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This repository has been archived by the owner on Jul 10, 2024. It is now read-only.
Like Binary Search, Jump Search is a searching algorithm for sorted arrays. The basic idea is to check fewer elements (than linear search) by jumping ahead by fixed steps or skipping some elements in place of searching all elements.
For example, suppose we have an array arr[] of size n and block (to be jumped) size m. Then we search at the indexes arr[0], arr[m], arr[2m]…..arr[km] and so on. Once we find the interval (arr[km] < x < arr[(k+1)m]), we perform a linear search operation from the index km to find the element x.
Pseudocode
procedure jump_search
A ← sorted array
n ← size of array
x ← value to be searched
Set block size = √n
while A[min(block size, n)-1] < x do
prev = block size
block size = block size + √n
if prev >= n
return not found
end while
while A[prev] < x do
prev = prev + 1
if prev == min(block size, n)
return not found
end while
if A[prev] == x
return prev
return not found
end procedure
Example
list = [1,2,3,4,5]
value = 4
Output : 3
How to contribute
Comment !assign to assign this issue to yourself
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Save the solution in program/program/implement-jump-search/ImplementJumpSearch.rb
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The text was updated successfully, but these errors were encountered:
Description
Write a Ruby program to implement jump search
Like Binary Search, Jump Search is a searching algorithm for sorted arrays. The basic idea is to check fewer elements (than linear search) by jumping ahead by fixed steps or skipping some elements in place of searching all elements.
For example, suppose we have an array arr[] of size n and block (to be jumped) size m. Then we search at the indexes arr[0], arr[m], arr[2m]…..arr[km] and so on. Once we find the interval (arr[km] < x < arr[(k+1)m]), we perform a linear search operation from the index km to find the element x.
Pseudocode
Example
How to contribute
!assign
to assign this issue to yourselfprogram/program/implement-jump-search/ImplementJumpSearch.rb
The text was updated successfully, but these errors were encountered: