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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.
Solution of a travelling salesman problem: the black line shows the shortest possible loop that connects every red dot. In the theory of computational complexity, the travelling salesman problem (TSP) asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the ...
The pseudocode below recursively computes the prime implicants given the list of minterms of a boolean function. It does this by trying to merge all possible minterms and filtering out minterms that have been merged until no more merges of the minterms can be performed and hence, the prime implicants of the function have been found.
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]
A simple decision tree to detect the presence of a 3-clique in a 4-vertex graph. It uses up to 6 questions of the form "Does the red edge exist?", matching the optimal bound n(n − 1)/2. The (deterministic) decision tree complexity of determining a graph property is the number of questions of the form "Is there an edge between vertex u and ...
The following pseudocode presents the simulated annealing heuristic as described above. It starts from a state s 0 and continues until a maximum of k max steps have been taken. In the process, the call neighbour( s ) should generate a randomly chosen neighbour of a given state s ; the call random(0, 1) should pick and return a value in the ...
The pseudocode DPLL function only returns whether the final assignment satisfies the formula or not. In a real implementation, the partial satisfying assignment typically is also returned on success; this can be derived by keeping track of branching literals and of the literal assignments made during unit propagation and pure literal elimination.
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