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Boyer Moore Algorithm for Pattern Searching

Last Updated : 11 Mar, 2024
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Pattern searching is an important problem in computer science. When we do search for a string in a notepad/word file, browser, or database, pattern searching algorithms are used to show the search results.

A typical problem statement would be- 

” Given a text txt[0..n-1] and a pattern pat[0..m-1] where n is the length of the text and m is the length of the pattern, write a function search(char pat[], char txt[]) that prints all occurrences of pat[] in txt[]. You may assume that n > m. “
Examples: 

Input: txt[] = “THIS IS A TEST TEXT”

pat[] = “TEST”

Output: Pattern found at index 10

Input: txt[] = “AABAACAADAABAABA”

pat[] = “AABA”

Output: Pattern found at index 0

Pattern found at index 9

Pattern found at index 12

first

In this post, we will discuss the Boyer Moore pattern searching algorithm. Like KMP and Finite Automata algorithms, Boyer Moore algorithm also preprocesses the pattern. 
Boyer Moore is a combination of the following two approaches. 

  1. Bad Character Heuristic 
  2. Good Suffix Heuristic 

Both of the above heuristics can also be used independently to search a pattern in a text. Let us first understand how two independent approaches work together in the Boyer Moore algorithm.

If we take a look at the Naive algorithm, it slides the pattern over the text one by one. KMP algorithm does preprocessing over the pattern so that the pattern can be shifted by more than one. The Boyer Moore algorithm does preprocessing for the same reason. It processes the pattern and creates different arrays for each of the two heuristics. At every step, it slides the pattern by the max of the slides suggested by each of the two heuristics. So, it uses greatest offset suggested by the two heuristics at every step

Unlike the previous pattern searching algorithms, the Boyer Moore algorithm starts matching from the last character of the pattern.
In this post, we will discuss the bad character heuristic and the Good Suffix heuristic in the next post. 

Bad Character Heuristic

The idea of bad character heuristic is simple. The character of the text which doesn’t match with the current character of the pattern is called the Bad Character. Upon mismatch, we shift the pattern until – 

  1. The mismatch becomes a match.
  2. Pattern P moves past the mismatched character.

Case 1 – Mismatch become match 

We will lookup the position of the last occurrence of the mismatched character in the pattern, and if the mismatched character exists in the pattern, then we’ll shift the pattern such that it becomes aligned to the mismatched character in the text T. 
 

case-1

Explanation:

In the above example, we got a mismatch at position 3.

Here our mismatching character is “A”. Now we will search for last occurrence of “A” in pattern. We got “A” at position 1 in pattern (displayed in Blue) and this is the last occurrence of it. Now we will shift pattern 2 times so that “A” in pattern get aligned with “A” in text.

Case 2 – Pattern move past the mismatch character 

We’ll lookup the position of last occurrence of mismatching character in pattern and if character does not exist we will shift pattern past the mismatching character. 
 

case-2

Explanation: 

Here we have a mismatch at position 7.

The mismatching character “C” does not exist in pattern before position 7 so we’ll shift pattern past to the position 7 and eventually in above example we have got a perfect match of pattern (displayed in Green). We are doing this because “C” does not exist in the pattern so at every shift before position 7 we will get mismatch and our search will be fruitless.

Implementation:

In the following implementation, we pre-process the pattern and store the last occurrence of every possible character in an array of size equal to alphabet size. If the character is not present at all, then it may result in a shift by m (length of pattern). Therefore, the bad character heuristic takes O(n/m) time in the best case. 

Below is the implementation of the above idea:

C++




/* C++ Program for Bad Character Heuristic of Boyer
Moore String Matching Algorithm */
#include <bits/stdc++.h>
using namespace std;
#define NO_OF_CHARS 256
 
// The preprocessing function for Boyer Moore's
// bad character heuristic
void badCharHeuristic(string str, int size,
                      int badchar[NO_OF_CHARS])
{
    int i;
 
    // Initialize all occurrences as -1
    for (i = 0; i < NO_OF_CHARS; i++)
        badchar[i] = -1;
 
    // Fill the actual value of last occurrence
    // of a character
    for (i = 0; i < size; i++)
        badchar[(int)str[i]] = i;
}
 
