BRUTE FORCE ALGORITHM

MADE BY:Rakshita tuli 1469it

Salika Chaudhary 1477it

INDEX Brute Force Brute Force String Matching Algorithm Example Efficiency of Brute force algorithm Strength of Brute force algorithm Weaknesses of Brute force

algorithm

Exact Pattern Matching String matching algorithms or pattern matching

algorithms try to find a place where one or several strings (also called patterns) are found within a larger string or text.

Various pattern matching algorithms are :• Brute force algorithm• Boyer Moore Algorithm• Aho - Corasik Algorithm etc.

Brute Force

A straightforward approach, usually based directly on the problem’s statement and definitions of the concepts involved

Examples:1. String and pattern matching

2. Computing n!

3. Multiplying two matrices

4. Searching for a key of a given value in a list

Brute-Force String Matching pattern: a string of m characters to search for text: a (longer) string of n characters to search in problem: find a substring in the text that matches the

pattern

Brute-force algorithmStep 1 Align pattern at beginning of textStep 2 Moving from left to right, compare each character of

pattern to the corresponding character in text until all characters are found to match (successful search); or a mismatch is detected

Step 3 While pattern is not found and the text is not yet exhausted, realign pattern one position to the right and repeat Step 2

Algorithm

Examples of Brute-Force String Matching

Efficiency The expected number of comparisons when

searching an input text string of n characters for a pattern of m characters is:

Where NC is expected number of comparisons and c is the size of alphabet of the text.

Efficiency Brute-force pattern matching runs in time O(nm).

Challenges

Brute force strengths Strengths:

It is wide applicable.

It is not complex in nature unlike other algorithms.

It yields reasonable algorithms for some important problems

searching; string matching; matrix multiplication

It yields standard algorithms for simple computational tasks

sum/product of n numbers; finding max/min in a list

Brute force weaknesses Weaknesses:

It rarely yields efficient algorithms

Some brute force algorithms are unacceptably slow

e.g., the recursive algorithm for computing Fibonacci numbers

It is not as constructive/creative as some other design techniques

Applications parsers.

spam filters.

digital libraries.

screen scrapers.

word processors.

web search engines.

natural language processing.

computational molecular biology.

feature detection in digitized images. . . .