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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 Implementation s thus cannot be operated on directly. 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 Function s accepting the abstract handle as an argument. Majority of typical ADTs have set operations and they are sometimes called '''dynamic sets'''. EXAMPLES ADTs typically seen in textbooks and implemented in programming languages (or their libraries) include: 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 and understood 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 the implementation in a concrete Data Structure . Selection of an abstract data structure is crucial in design of efficient Algorithm s 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 abstract data type, used in theory of Programming Language s. A close notion of Data Model additionally considers the pattern of interrelations between data elements ( Structure of the data structure, however awkward that may sound). 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 are building implementations of ADTs into the language as native types or adding 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 provides classes that implement the List, Stack, Queue, Map, Priority Queue, and String ADTs. CONCRETE EXAMPLES Rational numbers as an abstract data type For example, Rational Number s (numbers that can be written in the form a/b where a and b are integers) cannot be represented natively in a computer. A Rational ADT could be defined as shown below. Construction: Create an instance of a rational number ADT using two integers, a and b, where a represents the numerator and b represents the denominator. Operations: addition, subtraction, multiplication, division, exponentiation, comparison, simplify, conversion to a real (floating point) number. To be a complete specification, each operation should be defined in terms of the data. For example, when multiplying two rational numbers a/b and c/d, the result is defined as ac/bd. Typically, inputs, outputs, preconditions, postconditions, and assumptions to the ADT are specified as well. Stack Interface In a more concrete example, written in C-style notation, the interface for a Stack ADT might be:
Usage This ADT could be used in the following manner: long stack;
Implementation variants The above stack ADT could be initially implemented using an array, and then later changed to a linked list, without affecting any user code. The number of ways a given ADT can be implemented depends on the programming language. For example, the above example could be written in C using a struct and an accompanying set of data structures using arrays or linked lists to store the entries; however, since the constructor function returns an abstract handle, the actual implementation is hidden from the user. In object-oriented languages such as C++ and Java, ADTs are typically represented using the class construct where the data is represented by data members (attributes) and the operations are represented by member functions (methods). In addition, some languages such as C++ and Java provide a mechanism of enforcement (the private or protected keywords) to only allow the defined functions to operate on the data. When using object-oriented ADTs, the user can often expand the ADT by creating a subclass of the ADT. |
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