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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.
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.
Elements are distributed among bins Then, elements are sorted within each bin. Bucket sort, or bin sort, is a sorting algorithm that works by distributing the elements of an array into a number of buckets.
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 ...
This section gives pseudocode for adding or removing nodes from singly, doubly, and circularly linked lists in-place. Throughout, null is used to refer to an end-of-list marker or sentinel , which may be implemented in a number of ways.
The heapsort algorithm can be divided into two phases: heap construction, and heap extraction. The heap is an implicit data structure which takes no space beyond the array of objects to be sorted; the array is interpreted as a complete binary tree where each array element is a node and each node's parent and child links are defined by simple arithmetic on the array indexes.
Backtracking is a class of algorithms for finding solutions to some computational problems, notably constraint satisfaction problems, that incrementally builds candidates to the solutions, and abandons a candidate ("backtracks") as soon as it determines that the candidate cannot possibly be completed to a valid solution.
This pseudocode illustrates the concept algorithmically: . function quiescence_search(node, (optional) depth) is if node appears quiet or node is a terminal node or depth = 0 then return estimated value of node else (recursively search node children with quiescence_search) return estimated value of children function normal_search(node, depth) is if node is a terminal node then return estimated ...