/* A pattern searching function that uses Bad
Character Heuristic of Boyer Moore Algorithm */
void search(string txt, string pat)
{
    int m = pat.size();
    int n = txt.size();
 
    int badchar[NO_OF_CHARS];
 
    /* Fill the bad character array by calling
    the preprocessing function badCharHeuristic()
    for given pattern */
    badCharHeuristic(pat, m, badchar);
 
    int s = 0; // s is shift of the pattern with
               // respect to text
    while (s <= (n - m)) {
        int j = m - 1;
 
        /* Keep reducing index j of pattern while
        characters of pattern and text are
        matching at this shift s */
        while (j >= 0 && pat[j] == txt[s + j])
            j--;
 
        /* If the pattern is present at current
        shift, then index j will become -1 after
        the above loop */
        if (j < 0) {
            cout << "pattern occurs at shift = " << s
                 << endl;
 
            /* Shift the pattern so that the next
            character in text aligns with the last
            occurrence of it in pattern.
            The condition s+m < n is necessary for
            the case when pattern occurs at the end
            of text */
            s += (s + m < n) ? m - badchar[txt[s + m]] : 1;
        }
 
        else
            /* Shift the pattern so that the bad character
            in text aligns with the last occurrence of
            it in pattern. The max function is used to
            make sure that we get a positive shift.
            We may get a negative shift if the last
            occurrence of bad character in pattern
            is on the right side of the current
            character. */
            s += max(1, j - badchar[txt[s + j]]);
    }
}
 
/* Driver code */
int main()
{
    string txt = "ABAAABCD";
    string pat = "ABC";
    search(txt, pat);
    return 0;
}
 
// This code is contributed by rathbhupendra


C




/* C Program for Bad Character Heuristic of Boyer
   Moore String Matching Algorithm */
#include <limits.h>
#include <stdio.h>
#include <string.h>
 
#define NO_OF_CHARS 256
 
// A utility function to get maximum of two integers
int max(int a, int b) { return (a > b) ? a : b; }
 
// The preprocessing function for Boyer Moore's
// bad character heuristic
void badCharHeuristic(char* str, int size,
                      int badchar[NO_OF_CHARS])
{
    int i;
 
    // Initialize all occurrences as -1
    for (i = 0; i < NO_OF_CHARS; i++)
        badchar[i] = -1;
 
    // Fill the actual value of last occurrence
    // of a character
    for (i = 0; i < size; i++)
        badchar[(int)str[i]] = i;
}
 
/* A pattern searching function that uses Bad
   Character Heuristic of Boyer Moore Algorithm */
void search(char* txt, char* pat)
{
    int m = strlen(pat);
    int n = strlen(txt);
 
    int badchar[NO_OF_CHARS];
 
    /* Fill the bad character array by calling
       the preprocessing function badCharHeuristic()
       for given pattern */
    badCharHeuristic(pat, m, badchar);
 
    int s = 0; // s is shift of the pattern with
               // respect to text
    while (s <= (n - m)) {
        int j = m - 1;
 
        /* Keep reducing index j of pattern while
           characters of pattern and text are
           matching at this shift s */
        while (j >= 0 && pat[j] == txt[s + j])
            j--;
 
        /* If the pattern is present at current
           shift, then index j will become -1 after
           the above loop */
        if (j < 0) {
            printf("\n pattern occurs at shift = %d", s);
 
            /* Shift the pattern so that the next
               character in text aligns with the last
               occurrence of it in pattern.
               The condition s+m < n is necessary for
               the case when pattern occurs at the end
               of text */
            s += (s + m < n) ? m - badchar[txt[s + m]] : 1;
        }
 
        else
            /* Shift the pattern so that the bad character
               in text aligns with the last occurrence of
               it in pattern. The max function is used to
               make sure that we get a positive shift.
               We may get a negative shift if the last
               occurrence  of bad character in pattern
               is on the right side of the current
               character. */
            s += max(1, j - badchar[txt[s + j]]);
    }
}
 
/* Driver program to test above function */
int main()
{
    char txt[] = "ABAAABCD";
    char pat[] = "ABC";
    search(txt, pat);
    return 0;
}


