Boyer–Moore string search algorithm

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The document describes the Boyer-Moore string search algorithm, which improves on the naive string matching algorithm. It uses two rules - the bad character rule and good suffix rule - to skip unnecessary character comparisons, making string searches more efficient. The bad character rule uses a table to determine how far to shift the pattern when a mismatch occurs, while the good suffix rule allows reusing matches when they are found. Together these rules allow Boyer-Moore to significantly outperform the naive algorithm.

BOYER–MOORE STRING
SEARCH ALGORITHM
SeyedHamid Shekarforoush
Bowling Green State University

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BOYER–MOORE STRING SEARCH ALGORITHM
 developed by Robert S. Boyer and J Strother
Moore in 1977
 Smart naïve method
 tries to match the pattern with target text
 Use two rules to skip unnecessary matches
 Match from the end of pattern

FIRST RULE: THE BAD CHARACTER RULE (BCR)
 Text : bowling green state university computer science department
 Pattern : science
Letter s c i e n *
BCR 6 1 4 1 2 7

FIRST RULE: THE BAD CHARACTER RULE (BCR)
B OW L I NG G R E E N S T A T E U N I V E R S I T Y C OMP U T E R S C I E N C E
Letter s c i e n *
BCR 6 1 4 1 2 7
S C I E N C E

FIRST RULE: THE BAD CHARACTER RULE (BCR)
B OW L I NG G R E E N S T A T E U N I V E R S I T Y C OMP U T E R S C I E N C E
Letter s c i e n *
BCR 6 1 4 1 2 7
S C I E N C E 7 shifts

FIRST RULE: THE BAD CHARACTER RULE (BCR)
B OW L I NG G R E E N S T A T E U N I V E R S I T Y C OMP U T E R S C I E N C E
Letter s c i e n *
BCR 6 1 4 1 2 7
S C I E N C E 4 shifts

FIRST RULE: THE BAD CHARACTER RULE (BCR)
B OW L I NG G R E E N S T A T E U N I V E R S I T Y C OMP U T E R S C I E N C E
Letter s c i e n *
BCR 6 1 4 1 2 7
S C I E N C E1 shifts

BUILDING BCR TABLE
• Length – index – 1
• The BCR value can’t be less than 1
• If we have repeated letters we count the minimum BCR value, because it
should be the rightmost occurrence of the letter
• We use symbol “*” for any other letter that is not in the pattern and the BC
value is the length of the pattern, because we can skip the whole pattern
knowing that character “*” is not in the pattern.

BUILDING BCR TABLE • Length – index – 1
• Length = 7
index 0 1 2 3 4 5 6 7
pattern s c i e n c e *
BCR 6 5 4 3 2 1 0>>>1 7
•Length – index – 1
•7-0-1 =6
•The BCR value can’t be less than 1
•Why?

BUILDING BCR TABLE • Length – index – 1
• Length = 7
index 0 1 2 3 4 5 6 7
pattern s c i e n c e *
BCR 6 5 4 3 2 1 0>>>1 7
•Minimum BCR for repeated letters
Letter s c i e n *
BCR 6 1 4 1 2 7

SECOND RULE: GOOD SUFFIX RULE (GSR)
 It used when we have some
successful matches
 Reusing the already matched
string

SECOND RULE: GOOD SUFFIX RULE (GSR)
6 shifts

BOTH RULES TOGETHER
 At each step when we get a mismatch and we want to shift, the algorithm
use both rules and use the bigger shift

BOTH RULES TOGETHER
Letter T C G *
BCR 2 3 1 10
 BCR = 2 shifts  GSR = 6 shifts

PERFORMANCE
 The Boyer–Moore is work faster
and better with longer pattern
with less repeated characters
 Most of the time the BCR win
over the GSR
 many implementation don’t use
the GSR at all
Algorithm Preprocessing time Matching time
Naïve 0 (no preprocessing) Θ((n−m)m)
Rabin–Karp Θ(m) average Θ(n + m),
worst
Θ((n−m)m)
Finite-state Θ(mk) Θ(n)
Knuth–Morris–Pratt Θ(m) Θ(n)
Boyer–Moore Θ(m + k) best Ω(n/m), worst O(n)
Bitap Θ(m + k) O(mn)

REFRENCES
 [1] Robert S. Boyer and J. Strother Moore. 1977. A fast string searching
algorithm. Commun. ACM 20, 10 (October 1977), 762-772.
DOI=http://dx.doi.org/10.1145/359842.359859
 [2] Wikipedia contributors, "Boyer–Moore string search algorithm," Wikipedia,
The Free Encyclopedia,
https://en.wikipedia.org/w/index.php?title=Boyer%E2%80%93Moore_string_sear
ch_algorithm&oldid=688111014 (accessed November 20, 2015).

1. The Boyer-Moore algorithm improves upon naive exact string matching by using knowledge gained from character comparisons to skip future alignments that cannot possibly match. 2. It uses two rules - the bad character rule, which skips alignments based on the mismatching character, and the good suffix rule, which skips based on matching suffixes. Precomputed tables are used to determine the number of skips. 3. By skipping alignments in this way, Boyer-Moore is able to examine fewer total characters than naive matching and runs in linear worst-case time, compared to quadratic time for naive matching.

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Migrating from Lotus Notes to Outlook can be a complex and time-consuming task, especially when dealing with large volumes of NSF emails. This presentation provides a complete guide on how to batch export Lotus Notes NSF emails to Outlook PST format quickly and securely. It highlights the challenges of manual methods, the benefits of using an automated tool, and introduces eSoftTools NSF to PST Converter Software — a reliable solution designed to handle bulk email migrations efficiently. Learn about the software’s key features, step-by-step export process, system requirements, and how it ensures 100% data accuracy and folder structure preservation during migration. Make your email transition smoother, safer, and faster with the right approach. Read More:- https://www.esofttools.com/nsf-to-pst-converter.html

Not So Common Memory Leaks in Java WebinarTier1 app

This SlideShare presentation is from our May webinar, “Not So Common Memory Leaks & How to Fix Them?”, where we explored lesser-known memory leak patterns in Java applications. Unlike typical leaks, subtle issues such as thread local misuse, inner class references, uncached collections, and misbehaving frameworks often go undetected and gradually degrade performance. This deck provides in-depth insights into identifying these hidden leaks using advanced heap analysis and profiling techniques, along with real-world case studies and practical solutions. Ideal for developers and performance engineers aiming to deepen their understanding of Java memory management and improve application stability.

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How to Optimize Your AWS Environment for Improved Cloud PerformanceThousandEyes