Brute Force Algorithms Explained (2024)

/ #algorithms
Brute Force Algorithms Explained (1)

Brute Force Algorithms are exactly what they sound like – straightforward methods of solving a problem that rely on sheer computing power and trying every possibility rather than advanced techniques to improve efficiency.

For example, imagine you have a small padlock with 4 digits, each from 0-9. You forgot your combination, but you don't want to buy another padlock. Since you can't remember any of the digits, you have to use a brute force method to open the lock.

So you set all the numbers back to 0 and try them one by one: 0001, 0002, 0003, and so on until it opens. In the worst case scenario, it would take 104, or 10,000 tries to find your combination.

A classic example in computer science is the traveling salesman problem (TSP). Suppose a salesman needs to visit 10 cities across the country. How does one determine the order in which those cities should be visited such that the total distance traveled is minimized?

The brute force solution is simply to calculate the total distance for every possible route and then select the shortest one. This is not particularly efficient because it is possible to eliminate many possible routes through clever algorithms.

The time complexity of brute force is O(mn), which is sometimes written as O(n*m) . So, if we were to search for a string of "n" characters in a string of "m" characters using brute force, it would take us n * m tries.

More information about algorithms

In computer science, an algorithm is simply a set of step by step procedure to solve a given problem. Algorithms can be designed to perform calculations, process data, or perform automated reasoning tasks.

Here's how the dictionary defines algorithms in simple terms:

a step-by-step procedure for solving a problem or accomplishing some end.

There are certain requirements that an algorithm must abide by:

  1. Definiteness: Each step in the process is precisely stated.
  2. Effective Computability: Each step in the process can be carried out by a computer.
  3. Finiteness: The program will eventually successfully terminate.

Some common types of algorithms include:

  • sorting algorithms
  • search algorithms
  • compression algorithms.

Classes of algorithms include

  • Graph
  • Dynamic Programming
  • Sorting
  • Searching
  • Strings
  • Math
  • Computational Geometry
  • Optimization
  • Miscellaneous.

Although technically not a class of algorithms, Data Structures are often grouped with them.

Efficiency

Algorithms are most commonly judged by their efficiency and the amount of computing resources they require to complete their task.

A common way to evaluate an algorithm is to look at its time complexity. This shows how the running time of the algorithm grows as the input size grows. Since the algorithms today have to operate on large data inputs, it is essential for our algorithms to have a reasonably fast running time.

Sorting Algorithms

Sorting algorithms come in various flavors depending on your necessity. Some, very common and widely used are:

Quicksort

There is no sorting discussion which can finish without quick sort. Here is the basic concept: Quick Sort

Mergesort

A sorting algorithm which relies on the concept how to sorted arrays are merged to give one sorted arrays. Read more about it here: Mergesort

freeCodeCamp’s curriculum heavily emphasizes creating algorithms. This is because learning algorithms is a good way to practice programming skills. Interviewers most commonly test candidates on algorithms during developer job interviews.

Books about algorithms in JavaScript:

Data Structures in JavaScript

  • Free book which covers Data Structures in JavaScript
  • GitBook

Learning JavaScript Data Structures and Algorithms - Second Edition

  • Covers object oriented programming, prototypal inheritance, sorting & searching algorithms, quicksort, mergesort, binary search trees and advanced algorithm concepts
  • Amazon
  • ISBN-13: 978-1785285493

Data Structures and Algorithms with JavaScript: Bringing classic computing approaches to the Web

  • Covers recursion, sorting and searching algorithms, linked lists and binary search trees.
  • Amazon
  • ISBN-13: 978-1449364939

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Brute Force Algorithms Explained (2024)

FAQs

Brute Force Algorithms Explained? ›

Brute Force is a straightforward method used in algorithmic problem-solving that checks every possible solution until the correct one is found. Brute Force Algorithms function by searching each element sequentially until the desired result is found or all options are exhausted.

How does a brute force algorithm work? ›

In programming, a Brute Force algorithm solves a problem by generating all possible solutions and testing each one until it finds an answer that works. It's not sophisticated or efficient, but it's guaranteed to deliver an answer if one exists.

