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This is a list of algorithm general topics. Analysis of algorithms; Ant colony algorithm; Approximation algorithm; Best and worst cases; Big O notation; Combinatorial search; Competitive analysis; Computability theory; Computational complexity theory; Embarrassingly parallel problem; Emergent algorithm; Evolutionary algorithm; Fast Fourier ...
An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.
Programming language – formal constructed language designed to communicate instructions to a machine, particularly a computer. Programming languages can be used to create programs to control the behavior of a machine or to express algorithms. Generational list of programming languages; List of programming languages by type
Linear programming (also treats integer programming) — objective function and constraints are linear Algorithms for linear programming: Simplex algorithm. Bland's rule — rule to avoid cycling in the simplex method; Klee–Minty cube — perturbed (hyper)cube; simplex method has exponential complexity on such a domain
Computer programming or coding is the composition of sequences of instructions, called programs, that computers can follow to perform tasks. [1] [2] It involves designing and implementing algorithms, step-by-step specifications of procedures, by writing code in one or more programming languages.
The NIST Dictionary of Algorithms and Data Structures [1] is a reference work maintained by the U.S. National Institute of Standards and Technology. It defines a large number of terms relating to algorithms and data structures. For algorithms and data structures not necessarily mentioned here, see list of algorithms and list of data structures.
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There has also been criticism of competitive programming, particularly from professional software developers. [21] One critical point is that many fast-paced programming contests teach competitors bad programming habits and code style (like unnecessary use of macros, lack of OOP abstraction and comments, use of short variable names, etc.).