Open In App

Searching Algorithms

Last Updated : 01 Apr, 2024
Like Article

Searching algorithms are essential tools in computer science used to locate specific items within a collection of data. These algorithms are designed to efficiently navigate through data structures to find the desired information, making them fundamental in various applications such as databases, web search engines, and more.

Searching Algorithm

What is Searching?

Searching is the fundamental process of locating a specific element or item within a collection of data. This collection of data can take various forms, such as arrays, lists, trees, or other structured representations. The primary objective of searching is to determine whether the desired element exists within the data, and if so, to identify its precise location or retrieve it. It plays an important role in various computational tasks and real-world applications, including information retrieval, data analysis, decision-making processes, and more.

Searching terminologies:

Target Element:

In searching, there is always a specific target element or item that you want to find within the data collection. This target could be a value, a record, a key, or any other data entity of interest.

Search Space:

The search space refers to the entire collection of data within which you are looking for the target element. Depending on the data structure used, the search space may vary in size and organization.


Searching can have different levels of complexity depending on the data structure and the algorithm used. The complexity is often measured in terms of time and space requirements.

Deterministic vs. Non-deterministic:

Some searching algorithms, like binary search, are deterministic, meaning they follow a clear, systematic approach. Others, such as linear search, are non-deterministic, as they may need to examine the entire search space in the worst case.

Importance of Searching in DSA:

  • Efficiency: Efficient searching algorithms improve program performance.
  • Data Retrieval: Quickly find and retrieve specific data from large datasets.
  • Database Systems: Enables fast querying of databases.
  • Problem Solving: Used in a wide range of problem-solving tasks.

Applications of Searching:

Searching algorithms have numerous applications across various fields. Here are some common applications:

  • Information Retrieval: Search engines like Google, Bing, and Yahoo use sophisticated searching algorithms to retrieve relevant information from vast amounts of data on the web.
  • Database Systems: Searching is fundamental in database systems for retrieving specific data records based on user queries, improving efficiency in data retrieval.
  • E-commerce: Searching is crucial in e-commerce platforms for users to find products quickly based on their preferences, specifications, or keywords.
  • Networking: In networking, searching algorithms are used for routing packets efficiently through networks, finding optimal paths, and managing network resources.
  • Artificial Intelligence: Searching algorithms play a vital role in AI applications, such as problem-solving, game playing (e.g., chess), and decision-making processes
  • Pattern Recognition: Searching algorithms are used in pattern matching tasks, such as image recognition, speech recognition, and handwriting recognition.

Basics of Searching Algorithms:

Searching Algorithms:

Comparisons Between Different Searching Algorithms:

Library Implementations of Searching Algorithms:

Easy Problems on Searching:

Medium Problems on Searching:

Hard Problems on Searching:

Quick Links:


Similar Reads

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
5 min read
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
Searching Algorithms for 2D Arrays (Matrix)
Linear Search in 2D Array: Linear search is a simple and sequential searching algorithm. It is used to find whether a particular element is present in the array or not by traversing every element in the array. While searching in the 2D array is exactly the same but here all the cells need to be traversed In this way, any element is searched in a 2D
13 min read
Searching Algorithms in Python
Searching algorithms are fundamental techniques used to find an element or a value within a collection of data. In this tutorial, we'll explore some of the most commonly used searching algorithms in Python. These algorithms include Linear Search, Binary Search, Interpolation Search, and Jump Search. 1. Linear SearchLinear search is the simplest sea
6 min read
Iterative searching in Binary Search Tree
Given a binary search tree and a key. Check the given key exists in BST or not without recursion. Please refer binary search tree insertion for recursive search. C/C++ Code // C++ program to demonstrate searching operation // in binary search tree without recursion #include <bits/stdc++.h> using namespace std; struct Node { int data; struct N
7 min read
Pattern Searching using C++ library
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
3 min read
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
15+ min read
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
7 min read
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
7 min read
Real time optimized KMP Algorithm for Pattern Searching
In the article, we have already discussed the KMP algorithm for pattern searching. In this article, a real-time optimized KMP algorithm is discussed. From the previous article, it is known that KMP(a.k.a. Knuth-Morris-Pratt) algorithm preprocesses the pattern P and constructs a failure function F(also called as lps[]) to store the length of the lon
7 min read
Article Tags :
Practice Tags :