What is an example of a brute force algorithm in real life? ›

Brute Force Algorithms:

For example, imagine you have a small padlock with 4 digits ranging from 0–9. Unfortunately, you forgot your password and can not afford a new one so you apply brute force algorithm by setting all numbers from 0000 to 9999 which gives us a possibility of 10⁴ combinations.

What is brute force with an example? ›

A brute force attack is uses a trial-and-error approach to systematically guess login info, credentials, and encryption keys. The attacker submits combinations of usernames and passwords until they finally guess correctly.

Which sorting algorithms are brute force? ›

Brute Force Sorting
  • Algorithm SelectionSort(A[0...n-1])
  • Algorithm BubbleSort(A[0...n-1])
  • Algorithm BruteForceStringMatch(T[0...n-1], P[0...m-1])

What is the weakness of brute force algorithm? ›

Lack of Scalability: Brute-force algorithms are generally not scalable, meaning that they struggle to handle larger problem instances. As the input size grows, the exponential growth in computation time makes brute-force approaches impractical or impossible to apply.

What is better than brute force algorithm? ›

In many cases, the greedy method is faster than brute force because it does not explore all possible solutions. It can be effective in situations where the optimal solution can be obtained by making locally optimal choices.

Why is the brute force algorithm not efficient? ›

2 Disadvantages of brute force algorithms

They can consume a lot of computational resources, such as memory, CPU, or network bandwidth, depending on the size and complexity of the problem. For some problems, the number of possible solutions can be so large that it would take years or even centuries to try them all.

Are brute force attacks still used? ›

Despite being an old cyberattack method, brute force attacks are tried and tested and remain a popular tactic with hackers.

Is brute force a greedy algorithm? ›

By definition a greedy algorithm makes decisions at each step by choosing the locally optimal choice, with the hope of finding a global optimum, and a brute force algorithm tries every possible solution to a problem, in order to find the correct solution.

Is brute force illegal? ›

Is a brute force attack illegal? The legality of a brute force attack is dictated by intent. In other words, if you're attempting to maliciously access a user account or organization's network to cause harm through financial or other motivations, then it is illegal.

What is the formula for brute force? ›

The time complexity of brute force is O(mn), which is sometimes written as O(n*m) . So, if we were to search for a string of "n" characters in a string of "m" characters using brute force, it would take us n * m tries.

What is the difference between DDoS and brute force? ›

It should be noted that white DoS and DDoS attacks also use a lot of requests, they differ in overall goals when compared to a brute force attack. In the case of DoS and DDoS, the goal is to make the server inaccessible, whereas with a brute force attack the goal is to gain access to the server.

What is another name for brute force algorithm? ›

In computer science, brute-force search or exhaustive search, also known as generate and test, is a very general problem-solving technique and algorithmic paradigm that consists of systematically checking all possible candidates for whether or not each candidate satisfies the problem's statement.

How does the brute force algorithm work? ›

A brute force algorithm solves a problem through exhaustion: it goes through all possible choices until a solution is found. The time complexity of a brute force algorithm is often proportional to the input size. Brute force algorithms are simple and consistent, but very slow.

What is the most powerful sorting algorithm? ›

Quicksort is the fastest known comparison-based sorting algorithm when applied to large, unordered, sequences. It also has the advantage of being an in-place (or nearly in-place) sort.

How does a brute force matcher work? ›

Brute-Force matcher is simple. It takes the descriptor of one feature in first set and is matched with all other features in second set using some distance calculation. And the closest one is returned. For BF matcher, first we have to create the BFMatcher object using cv.

How does brute force string matching algorithm work? ›

The Brute Force algorithm compares the pattern to the text, one character at a time, until unmatching characters are found: - Compared characters are italicized. - Correct matches are in boldface type.

Is the brute force algorithm efficient? ›

While this approach can be straightforward to implement, it can also be prolonged and inefficient, particularly for large input sizes. The time complexity of a brute force algorithm is often proportional to the input size, which means that as the size of the input increases, the algorithm's running time also increases.

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