Table of Contents
Definition of linear search and brute force search
Is linear search a violent search?
Complexity analysis
Example Analysis
Home Web Front-end JS Tutorial Linear search and violent search: concept analysis and application

Linear search and violent search: concept analysis and application

Aug 15, 2025 pm 12:54 PM

Linear search and violent search: conceptual analysis and application

This article aims to clarify the relationship between linear search and brute-force search algorithms. Although linear search can be considered a form of violent search in some cases, the two are not exactly equivalent. This article will explore their definition, applicable scenarios and differences in complexity, and through example analysis, help readers better understand and distinguish these two algorithms.

Linear Search , also known as sequential search, is a simple search algorithm. It starts with the first element of the dataset, comparing each element to the target value one by one until a match is found or the complete dataset is traversed.

Brute Force , also known as exhaustive search, is a common problem-solving strategy. It tries all possible solutions until it finds a solution that meets the requirements of the problem. Violent search is often applied to problems without obvious optimization methods, or in the case of smaller issues.

Broadly speaking, linear search can be regarded as a special case of violent search. When it is necessary to find a specific element in an unsorted dataset, a linear search will traverse all possible elements until the target element is found. This method of traversing all possibilities is in line with the definition of brute force search.

However, it is important to understand that brute force search is often used to describe those less efficient algorithms. For some problems, more efficient solutions exist, and brute force search simply tries all possibilities without taking advantage of any particular nature of the problem.

Complexity analysis

  • Linear search: In the worst case, linear search requires traversing the entire dataset, so its time complexity is O(n), where n is the size of the dataset.
  • Violent Search: The time complexity of a violent search depends on the nature of the problem and the number of possible solutions. In some cases, the time complexity of brute-force search may be exponential or factorial, which makes it unfeasible when dealing with large-scale problems.

Example Analysis

The following code example shows a JavaScript function that solves the largest subarrays and problems using brute force search:

 const maxSubArray = function(nums) {
 let max = -Infinity; // Initialize to negative infinity, dealing with the case of array of all negative numbers for (let i = 0; i <p> In this example, the algorithm tries all possible subarrays and calculates their sums. This is a typical brute-force search method because it does not utilize any specific properties about subarray sum to optimize the search process. Although effective for small-scale arrays, it will be very inefficient for large-scale arrays. A more efficient solution is to use a dynamic programming algorithm with a time complexity of O(n).</p><h2> Summarize</h2><p> Linear search is the best search method in unsorted data sets, so it cannot be simply classified as "brute force search". Violent searches usually refer to algorithms that are less efficient and do not take advantage of the specific nature of the problem. Although linear search can be regarded as a form of brute force search in some cases, it is important to select the appropriate algorithm based on the specific situation of the problem. When selecting an algorithm, the efficiency, complexity and ease of implementation should be weighed. For large-scale problems, it is often necessary to find more efficient algorithms instead of simply using brute force search.</p>

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