Binary Search in Data Structure

Level : Advanced
Mentor: Shailendra Chauhan
Duration : 00:02:00

What is Binary Search?

Binary search is an effective approach for retrieving an item from a sorted list of elements. It works by periodically dividing the portion of the list that might hold the item in half until only one location remains.


Binary Search Algorithm

  • Define the search interval as a full array or list.
  • Finding a midway divides the search space in half.
  • Check the center element against the key.
  • If the key matches the middle element, the search is completed; return index.
  • If the key does not match the middle element, select the next search space.
  • If the key is less than the middle element, proceed to the left side of the search.
  • If the key is greater than the middle element, proceed to the right side of the search.
  • Repeat step 2.
  • Continue the process until the key is found or the complete search space has been exhausted.

Conditions for using Binary Search in a Data Structure

To implement the Binary Search algorithm:

  • The data structure should be sorted.
  • Access to any element of the data structure requires constant time.

Implement Binary Search Algorithm in Data Structures

There are two basic techniques to implement the Binary Search Algorithm in Data Structures:

  1. Recursive Binary Search
  2. Iterative Binary Search

Complexity Analysis of Binary Search

Time Complexity

Space Complexity

The space complexity, or O(1), of Binary Search is constant since no appreciable additional memory is used.

Applications of Binary Search

  • Libraries: Used in Java,.NET, and C++ STL libraries.
  • Debugging: Helps in identifying faults during the debugging process.
  • Machine Learning: Provides the foundation for advanced machine learning methods such as neural network training.
  • Computer graphics: A component of texture mapping and ray tracing techniques.
  • Database Searches: Used to search databases.

Advantages of Binary Search

  • Faster than linear search, particularly for big arrays (O(logN)).
  • More efficient than other temporal complexity algorithms such as interpolation or exponential search.
  • Each cycle removes half of the list, considerably reducing the search space.
  • Ideal for searching huge datasets on external memory.
  • Works with rotating arrays.

Disadvantages of Binary Search

  • Requires a sorted array; not applicable to unsorted data.
  • A data structure requires contiguous memory locations.
  • Not suited for dynamically updated arrays; only works with static arrays.
  • Elements must be equivalent to ensure good ordering.
  • The recursive binary search requires stack space.

Applications of Binary Search

  • Machine Learning Applications
  • Computer Graphics Utilization
  • Database Search Implementation
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