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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.
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]
Example of a Nassi–Shneiderman diagram. A Nassi–Shneiderman diagram (NSD) in computer programming is a graphical design representation for structured programming. [1] This type of diagram was developed in 1972 by Isaac Nassi and Ben Shneiderman who were both graduate students at Stony Brook University. [2]
A line rendered in this way exhibits some special properties that may be taken advantage of. For example, in cases like this, sections of the line are periodical. This results in an algorithm which is significantly faster than precise variants, especially for longer lines. A worsening in quality is only visible on lines with very low steepness.
Here is a very simple and explicit group of pseudocode that can be easily understood by the layman: [citation needed] Kp - proportional gain; Ki - integral gain; Kd - derivative gain; dt - loop interval time (assumes reasonable scale) [b]
Best-first search is a class of search algorithms which explores a graph by expanding the most promising node chosen according to a specified rule.. Judea Pearl described best-first search as estimating the promise of node n by a "heuristic evaluation function () which, in general, may depend on the description of n, the description of the goal, the information gathered by the search up to ...
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 ...
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).