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Pseudocode is commonly used in textbooks and scientific publications related to computer science and numerical computation to describe algorithms in a way that is accessible to programmers regardless of their familiarity with specific programming languages.
At the end of this process, if the sequence has a majority, it will be the element stored by the algorithm. This can be expressed in pseudocode as the following steps: Initialize an element m and a counter c with c = 0; For each element x of the input sequence: If c = 0, then assign m = x and c = 1; else if m = x, then assign c = c + 1; else ...
The subset sum problem (SSP) is a decision problem in computer science.In its most general formulation, there is a multiset of integers and a target-sum , and the question is to decide whether any subset of the integers sum to precisely . [1]
Pseudocode is similar to skeleton programming, however deviates in the fact that pseudocode is primarily an informal method of programming. [3] Dummy code is also very similar to this, where code is used simply as a placeholder, or to signify the intended existence of a method in a class or interface.
Bruce Ballard was the first to develop a technique, called *-minimax, that enables alpha-beta pruning in expectiminimax trees. [3] [4] The problem with integrating alpha-beta pruning into the expectiminimax algorithm is that the scores of a chance node's children may exceed the alpha or beta bound of its parent, even if the weighted value of each child does not.
Dekker's algorithm is the first known correct solution to the mutual exclusion problem in concurrent programming where processes only communicate via shared memory. The solution is attributed to Dutch mathematician Th. J. Dekker by Edsger W. Dijkstra in an unpublished paper on sequential process descriptions [1] and his manuscript on cooperating sequential processes. [2]
From this definition we can derive straightforward recursive code for q(i, j). In the following pseudocode, n is the size of the board, c(i, j) is the cost function, and min() returns the minimum of a number of values:
The basic form of the Bron–Kerbosch algorithm is a recursive backtracking algorithm that searches for all maximal cliques in a given graph G.More generally, given three disjoint sets of vertices R, P, and X, it finds the maximal cliques that include all of the vertices in R, some of the vertices in P, and none of the vertices in X.