In computer science, adata structure is a particular way of storing and organizing data in a computer so that it can be used efficiently. Different kinds of data structures are suited to different kinds of applications, and some are highly specialized to specific tasks. For example, B-trees are particularly well-suited for implementation of databases, while compiler implementations usually use hash tables to look up identifiers. Data structures are used in almost every program or software system. Specific data structures are essential ingredients of many efficient algorithms, and make possible the management of huge amounts of data, such as large databases and internet indexing services. Some formal design methods and programming languages emphasize data structures, rather than algorithms, as the key organizing factor in software design.
Data structures are generally based on the ability of a computer to fetch and store data at any place in its memory, specified by an address — a bit string that can be itself stored in memory and manipulated by the program. Thus the record and array data structures are based on computing the addresses of data items with arithmetic operations; while the linked data structures are based on storing addresses of data items within the structure itself. Many data structures use both principles, sometimes combined in non-trivial ways (as in XOR linking).
Abstract data structures
The implementation of a data structure usually requires writing a set of procedures that create and manipulate instances of that structure. The efficiency of a data structure cannot be analyzed separately from those operations. This observation motivates the theoretical concept of an abstract data type, a data structure that is defined indirectly by the operations that may be performed on it, and the mathematical properties of those operations (including their space and time cost).
Assembly languages and some low-level languages, such as BCPL, generally lack support for data structures. Many high-level programming languages, on the other hand, have special syntax or other built-in support for certain data structures, such as vectors (one-dimensional arrays) in the C programming language, multi-dimensional arrays in Pascal, linked lists in Common Lisp, and hash tables in Perl and in Python. Many languages also provide basic facilities such as references and the definition record data types, that programmers can use to build arbitrarily complex structures. Most programming languages feature some sort of library mechanism that allows data structure implementations to be reused by different programs. Modern programming languages usually come with standard libraries that implement the most common data structures. Examples are the C++ Standard Template Library, the Java Collections Framework, and Microsoft's .NET Framework. Modern languages also generally support modular programming, the separation between the interface of a library module and its implementation. Some provide opaque data types that allow clients to hide implementation details.
Object-oriented programming languages, such as C++, .NET Framework and Java, use classes for this purpose. With the advent of multi-core processors, many known data structures have concurrent versions that allow multiple computing threads to access the data structure simultaneously.
Classification of data structure
Primitive / Non-primitive: Primitive data structures are basic data structure and are directly operated upon machine instructions, e.g., integer, character. Non-primitive data structures are derived from primitive data structures, e.g., structure, union, array.
Homogeneous / Heterogeneous: In homogeneous data structures all elements are of the same type, e.g., array. In heterogeneous data structures elements are of different types, e.g. structure.
Static / Dynamic: In static data structures memory is allocated at the time of compilation. In dynamic data structures memory is allocated at run-time, throught functions such as malloc, calloc, etc.
Linear / Non-linear: Linear data structures maintain a linear relationship between their elements, e.g., array. Non-linear data structures do not maintain any linear relationship between their elements, e.g., in a tree.jj
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