Java




/* Java Program for Bad Character Heuristic of Boyer
Moore String Matching Algorithm */
 
class AWQ {
 
    static int NO_OF_CHARS = 256;
 
    // A utility function to get maximum of two integers
    static int max(int a, int b) { return (a > b) ? a : b; }
 
    // The preprocessing function for Boyer Moore's
    // bad character heuristic
    static void badCharHeuristic(char[] str, int size,
                                 int badchar[])
    {
 
        // Initialize all occurrences as -1
        for (int i = 0; i < NO_OF_CHARS; i++)
            badchar[i] = -1;
 
        // Fill the actual value of last occurrence
        // of a character (indices of table are ascii and
        // values are index of occurrence)
        for (int i = 0; i < size; i++)
            badchar[(int)str[i]] = i;
    }
 
    /* A pattern searching function that uses Bad
    Character Heuristic of Boyer Moore Algorithm */
    static void search(char txt[], char pat[])
    {
        int m = pat.length;
        int n = txt.length;
 
        int badchar[] = new int[NO_OF_CHARS];
 
        /* Fill the bad character array by calling
           the preprocessing function badCharHeuristic()
           for given pattern */
        badCharHeuristic(pat, m, badchar);
 
        int s = 0; // s is shift of the pattern with
                   // respect to text
        // there are n-m+1 potential alignments
        while (s <= (n - m)) {
            int j = m - 1;
 
            /* Keep reducing index j of pattern while
               characters of pattern and text are
               matching at this shift s */
            while (j >= 0 && pat[j] == txt[s + j])
                j--;
 
            /* If the pattern is present at current
               shift, then index j will become -1 after
               the above loop */
            if (j < 0) {
                System.out.println(
                    "Patterns occur at shift = " + s);
 
                /* Shift the pattern so that the next
                   character in text aligns with the last
                   occurrence of it in pattern.
                   The condition s+m < n is necessary for
                   the case when pattern occurs at the end
                   of text */
                // txt[s+m] is character after the pattern
                // in text
                s += (s + m < n) ? m - badchar[txt[s + m]]
                                 : 1;
            }
 
            else
                /* Shift the pattern so that the bad
                   character in text aligns with the last
                   occurrence of it in pattern. The max
                   function is used to make sure that we get
                   a positive shift. We may get a negative
                   shift if the last occurrence  of bad
                   character in pattern is on the right side
                   of the current character. */
                s += max(1, j - badchar[txt[s + j]]);
        }
    }
 
    /* Driver program to test above function */
    public static void main(String[] args)
    {
 
        char txt[] = "ABAAABCD".toCharArray();
        char pat[] = "ABC".toCharArray();
        search(txt, pat);
    }
}


C#




/* C# Program for Bad Character Heuristic of Boyer
Moore String Matching Algorithm */
 
using System;
public class AWQ {
 
    static int NO_OF_CHARS = 256;
 
    // A utility function to get maximum of two integers
    static int max(int a, int b) { return (a > b) ? a : b; }
 
    // The preprocessing function for Boyer Moore's
    // bad character heuristic
    static void badCharHeuristic(char[] str, int size,
                                 int[] badchar)
    {
        int i;
 
        // Initialize all occurrences as -1
        for (i = 0; i < NO_OF_CHARS; i++)
            badchar[i] = -1;
 
        // Fill the actual value of last occurrence
        // of a character
        for (i = 0; i < size; i++)
            badchar[(int)str[i]] = i;
    }
 
    /* A pattern searching function that uses Bad
    Character Heuristic of Boyer Moore Algorithm */
    static void search(char[] txt, char[] pat)
    {
        int m = pat.Length;
        int n = txt.Length;
 
        int[] badchar = new int[NO_OF_CHARS];
 
        /* Fill the bad character array by calling
            the preprocessing function badCharHeuristic()
            for given pattern */
        badCharHeuristic(pat, m, badchar);
 
        int s = 0; // s is shift of the pattern with
                   // respect to text
        while (s <= (n - m)) {
            int j = m - 1;
 
