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For a more comprehensive listing of data structures, see List of data structures. The comparisons in this article are organized by abstract data type . As a single concrete data structure may be used to implement many abstract data types, some data structures may appear in multiple comparisons (for example, a hash map can be used to implement ...
java.util.Collection class and interface hierarchy Java's java.util.Map class and interface hierarchy. The Java collections framework is a set of classes and interfaces that implement commonly reusable collection data structures. [1] Although referred to as a framework, it works in a manner of a library. The collections framework provides both ...
Algorithms + Data Structures = Programs [1] is a 1976 book written by Niklaus Wirth covering some of the fundamental topics of system engineering, computer programming, particularly that algorithms and data structures are inherently related.
It should be possible to define a new operation for (some) classes of an object structure without changing the classes. When new operations are needed frequently and the object structure consists of many unrelated classes, it's inflexible to add new subclasses each time a new operation is required because "[..] distributing all these operations across the various node classes leads to a system ...
Concurrent data structures are significantly more difficult to design and to verify as being correct than their sequential counterparts. The primary source of this additional difficulty is concurrency, exacerbated by the fact that threads must be thought of as being completely asynchronous: they are subject to operating system preemption, page faults, interrupts, and so on.
Unlike general lossless data compression algorithms, succinct data structures retain the ability to use them in-place, without decompressing them first. A related notion is that of a compressed data structure, insofar as the size of the stored or encoded data similarly depends upon the specific content of the data itself.
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In computer science, a disjoint-set data structure, also called a union–find data structure or merge–find set, is a data structure that stores a collection of disjoint (non-overlapping) sets. Equivalently, it stores a partition of a set into disjoint subsets .