In computer science, a data structure is a data organization and storage format that is usually chosen for efficient access to data. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data, i.e., it is an algebraic structure about data.
In computer science, a hash table is a data structure that implements an associative array, also called a dictionary or simply map; an associative array is an abstract data type that maps keys to values. A hash table uses a hash function to compute an index, also called a hash code, into an array of buckets or slots, from which the desired value can be found. During lookup, the key is hashed and the resulting hash indicates where the corresponding value is stored. A map implemented by a hash table is called a hash map.
In computer science, a heap is a tree-based data structure that satisfies the heap property: In a max heap, for any given node C, if P is the parent node of C, then the key of P is greater than or equal to the key of C. In a min heap, the key of P is less than or equal to the key of C. The node at the "top" of the heap is called the root node.
In computer science, a priority queue is an abstract data type similar to a regular queue or stack abstract data type. Each element in a priority queue has an associated priority. In a priority queue, elements with high priority are served before elements with low priority. In some implementations, if two elements have the same priority, they are served in the same order in which they were enqueued. In other implementations, the order of elements with the same priority is undefined.
In computer science, a queue is a collection of entities that are maintained in a sequence and can be modified by the addition of entities at one end of the sequence and the removal of entities from the other end of the sequence. By convention, the end of the sequence at which elements are added is called the back, tail, or rear of the queue, and the end at which elements are removed is called the head or front of the queue, analogously to the words used when people line up to wait for goods or services.
In computer science, an associative array, map, symbol table, or dictionary is an abstract data type that stores a collection of pairs, such that each possible key appears at most once in the collection. In mathematical terms, an associative array is a function with finite domain. It supports 'lookup', 'remove', and 'insert' operations.
In computer programming, an iterator is an object that progressively provides access to each item of a collection, in order.
In object-oriented (OO) and functional programming, an immutable object is an object whose state cannot be modified after it is created. This is in contrast to a mutable object, which can be modified after it is created. In some cases, an object is considered immutable even if some internally used attributes change, but the object's state appears unchanging from an external point of view. For example, an object that uses memoization to cache the results of expensive computations could still be considered an immutable object.
In computer science, a set is an abstract data type that can store unique values, without any particular order. It is a computer implementation of the mathematical concept of a finite set. Unlike most other collection types, rather than retrieving a specific element from a set, one typically tests a value for membership in a set.
In computer programming, a weak reference is a reference that does not protect the referenced object from collection by a garbage collector, unlike a strong reference. An object referenced only by weak references – meaning "every chain of references that reaches the object includes at least one weak reference as a link" – is considered weakly reachable, and can be treated as unreachable and so may be collected at any time. Some garbage-collected languages feature or support various levels of weak references, such as C#, Lua, Java, Lisp, OCaml, MATLAB, Perl, Python and PHP since the version 7.4.
In computer programming, foreach loop is a control flow statement for traversing items in a collection. foreach is usually used in place of a standard for loop statement. Unlike other for loop constructs, however, foreach loops usually maintain no explicit counter: they essentially say "do this to everything in this set", rather than "do this x times". This avoids potential off-by-one errors and makes code simpler to read. In object-oriented languages, an iterator, even if implicit, is often used as the means of traversal.
A bit array is an array data structure that compactly stores bits. It can be used to implement a simple set data structure. A bit array is effective at exploiting bit-level parallelism in hardware to perform operations quickly. A typical bit array stores kw bits, where w is the number of bits in the unit of storage, such as a byte or word, and k is some nonnegative integer. If w does not divide the number of bits to be stored, some space is wasted due to internal fragmentation.
In computer science, a dynamic array, growable array, resizable array, dynamic table, mutable array, or array list is a random access, variable-size list data structure that allows elements to be added or removed. It is supplied with standard libraries in many modern mainstream programming languages. Dynamic arrays overcome a limit of static arrays, which have a fixed capacity that needs to be specified at allocation.
In computer science, a multimap is a generalization of a map or associative array abstract data type in which more than one value may be associated with and returned for a given key. Both map and multimap are particular cases of containers. Often the multimap is implemented as a map with lists or sets as the map values.
The Java collections framework is a set of classes and interfaces that implement commonly reusable collection data structures.
This comparison of programming languages (associative arrays) compares the features of associative array data structures or array-lookup processing for over 40 computer programming languages.
OptimJ is an extension for Java with language support for writing optimization models and abstractions for bulk data processing. The extensions and the proprietary product implementing the extensions were developed by Ateji which went out of business in September 2011. OptimJ aims at providing a clear and concise algebraic notation for optimization modeling, removing compatibility barriers between optimization modeling and application programming tools, and bringing software engineering techniques such as object-orientation and modern IDE support to optimization experts.
Rust is a general-purpose programming language emphasizing performance, type safety, and concurrency. It enforces memory safety, meaning that all references point to valid memory. It does so without a traditional garbage collector; instead, memory safety errors and data races are prevented by the "borrow checker", which tracks the object lifetime of references at compile time.
Nim is a general-purpose, multi-paradigm, statically typed, compiled high-level system programming language, designed and developed by a team around Andreas Rumpf. Nim is designed to be "efficient, expressive, and elegant", supporting metaprogramming, functional, message passing, procedural, and object-oriented programming styles by providing several features such as compile time code generation, algebraic data types, a foreign function interface (FFI) with C, C++, Objective-C, and JavaScript, and supporting compiling to those same languages as intermediate representations.
