Different kinds of data structures are suited to different kinds of applications, and some are highly specialized to certain tasks. For example, B-trees are particularly well-suited for implementation of databases, while networks of machines rely on routing tables to function.
In the design of many types of programs, the choice of data structures is a primary design consideration, as experience in building large systems has shown that the difficulty of implementation and the quality and performance of the final result depends heavily on choosing the best data structure. After the data structures are chosen, the algorithms to be used often become relatively obvious. Sometimes things work in the opposite direction — data structures are chosen because certain key tasks have algorithms that work best with particular data structures. In either case, the choice of appropriate data structures is crucial.
This insight has given rise to many formalised design methods and programming languages in which data structures, rather than algorithms, are the key organising factor. Most languages feature some sort of module system, allowing data structures to be safely reused in different applications by hiding their verified implementation details behind controlled interfaces. Object-oriented programming languages such as C++ and Java in particular use classes for this purpose.
Since data structures are so crucial, many of them are included in standard libraries of modern programming languages and environments, such as C++'s Standard Template Library containers, the Java Collections Framework, and the Microsoft .NET Framework.
The fundamental building blocks of most data structures are arrays, records, discriminated unions, and references. For example, the nullable reference, a reference which can be null, is a combination of references and discriminated unions, and the simplest linked data structure, the linked list, is built from records and nullable references.
Data structures represent implementations or interfaces: A data structure can be viewed as an interface between two functions or as an implementation of methods to access storage that is organized according to the associated data type.
US Patent Issued to NetApp on May 28 for "Update of Data Structure Configured to Store Metadata Associated with a Database System" (Indian Inventors)
May 28, 2013; ALEXANDRIA, Va., May 28 -- United States Patent no. 8,452,817, issued on May 28, was assigned to NetApp Inc. (Sunnyvale,...