the sense that it is independent of various concrete implementations. The definition can be mathematical, or it can be programmed as an interface. The interface provides a constructor, which returns an abstract handle to new data, and several operations, which are functions accepting the abstract handle as an argument.

Examples

ADTs typically seen in textbooks and implemented in programming languages (or their libraries) include:

String
List
Linked List
Stack
Queue
Binary search tree
Priority queue
Complex number
Associative array
Multimap

Separation of interface and implementation

When realized in a computer program, the ADT is represented by an interface, which shields a corresponding implementation. Users of an ADT are concerned with the interface, but not the implementation, as the implementation can change in the future. (This supports the principle of information hiding, or protecting the program from design decisions that are subject to change.)

The strength of an ADT is that the implementation is hidden from the user. Only the interface is published. This means that the ADT can be implemented in various ways, but as long as it adheres to the interface, user programs are unaffected.

There is a distinction, although sometimes subtle, between the abstract data type and the data structure used in its implementation. For example, a List ADT can be represented using an array-based implementation or a linked-list implementation. A List is an abstract data type with well-defined operations (add element, remove element, etc.) while a linked-list is a pointer-based data structure that can be used to create a representation of a List. The linked-list implementation is so commonly used to represent a List ADT that the terms are interchanged in common use.

Similarly, a Binary Search Tree ADT can be represented in several ways: binary tree, AVL tree, red-black tree, array, etc. Regardless of the implementation, the Binary Search Tree always has the same operations (insert, remove, find, etc.)

Abstract data structure

An abstract data structure is an abstract storage for data defined in terms of the set of operations to be performed on data and computational complexity for performing these operations, regardless of the implementation in a concrete data structure.

Selection of an abstract data structure is crucial in the design of efficient algorithms and in estimating their computational complexity, while selection of concrete data structures is important for efficient implementation of algorithms.

This notion is very close to that of an abstract data type, used in the theory of programming languages. The names of many abstract data structures (and abstract data types) match the names of concrete data structures.

Built-in abstract data types

Because some ADTs are so common and useful in computer programs, some programming languages build implementations of ADTs into the language as native types or add them into their standard libraries. For instance, Perl arrays can be thought of as an implementation of the List or Deque ADTs and Perl hashes can be thought of in terms of Map or Table ADTs. The C++ Standard Library and Java libraries provide classes that implement the List, Stack, Queue, Map, Priority Queue, and String ADTs.

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