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Slowsort
Slowsort is a sorting algorithm. It is of humorous nature and not useful. It is a ''reluctant algorithm'' based on the principle of ''multiply and surrender'' (a parody formed by taking the opposites of '' divide and conquer''). It was published in 1986 by Andrei Broder and Jorge Stolfi in their paper ''Pessimal Algorithms and Simplexity Analysis'' (a parody of '' optimal algorithms'' and ''complexity analysis''). Algorithm Slowsort is a recursive algorithm. * It sorts in-place. * It is a stable sort. (It does not change the order of equal-valued keys.) This is an implementation in pseudocode: procedure slowsort(A[], start_idx, end_idx) // Sort array range A[start ... end] in-place. if start_idx ≥ end_idx then return middle_idx := floor( (start_idx + end_idx)/2 ) slowsort(A, start_idx, middle_idx) // (1.1) slowsort(A, middle_idx + 1, end_idx) // (1.2) if A nd_idx -> slowsort xs , length xs 0. Slowsort is therefore ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sorting Algorithm
In computer science, a sorting algorithm is an algorithm that puts elements of a List (computing), list into an Total order, order. The most frequently used orders are numerical order and lexicographical order, and either ascending or descending. Efficient sorting is important for optimizing the Algorithmic efficiency, efficiency of other algorithms (such as search algorithm, search and merge algorithm, merge algorithms) that require input data to be in sorted lists. Sorting is also often useful for Canonicalization, canonicalizing data and for producing human-readable output. Formally, the output of any sorting algorithm must satisfy two conditions: # The output is in monotonic order (each element is no smaller/larger than the previous element, according to the required order). # The output is a permutation (a reordering, yet retaining all of the original elements) of the input. For optimum efficiency, the input data should be stored in a data structure which allows random access ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer Humor
Computer humour, also known as hacker humour, is humour on the subject of computers or their users. Examples Examples of computer humour include: *"Any key", taken to mean pressing the (non-existent) "Any" key rather than any key *April Fools' Day Request for Comments *Bastard Operator From Hell, a fictional rogue computer operator *Blinkenlights, a neologism for diagnostic lights *Bogosort, a portmanteau of the words bogus and sort *COMEFROM, an obscure programming language control flow structure, originally as a joke *"The Complexity of Songs", a journal article published by computer scientist Donald Knuth in 1977 as an in-joke about computational complexity theory *''The Computer Contradictionary'', a non-fiction book by Stan Kelly-Bootle that compiles a satirical list of definitions of computer industry terms *''The Daily WTF'', a humorous blog dedicated to "Curious Perversions in Information Technology" *''Dilbert'', an American comic strip *Easter egg (media), Easter egg, an ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parody
A parody, also known as a spoof, a satire, a send-up, a take-off, a lampoon, a play on (something), or a caricature, is a creative work designed to imitate, comment on, and/or mock its subject by means of satiric or ironic imitation. Often its subject is an original work or some aspect of it (theme/content, author, style, etc), but a parody can also be about a real-life person (e.g. a politician), event, or movement (e.g. the French Revolution or 1960s counterculture). Literary scholar Professor Simon Dentith defines parody as "any cultural practice which provides a relatively polemical allusive imitation of another cultural production or practice". The literary theorist Linda Hutcheon said "parody ... is imitation, not always at the expense of the parodied text." Parody may be found in art or culture, including literature, music, theater, television and film, animation, and gaming. Some parody is practiced in theater. The writer and critic John Gross observes in his ''Oxford Boo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Opposite (semantics)
In lexical semantics, opposites are words lying in an inherently incompatible binary relationship. For example, something that is ''long'' entails that it is not ''short''. It is referred to as a 'binary' relationship because there are two members in a set of opposites. The relationship between opposites is known as opposition. A member of a pair of opposites can generally be determined by the question ''What is the opposite of X ?'' The term antonym (and the related antonymy) is commonly taken to be synonymous with opposite, but antonym also has other more restricted meanings. Graded (or gradable) antonyms are word pairs whose meanings are opposite and which lie on a continuous spectrum (hot, cold). Complementary antonyms are word pairs whose meanings are opposite but whose meanings do not lie on a continuous spectrum (''push'', ''pull''). Relational antonyms are word pairs where opposite makes sense only in the context of the relationship between the two meanings (''tea ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Divide-and-conquer Algorithm
In computer science, divide and conquer is an algorithm design paradigm. A divide-and-conquer algorithm recursively breaks down a problem into two or more sub-problems of the same or related type, until these become simple enough to be solved directly. The solutions to the sub-problems are then combined to give a solution to the original problem. The divide-and-conquer technique is the basis of efficient algorithms for many problems, such as sorting (e.g., quicksort, merge sort), multiplying large numbers (e.g., the Karatsuba algorithm), finding the closest pair of points, syntactic analysis (e.g., top-down parsers), and computing the discrete Fourier transform (FFT). Designing efficient divide-and-conquer algorithms can be difficult. As in mathematical induction, it is often necessary to generalize the problem to make it amenable to a recursive solution. The correctness of a divide-and-conquer algorithm is usually proved by mathematical induction, and its computational cost is o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Asymptotically Optimal Algorithm
