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Queue (abstract Data Type)
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. The operation of adding an element to the rear of the queue is known as ''enqueue'', and the operation of removing an element from the front is known as ''dequeue''. Other operations may also be allowed, often including a ''peek'' or ''front'' operation that returns the value of the next element to be dequeued without dequeuing it. The operations of a queue make it a first-in-first-out (FIFO) data structure. In a FIFO data structure, the first element added to the queue will b ...
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FIFO (computing And Electronics)
Representation of a FIFO queue In computing and in systems theory, FIFO is an acronym for first in, first out (the first in is the first out), a method for organizing the manipulation of a data structure (often, specifically a data buffer) where the oldest (first) entry, or "head" of the queue, is processed first. Such processing is analogous to servicing people in a queue area on a first-come, first-served (FCFS) basis, i.e. in the same sequence in which they arrive at the queue's tail. FCFS is also the jargon term for the FIFO operating system scheduling algorithm, which gives every process central processing unit (CPU) time in the order in which it is demanded. FIFO's opposite is LIFO, last-in-first-out, where the youngest entry or "top of the stack" is processed first. A priority queue is neither FIFO or LIFO but may adopt similar behaviour temporarily or by default. Queueing theory encompasses these methods for processing data structures, as well as interactions between s ...
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Doubly Linked List
In computer science, a doubly linked list is a linked data structure that consists of a set of sequentially linked record (computer science), records called node (computer science), nodes. Each node contains three field (computer science), fields: two link fields (reference (computer science), references to the previous and to the next node in the sequence of nodes) and one data field. The beginning and ending nodes' previous and next links, respectively, point to some kind of terminator, typically a sentinel node or null pointer, null, to facilitate traversal of the list. If there is only one sentinel node, then the list is circularly linked via the sentinel node. It can be conceptualized as two linked list, singly linked lists formed from the same data items, but in opposite sequential orders. The two node links allow traversal of the list in either direction. While adding or removing a node in a doubly linked list requires changing more links than the same operations on a sin ...
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Linked List
In computer science, a linked list is a linear collection of data elements whose order is not given by their physical placement in memory. Instead, each element points to the next. It is a data structure consisting of a collection of nodes which together represent a sequence. In its most basic form, each node contains: data, and a reference (in other words, a ''link'') to the next node in the sequence. This structure allows for efficient insertion or removal of elements from any position in the sequence during iteration. More complex variants add additional links, allowing more efficient insertion or removal of nodes at arbitrary positions. A drawback of linked lists is that access time is linear (and difficult to pipeline). Faster access, such as random access, is not feasible. Arrays have better cache locality compared to linked lists. Linked lists are among the simplest and most common data structures. They can be used to implement several other common abstract data types, in ...
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Memoization
In computing, memoization or memoisation is an optimization technique used primarily to speed up computer programs by storing the results of expensive function calls and returning the cached result when the same inputs occur again. Memoization has also been used in other contexts (and for purposes other than speed gains), such as in simple mutually recursive descent parsing. Although related to caching, memoization refers to a specific case of this optimization, distinguishing it from forms of caching such as buffering or page replacement. In the context of some logic programming languages, memoization is also known as tabling. Etymology The term "memoization" was coined by Donald Michie in 1968 and is derived from the Latin word "memorandum" ("to be remembered"), usually truncated as "memo" in American English, and thus carries the meaning of "turning he results ofa function into something to be remembered". While "memoization" might be confused with "memorization" (becaus ...
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Lazy Evaluation
In programming language theory, lazy evaluation, or call-by-need, is an evaluation strategy which delays the evaluation of an expression until its value is needed (non-strict evaluation) and which also avoids repeated evaluations (sharing). The benefits of lazy evaluation include: * The ability to define control flow (structures) as abstractions instead of primitives. * The ability to define potentially infinite data structures. This allows for more straightforward implementation of some algorithms. * The ability to define partially-defined data structures where some elements are errors. This allows for rapid prototyping. Lazy evaluation is often combined with memoization, as described in Jon Bentley's ''Writing Efficient Programs''. After a function's value is computed for that parameter or set of parameters, the result is stored in a lookup table that is indexed by the values of those parameters; the next time the function is called, the table is consulted to determine whe ...