            /* Keep reducing index j of pattern while
                characters of pattern and text are
                matching at this shift s */
            while (j >= 0 && pat[j] == txt[s + j])
                j--;
 
            /* If the pattern is present at current
                shift, then index j will become -1 after
                the above loop */
            if (j < 0) {
                Console.WriteLine(
                    "Patterns occur at shift = " + s);
 
                /* Shift the pattern so that the next
                    character in text aligns with the last
                    occurrence of it in pattern.
                    The condition s+m < n is necessary for
                    the case when pattern occurs at the end
                    of text */
                s += (s + m < n) ? m - badchar[txt[s + m]]
                                 : 1;
            }
 
            else
                /* Shift the pattern so that the bad
                   character in text aligns with the last
                   occurrence of it in pattern. The max
                   function is used to make sure that we get
                   a positive shift. We may get a negative
                   shift if the last occurrence of bad
                   character in pattern is on the right side
                   of the current character. */
                s += max(1, j - badchar[txt[s + j]]);
        }
    }
 
    /* Driver program to test above function */
    public static void Main()
    {
 
        char[] txt = "ABAAABCD".ToCharArray();
        char[] pat = "ABC".ToCharArray();
        search(txt, pat);
    }
}
 
// This code is contributed by PrinciRaj19992


Javascript




<script>
/* Javascript Program for Bad Character Heuristic of Boyer
Moore String Matching Algorithm */
let NO_OF_CHARS = 256;
 
// A utility function to get maximum of two integers
function max (a,b)
{
    return (a > b)? a: b;
}
 
// The preprocessing function for Boyer Moore's
// bad character heuristic
function badCharHeuristic(str,size,badchar)
{
    // Initialize all occurrences as -1
      for (let i = 0; i < NO_OF_CHARS; i++)
           badchar[i] = -1;
  
      // Fill the actual value of last occurrence
      // of a character (indices of table are ascii and values are index of occurrence)
      for (i = 0; i < size; i++)
           badchar[ str[i].charCodeAt(0)] = i;
}
 
/* A pattern searching function that uses Bad
     Character Heuristic of Boyer Moore Algorithm */
function search(txt,pat)
{
    let m = pat.length;
      let n = txt.length;
  
      let badchar = new Array(NO_OF_CHARS);
  
      /* Fill the bad character array by calling
         the preprocessing function badCharHeuristic()
         for given pattern */
      badCharHeuristic(pat, m, badchar);
  
      let s = 0;  // s is shift of the pattern with
                  // respect to text
       // there are n-m+1 potential alignments
      while(s <= (n - m))
      {
          let j = m-1;
  
          /* Keep reducing index j of pattern while
             characters of pattern and text are
             matching at this shift s */
          while(j >= 0 && pat[j] == txt[s+j])
              j--;
  
          /* If the pattern is present at current
             shift, then index j will become -1 after
             the above loop */
          if (j < 0)
          {
              document.write("Patterns occur at shift = " + s);
  
              /* Shift the pattern so that the next
                 character in text aligns with the last
                 occurrence of it in pattern.
                 The condition s+m < n is necessary for
                 the case when pattern occurs at the end
                 of text */
              //txt[s+m] is character after the pattern in text
              s += (s+m < n)? m-badchar[txt[s+m].charCodeAt(0)] : 1;
  
          }
  
          else
              /* Shift the pattern so that the bad character
                 in text aligns with the last occurrence of
                 it in pattern. The max function is used to
                 make sure that we get a positive shift.
                 We may get a negative shift if the last
                 occurrence  of bad character in pattern
                 is on the right side of the current
                 character. */
              s += max(1, j - badchar[txt[s+j].charCodeAt(0)]);
      }
}
 
/* Driver program to test above function */
let txt="ABAAABCD".split("");
let pat = "ABC".split("");
search(txt, pat);
 
// This code is contributed by unknown2108
</script>


Python3




# Python3 Program for Bad Character Heuristic
# of Boyer Moore String Matching Algorithm
 
NO_OF_CHARS = 256
 
 
def badCharHeuristic(string, size):
    '''
    The preprocessing function for
    Boyer Moore's bad character heuristic
    '''
 
