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Pseudocode resembles skeleton programs, which can be compiled without errors. Flowcharts, drakon-charts and Unified Modelling Language (UML) charts can be thought of as a graphical alternative to pseudocode, but need more space on paper. Languages such as bridge the gap between pseudocode and code written in programming languages.
For example, in the for statement in the following pseudocode fragment, when calculating the new value for A(i), except for the first (with i = 2) the reference to A(i - 1) will obtain the new value that had been placed there in the previous step.
Often pseudo-code is used, which uses the common idioms of such languages without strictly adhering to the details of a particular one. Also, flowcharts are not well-suited for new programming techniques such as recursive programming. Nevertheless, flowcharts were still used in the early 21st century for describing computer algorithms. [9]
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 ...
In pseudocode the algorithm can be stated as: Begin 1) Objective function: (), = (,,...,); 2) Generate an initial population of fireflies (=,, …,);. 3) Formulate light intensity I so that it is associated with () (for example, for maximization problems, () or simply = ();) 4) Define absorption coefficient γ while (t < MaxGeneration) for i = 1 : n (all n fireflies) for j = 1 : i (n fireflies ...
The running time of this algorithm when run on a polyline consisting of n – 1 segments and n vertices is given by the recurrence T(n) = T(i + 1) + T(n − i) + O where i = 1, 2,..., n − 2 is the value of index in the pseudocode. In the worst case, i = 1 or i = n − 2 at each recursive invocation yields a running time of O(n 2).
D* (pronounced "D star") is any one of the following three related incremental search algorithms: The original D*, [1] by Anthony Stentz, is an informed incremental search algorithm.
Input: initial guess x (0) to the solution, (diagonal dominant) matrix A, right-hand side vector b, convergence criterion Output: solution when convergence is reached Comments: pseudocode based on the element-based formula above k = 0 while convergence not reached do for i := 1 step until n do σ = 0 for j := 1 step until n do if j ≠ i then ...