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In computer science, brute-force search or exhaustive search, also known as generate and test, is a very general problem-solving technique and algorithmic paradigm that consists of systematically checking all possible candidates for whether or not each candidate satisfies the problem's statement.
There are also search methods designed for quantum computers, like Grover's algorithm, that are theoretically faster than linear or brute-force search even without the help of data structures or heuristics. While the ideas and applications behind quantum computers are still entirely theoretical, studies have been conducted with algorithms like ...
A string-matching algorithm wants to find the starting index m in string S[] that matches the search word W[].. The most straightforward algorithm, known as the "brute-force" or "naive" algorithm, is to look for a word match at each index m, i.e. the position in the string being searched that corresponds to the character S[m].
Instead of a brute-force search of all alignments (of which there are + ), Boyer–Moore uses information gained by preprocessing P to skip as many alignments as possible. Previous to the introduction of this algorithm, the usual way to search within text was to examine each character of the text for the first character of the pattern.
This technique can be used in a way that is much more efficient than the naïve brute-force search algorithm, which considers all 64 8 = 2 48 = 281,474,976,710,656 possible blind placements of eight queens, and then filters these to remove all placements that place two queens either on the same square (leaving only 64!/56! = 178,462,987,637,760 ...
(A brute-force search would require 2 80 operations.) The authors write: "In particular, our analysis is built upon the original differential attack on SHA-0, the near collision attack on SHA-0, the multiblock collision techniques, as well as the message modification techniques used in the collision search attack on MD5.
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To find a maximum clique, one can systematically inspect all subsets, but this sort of brute-force search is too time-consuming to be practical for networks comprising more than a few dozen vertices. Although no polynomial time algorithm is known for this problem, more efficient algorithms than the brute-force search are known.