    # Initialize all occurrence as -1
    badChar = [-1]*NO_OF_CHARS
 
    # Fill the actual value of last occurrence
    for i in range(size):
        badChar[ord(string[i])] = i
 
    # return initialized list
    return badChar
 
 
def search(txt, pat):
    '''
    A pattern searching function that uses Bad Character
    Heuristic of Boyer Moore Algorithm
    '''
    m = len(pat)
    n = len(txt)
 
    # create the bad character list by calling
    # the preprocessing function badCharHeuristic()
    # for given pattern
    badChar = badCharHeuristic(pat, m)
 
    # s is shift of the pattern with respect to text
    s = 0
    while(s <= n-m):
        j = m-1
 
        # Keep reducing index j of pattern while
        # characters of pattern and text are matching
        # at this shift s
        while j >= 0 and pat[j] == txt[s+j]:
            j -= 1
 
        # If the pattern is present at current shift,
        # then index j will become -1 after the above loop
        if j < 0:
            print("Pattern occur at shift = {}".format(s))
 
            '''   
                Shift the pattern so that the next character in text
                      aligns with the last occurrence of it in pattern.
                The condition s+m < n is necessary for the case when
                   pattern occurs at the end of text
               '''
            s += (m-badChar[ord(txt[s+m])] if s+m < n else 1)
        else:
            '''
               Shift the pattern so that the bad character in text
               aligns with the last occurrence of it in pattern. The
               max function is used to make sure that we get a positive
               shift. We may get a negative shift if the last occurrence
               of bad character in pattern is on the right side of the
               current character.
            '''
            s += max(1, j-badChar[ord(txt[s+j])])
 
 
# Driver program to test above function
def main():
    txt = "ABAAABCD"
    pat = "ABC"
    search(txt, pat)
 
 
if __name__ == '__main__':
    main()
 
# This code is contributed by Atul Kumar
# (www.facebook.com/atul.kr.007)


Output

pattern occurs at shift = 4

Time Complexity : O(m*n)

Auxiliary Space: O(1)

The Bad Character Heuristic may take O(m*n) time in worst case. The worst case occurs when all characters of the text and pattern are same. For example, txt[] = “AAAAAAAAAAAAAAAAAA” and pat[] = “AAAAA”. The Bad Character Heuristic may take O(n/m) in the best case. The best case occurs when all the characters of the text and pattern are different. 

