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In computer programming, foreach loop (or for-each loop) is a control flow statement for traversing items in a collection. ... test (or a hasOwn() ...
To see this, assume that there is an algorithm PHSR ("partial halting solver recognizer") to do that. Then it can be used to solve the halting problem, as follows: To test whether input program x halts on y, construct a program p that on input (x,y) reports true and diverges on all other inputs. Then test p with PHSR.
Peephole optimization is an optimization technique performed on a small set of compiler-generated instructions, known as a peephole or window, [1] [2] that involves replacing the instructions with a logically equivalent set that has better performance.
First, it can be false in practice. A theoretical polynomial algorithm may have extremely large constant factors or exponents, rendering it impractical. For example, the problem of deciding whether a graph G contains H as a minor , where H is fixed, can be solved in a running time of O ( n 2 ), [ 25 ] where n is the number of vertices in G .
Robot in a wooden maze. A maze-solving algorithm is an automated method for solving a maze.The random mouse, wall follower, Pledge, and Trémaux's algorithms are designed to be used inside the maze by a traveler with no prior knowledge of the maze, whereas the dead-end filling and shortest path algorithms are designed to be used by a person or computer program that can see the whole maze at once.
The assumption is that the loop must be normalized – written so that the loop index/variable starts at 1 and gets incremented by 1 in every iteration. For example, in the following loop, a=2, b=3, c=2, d=0 and GCD(a,c)=2 and (d-b) is -3. Since 2 does not divide -3, no dependence is possible.
The amount of memory that the algorithm needs is the space for one element and one counter. In the random access model of computing usually used for the analysis of algorithms, each of these values can be stored in a machine word and the total space needed is O(1). If an array index is needed to keep track of the algorithm's position in the ...
Whole program optimization (WPO) is the compiler optimization of a program using information about all the modules in the program. Normally, optimizations are performed on a per module, "compiland", basis; but this approach, while easier to write and test and less demanding of resources during the compilation itself, does not allow certainty about the safety of a number of optimizations such ...