In computer science, an algorithm is said to be asymptotically optimal if, roughly speaking, for large inputs it performs at worst a constant factor (independent of the input size) worse than the best possible algorithm. It is a term commonly encountered in computer science research as a result of widespread use of big-O notation. More formally, an algorithm is asymptotically optimal with respect to a particular resource if the problem has been proven to require of that resource, and the algorithm has been proven to use only These proofs require an assumption of a particular model of computation, i.e., certain restrictions on operations allowable with the input data. As a simple example, it's known that all comparison sorts require at least comparisons in the average and worst cases. Mergesort and heapsort are comparison sorts which perform comparisons, so they are asymptotically optimal in this sense. If the input data have some ''a priori'' properties which can be expl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computational Complexity Theory
In theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as an algorithm. A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used. The theory formalizes this intuition, by introducing mathematical models of computation to study these problems and quantifying their computational complexity, i.e., the amount of resources needed to solve them, such as time and storage. Other measures of complexity are also used, such as the amount of communication (used in communication complexity), the number of gates in a circuit (used in circuit complexity) and the number of processors (used in parallel computing). One of the roles of computationa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recursive Algorithm
In computer science, recursion is a method of solving a computational problem where the solution depends on solutions to smaller instances of the same problem. Recursion solves such recursive problems by using functions that call themselves from within their own code. The approach can be applied to many types of problems, and recursion is one of the central ideas of computer science. Most computer programming languages support recursion by allowing a function to call itself from within its own code. Some functional programming languages (for instance, Clojure) do not define any looping constructs but rely solely on recursion to repeatedly call code. It is proved in computability theory that these recursive-only languages are Turing complete; this means that they are as powerful (they can be used to solve the same problems) as imperative languages based on control structures such as and . Repeatedly calling a function from within itself may cause the call stack to have a s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
In-place Algorithm
In computer science, an in-place algorithm is an algorithm which transforms input using no auxiliary data structure. However, a small amount of extra storage space is allowed for auxiliary variables. The input is usually overwritten by the output as the algorithm executes. An in-place algorithm updates its input sequence only through replacement or swapping of elements. An algorithm which is not in-place is sometimes called not-in-place or out-of-place. In-place can have slightly different meanings. In its strictest form, the algorithm can only have a constant amount of extra space, counting everything including function calls and pointers. However, this form is very limited as simply having an index to a length array requires bits. More broadly, in-place means that the algorithm does not use extra space for manipulating the input but may require a small though nonconstant extra space for its operation. Usually, this space is , though sometimes anything in is allowed. Note tha ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Haskell (programming Language)
Haskell () is a general-purpose, statically-typed, purely functional programming language with type inference and lazy evaluation. Designed for teaching, research and industrial applications, Haskell has pioneered a number of programming language features such as type classes, which enable type-safe operator overloading, and monadic IO. Haskell's main implementation is the Glasgow Haskell Compiler (GHC). It is named after logician Haskell Curry. Haskell's semantics are historically based on those of the Miranda programming language, which served to focus the efforts of the initial Haskell working group. The last formal specification of the language was made in July 2010, while the development of GHC continues to expand Haskell via language extensions. Haskell is used in academia and industry. , Haskell was the 28th most popular programming language by Google searches for tutorials, and made up less than 1% of active users on the GitHub source code repository. History ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Asymptotic Bound
Big ''O'' notation is a mathematical notation that describes the limiting behavior of a function when the argument tends towards a particular value or infinity. Big O is a member of a family of notations invented by Paul Bachmann, Edmund Landau, and others, collectively called Bachmann–Landau notation or asymptotic notation. The letter O was chosen by Bachmann to stand for ''Ordnung'', meaning the order of approximation. In computer science, big O notation is used to classify algorithms according to how their run time or space requirements grow as the input size grows. In analytic number theory, big O notation is often used to express a bound on the difference between an arithmetical function and a better understood approximation; a famous example of such a difference is the remainder term in the prime number theorem. Big O notation is also used in many other fields to provide similar estimates. Big O notation characterizes functions according to their growth rates: diff ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Landau Notation
Big ''O'' notation is a mathematical notation that describes the limiting behavior of a function when the argument tends towards a particular value or infinity. Big O is a member of a family of notations invented by Paul Bachmann, Edmund Landau, and others, collectively called Bachmann–Landau notation or asymptotic notation. The letter O was chosen by Bachmann to stand for ''Ordnung'', meaning the order of approximation. In computer science, big O notation is used to classify algorithms according to how their run time or space requirements grow as the input size grows. In analytic number theory, big O notation is often used to express a bound on the difference between an arithmetical function and a better understood approximation; a famous example of such a difference is the remainder term in the prime number theorem. Big O notation is also used in many other fields to provide similar estimates. Big O notation characterizes functions according to their growth rates: diff ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