Boyer Moore Algorithm | Good Suffix heuristic



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Given a text txt[0..n-1] and a pattern pat[0..m-1], write a function that prints all occurrences of pat[] in txt[]. You may assume that n > m.Examples: Input : txt[] = "geeks for geeks" pat[] = "geeks" Output : Pattern found at index 0 Pattern found at index 10 Input : txt[] = "aaaa" pat[] = "aa" Output : Pattern found at index 0 Pattern found a
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Pattern Searching | Set 6 (Efficient Construction of Finite Automata)
In the previous post, we discussed the Finite Automata-based pattern searching algorithm. The FA (Finite Automata) construction method discussed in the previous post takes O((m^3)*NO_OF_CHARS) time. FA can be constructed in O(m*NO_OF_CHARS) time. In this post, we will discuss the O(m*NO_OF_CHARS) algorithm for FA construction. The idea is similar t
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Pattern Searching using a Trie of all Suffixes
Problem Statement: Given a text txt[0..n-1] and a pattern pat[0..m-1], write a function search(char pat[], char txt[]) that prints all occurrences of pat[] in txt[]. You may assume that n > m.As discussed in the previous post, we discussed that there are two ways efficiently solve the above problem.1) Preprocess Pattern: KMP Algorithm, Rabin Kar
13 min read
What is Pattern Searching ?
Pattern searching in Data Structures and Algorithms (DSA) is a fundamental concept that involves searching for a specific pattern or sequence of elements within a given data structure. This technique is commonly used in string matching algorithms to find occurrences of a particular pattern within a text or a larger string. By using various algorith
5 min read
Pattern Searching using Suffix Tree
Given a text txt[0..n-1] and a pattern pat[0..m-1], write a function search(char pat[], char txt[]) that prints all occurrences of pat[] in txt[]. You may assume that n > m. Preprocess Pattern or Preprocess Text? We have discussed the following algorithms in the previous posts: KMP Algorithm Rabin Karp Algorithm Finite Automata based Algorithm B
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Introduction to Pattern Searching
Pattern searching is an algorithm that involves searching for patterns such as strings, words, images, etc. We use certain algorithms to do the search process. The complexity of pattern searching varies from algorithm to algorithm. They are very useful when performing a search in a database. The Pattern Searching algorithm is useful for finding pat
15+ min read
Pattern Searching
Pattern searching algorithms are essential tools in computer science and data processing. These algorithms are designed to efficiently find a particular pattern within a larger set of data. Pattern searching algorithms play important role in tasks such as text processing, data mining, and information retrieval. What is Pattern Searching?Pattern sea
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Fastest Searching Algorithm | GFact
Pattern searching is a critical operation in the field of computer science, Its applications range from text processing and DNA sequencing to image recognition and data mining. As data sizes grow exponentially, the demand for faster pattern-searching algorithms has only grown. Which is the Fastest Searching Algorithm?One of the best algorithms is t
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Array range queries for searching an element
Given an array of N elements and Q queries of the form L R X. For each query, you have to output if the element X exists in the array between the indices L and R(included). Prerequisite : Mo's Algorithms Examples : Input : N = 5 arr = [1, 1, 5, 4, 5] Q = 3 1 3 2 2 5 1 3 5 5 Output : No Yes Yes Explanation : For the first query, 2 does not exist bet
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Octree | Insertion and Searching
Octree is a tree data structure in which each internal node can have at most 8 children. Like Binary tree which divides the space into two segments, Octree divides the space into at most eight-part which is called as octanes. It is used to store the 3-D point which takes a large amount of space. If all the internal node of the Octree contains exact
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m-WAY Search Trees | Set-1 ( Searching )
The m-way search trees are multi-way trees which are generalised versions of binary trees where each node contains multiple elements. In an m-Way tree of order m, each node contains a maximum of m - 1 elements and m children.The goal of m-Way search tree of height h calls for O(h) no. of accesses for an insert/delete/retrieval operation. Hence, it
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Searching Algorithms in Java
Searching Algorithms are designed to check for an element or retrieve an element from any data structure where it is stored. Based on the type of search operation, these algorithms are generally classified into two categories: Sequential Search: In this, the list or array is traversed sequentially and every element is checked. For Example: Linear S
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Difference between Searching and Sorting Algorithms
Prerequisite: Searching and Sorting Algorithms Searching Algorithms are designed to check for an element or retrieve an element from any data structure where it is used. Based on the type of operations these algorithms are generally classified into two categories: Sequential Search: The Sequential Search is the basic and simple Searching Algorithm.
4 min read
Smallest value of X not present in given Vector by searching X*K repeatedly
Given a vector vec, and integers X and K, the task is to keep replacing X with product of X and K, each time X is found in the vector. Return the final product which is not present in the vector. Examples: Input: vec = {1, 2, 6, 10}, X = 2, K = 3Output: 18Explanation: Since the original X is 2 which is present in the vector, multiply it by 3 (2*3=6
7 min read
Searching in Circular Linked list
Given a Circular Linked List CList, and an element K, the task is to check if this element K is present in the Circular Linked list or not. Example: Input: CList = 6->5->4->3->2, K = 3 Output: Found Input: CList = 6->5->4->3->2, K = 1 Output: Not Found Approach: The approach to find an element in Circular Linked List can be
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Searching in Binary Indexed Tree using Binary Lifting in O(LogN)
Binary Indexed Tree (BIT) is a data structure that allows efficient queries of a range of elements in an array and updates on individual elements in O(log n) time complexity, where n is the number of elements in the array. Binary Lifting:One of the efficient techniques used to perform search operations in BIT is called Binary lifting.Binary Lifting
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Searching in Splay Tree
Splay Tree- Splay tree is a binary search tree. In a splay tree, M consecutive operations can be performed in O (M log N) time. A single operation may require O(N) time but average time to perform M operations will need O (M Log N) time. When a node is accessed, it is moved to the top through a set of operations known as splaying. Splaying techniqu
15+ min read
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