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Persistent Data Structure
In computing, a persistent data structure or not ephemeral data structure is a data structure that always preserves the previous version of itself when it is modified. Such data structures are effectively immutable, as their operations do not (visibly) update the structure in-place, but instead always yield a new updated structure. The term was introduced in Driscoll, Sarnak, Sleator, and Tarjans' 1986 article. A data structure is partially persistent if all versions can be accessed but only the newest version can be modified. The data structure is fully persistent if every version can be both accessed and modified. If there is also a meld or merge operation that can create a new version from two previous versions, the data structure is called confluently persistent. Structures that are not persistent are called ''ephemeral''. These types of data structures are particularly common in logical and functional programming, as languages in those paradigms discourage (or fully forbid) ...
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Amortized Analysis
In computer science, amortized analysis is a method for analyzing a given algorithm's complexity, or how much of a resource, especially time or memory, it takes to execute. The motivation for amortized analysis is that looking at the worst-case run time can be too pessimistic. Instead, amortized analysis averages the running times of operations in a sequence over that sequence. As a conclusion: "Amortized analysis is a useful tool that complements other techniques such as worst-case and average-case analysis." For a given operation of an algorithm, certain situations (e.g., input parametrizations or data structure contents) may imply a significant cost in resources, whereas other situations may not be as costly. The amortized analysis considers both the costly and less costly operations together over the whole sequence of operations. This may include accounting for different types of input, length of the input, and other factors that affect its performance. History Amortized ...
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Purely Functional Data Structure
In computer science, a purely functional data structure is a data structure that can be implemented in a purely functional language. The main difference between an arbitrary data structure and a purely functional one is that the latter is (strongly) immutable. This restriction ensures the data structure possesses the advantages of immutable objects: (full) persistency, quick copy of objects, and thread safety. Efficient purely functional data structures may require the use of lazy evaluation and memoization. Definition Persistent data structures have the property of keeping previous versions of themselves unmodified. On the other hand, structures such as arrays admit a destructive update,''Purely functional ...
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JavaScript
JavaScript (), often abbreviated as JS, is a programming language that is one of the core technologies of the World Wide Web, alongside HTML and CSS. As of 2022, 98% of Website, websites use JavaScript on the Client (computing), client side for Web page, webpage behavior, often incorporating third-party Library (computing), libraries. All major Web browser, web browsers have a dedicated JavaScript engine to execute the Source code, code on User (computing), users' devices. JavaScript is a High-level programming language, high-level, often Just-in-time compilation, just-in-time compiled language that conforms to the ECMAScript standard. It has dynamic typing, Prototype-based programming, prototype-based object-oriented programming, object-orientation, and first-class functions. It is Programming paradigm, multi-paradigm, supporting Event-driven programming, event-driven, functional programming, functional, and imperative programming, imperative programming paradigm, programmin ...
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Gearman
Gearman is an open-source application framework designed to distribute appropriate computer tasks to multiple computers, so large tasks can be done more quickly. In some cases, load balancing rather than raw speed may be the main goal; a Web server, for instance, could use Gearman to send tasks for which it is not optimized to another computer (which may be running on a different architecture, using another operating system, or loaded with a computer language better suited to a particular operation). It was originally written in Perl by Brad Fitzpatrick. Brian Aker and Eric Day rewrote the framework in C. How Gearman Works Gearman assigns each involved computer a role as client, job server, or worker. A worker machine can be assigned multiple instances of the worker role, which allows more powerful computers to complete more portions of a given task. Tasks originate on a client, are transmitted from the client to the job server, and performed on one or more workers. The co ...
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Standard Template Library
The Standard Template Library (STL) is a Library (computer science), software library originally designed by Alexander Stepanov for the C++ programming language that influenced many parts of the C++ Standard Library. It provides four components called ''Algorithm (C++), algorithms'', ''Container (data structure), containers'', ''Function object, functions'', and ''iterators''. The STL provides a set of common C++ classes, classes for C++, such as containers and associative arrays, that can be used with any built-in type and with any user-defined type that supports some elementary operations (such as copying and assignment). STL algorithms are independent of containers, which significantly reduces the complexity of the library. The STL achieves its results through the use of template (programming), templates. This approach provides compile-time polymorphism that is often more efficient than traditional Polymorphism in object-oriented programming, run-time polymorphism. Modern C+ ...
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