**Algorithmic Analysis**

It is frequently important to know how much of a particular resource (such as time or storage) is theoretically required for a given algorithm. Methods have been developed for the analysis of algorithms to obtain such quantitative answers (estimates); for example, the sorting algorithm above has a time requirement of O(*n*), using the big O notation with *n* as the length of the list. At all times the algorithm only needs to remember two values: the largest number found so far, and its current position in the input list. Therefore it is said to have a space requirement of *O(1)*, if the space required to store the input numbers is not counted, or O(*n*) if it is counted.

Different algorithms may complete the same task with a different set of instructions in less or more time, space, or 'effort' than others. For example, a binary search algorithm will usually outperform a brute force sequential search when used for table lookups on sorted lists.

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### Famous quotes containing the word analysis:

“Cubism had been an *analysis* of the object and an attempt to put it before us in its totality; both as *analysis* and as synthesis, it was a criticism of appearance. Surrealism transmuted the object, and suddenly a canvas became an apparition: a new figuration, a real transfiguration.”

—Octavio Paz (b. 1914)