what is binary search

Binary Search Vs. Linear Search: What’s The difference


As two of the most popular searching methods in computer science, binary search and lingerer search are two major subjects. However, some new learners find it a little confused. Thus, in today’s article, algo.monster will compare binary search and linear search to tell the difference between the two. 

General ideas of the two

The simplest search algorithm is linear search. Also, we can call it sequential search. In fact, this search is for a specific value in a list, by looking at every element of the list. On the other hand, binary search can also be used to find a specific value in a sorted listing. Actually, binary search reduces the number of elements that must be checked in each iteration, which decreases the time required to find the item.

Before we come to a more detailed comparison, let’s check out the definitions of these two searching methods.

What is binary search? 

A binary search can be applicable to find a specific item in a sorted listing. And the method begins by comparing the search element to the elements at the top of the list. If they are equal, the method returns the position of each element. On the other hand, the method will stop if the search element is greater or equal to the middle element and it will start the process again with the top half of the sorted lists. Also, the method will only use the top half of the sorted lists if the searched element is lower than the middle element. However, the method will return a unique value indicating if the searched element isn’t in the list. 

what is binary search

The search method reduces the number of elements that can be compared in each iteration by reducing the number of elements to half, depending on the results of the comparison. This searching method is therefore performed in logarithmic times, with an average case performance of o(log n).

What is linear search?

As have mentioned above, linear search is the simplest method of searching. It checks every element in a list sequentially until it locates a specific element. Also, linear search requires a sequence, collection, or string as input. The output is the item to be searched. If the item in question is found within the given sequence, the output will be true. Then, it’s false if it’s not. 

Thus, this method will check every item in the list until it finds the item. In the worst case, it will go through all elements of the list before it locates the element. 

Linear search is complex at o(n). It is therefore not recommended for large lists of elements. This is however very easy and simple to do.

General idea: Binary search versus linear search

As a searching method, linear won’t stop searching every record until it finds the target element. Also, in the linear search, a linked list allows for faster insert and deletion than an array. Generally, linear search is slower than binary search for sorted arrays, except when the array is very short. However, it will be another story in an unsorted array. Sorting algorithms that use comparing elements such as merge sort and quicksort require at most O(log n), in the worst case. Binary search can be applicable to approximate match, which linear search can’t. You can find the smallest or largest element in a sorted array. However, it won’t work when you’re dealing with an unsorted array.

What’s the difference between linear search and binary search?

Both binary search and linear search can be used to search for information, but they have many differences. Liner search is able to operate on unsorted lists. The former search works only with sorted lists. Linear search is simpler and easier to use than binary. Because of its slow average-case performance, the linear search cannot be used with large lists. Binary search, on the other hand, is more efficient and can be used with large lists. However, it can be difficult to implement the binary search. A study showed that only five of twenty books contained the exact code.

Complexities: comparing binary search with linear search

Generally speaking, the solution binary search offers are more efficient and optimized than linear search gives. This is especially true when elements are sorted in the right order. Let’s check out the complexities of these two searching methods.

Time complexity

Linear Search: N – In linear search, we go through an array to see if there is a key. The worst-case scenario is that the element will not be found at the end of an array. Therefore, we will have to traverse the end.

Binary Search: O (log N) – It cuts down on the search time because we only need to look at the middle of an array. We are continually reducing our search to the area where the element is found.

Space Complexity

Linear Search: O(1) We don’t use any extra space, so the space complexity will only be O(1).

Binary Search: Since we are not using extra space, the space complexity will be O(1).

Apart from these two, is there another way to search for an element within an array?

While binary search and linear search are both popular methods of searching, interpolation is a more effective method. This is an optimized Binary Search version where all elements are evenly distributed.

In fact, this method works because in binary search we always look at the middle of an array. Also, this method allows the search to be directed to any location the key is located. If the key is found near the end of an array, then the search will begin at the end.


Despite the difference, both search methods are practical and efficient. Hence, which is better mainly depends on various applications. Actually, if an array is the data structure as a sorted array, binary search will be the best option for a quick search! 

For more useful information or courses, please visit algo.monster. You’ll definitely find more about algorithms including these two and more.

Uneeb Khan

I love Web Surfing. Writer. Blogger. Self-Believer.| I love to grab the latest news Knowledge and share the fresh dose of technology, lifestyle, travel, how-to’s, life lessons through the social platform and my blog. At my free time I love to read new things and write the post of my blog and share with my social locality.