The purpose of searching algorithms is to find out whether a specific element is present in a data structure or not. If the element can be found, an operation relevant to it will be performed. According to the traversing mechanism, search algorithms can be based on linear search or binary search. The primary difference between linear search and binary search is that while the former depends on sequential comparison, the latter follows the divide-and-conquer rule to find an element.
Understanding the difference between linear search and binary search is crucial to figure out which method to use for searching an element. Dive into this article to gain details about the difference between linear search and binary search.
Linear search is a simple searching algorithm based on a sequential model. Unlike binary search, the linear search algorithm checks every item in a list to find the required element. Like stacks in data structures, a linear search algorithm will check elements in a particular order. A linear search, sometimes referred to as a sequential search and is suitable for searching over a small array or an unsorted array.
When the element you are looking for is in the first position of the data structure, only one comparison would be sufficient. But an N number of comparisons will be required to find elements in the last position.
Binary search is an algorithm for finding an item from a sorted list of items. It is called binary search because it splits the array into two halves as part of the algorithm. It is also known as half-interval search, logarithmic search, or binary chop.
When you compare linear search and binary search, the binary search seems to be faster. But a significant difference between linear search and binary search is that you need to sort the items in a list before using the binary search algorithm. Click on this to understand more about sorting in data structures.
Basically, the binary search can help you find any item by comparing the middlemost item of the collection. Therefore, one massive difference between linear search and binary search is that binary search can be completed within a short span.
Several exciting data science projects for beginners demand the application of searching algorithms. Data analytics professionals often need to use linear vs. binary search for operations. You can understand everything about data science and analytics here: Data Science Vs. Data Analytics: Key Difference Between Data Science & Data Analytics. But if you want to understand the difference between linear search and binary search, keep scrolling down.
In linear search vs binary search, linear search will iterate through different elements. The major difference between linear search and binary search in terms of working is that the linear search compares all the elements with the key that needs to be searched. But binary search can reduce the size of the array which should be searched, and the binary search compares the key with the mid element.
In linear search vs. binary search, the linear search can only be implemented on data structures allowing at least one-way traversal like linked lists and arrays whereas, the binary search can only be implemented on data structures supporting only two-way traversal.
The difference between linear search and binary search is that linear search is simpler to use and is less complex whereas the binary search is comparatively complicated.
A business analyst course will offer more details about the simplicity and complexity of linear search vs. binary search.
In linear search vs binary search, the latter is more complicated. But the binary search can be performed much faster, and there is a huge difference between linear search and binary search in terms of speed comparison. Basically, in large data set the speed of liner search become slow whereas, speed of binary search would be faster and will cost less.
A major difference between linear search and binary search can be spotted in terms of flexibility. Linear search is flexible with different data structures like lists, linked lists, arrays, and more. However, the binary search cannot be performed on every data structure. Since binary search is useful for multi-directional traversal, data structures like a single list cannot be used.
Linear search isn’t efficient for large data sets. But when you compare the difference between linear search and binary search, binary search will be perfect for large datasets.
A difference between linear search and binary search can also be spotted in terms of prerequisites. In Linear vs binary searches, the linear search can be performed on sorted as well as random data, however binary search is only applicable to sorted datasets.
A difference between linear search and binary search is also prevalent in terms of use cases. The binary search is useful for large and sorted datasets.
Binary search can be implemented of only one-dimensional array whereas, Linear search can be used on both single and multidimensional array.
You can check the real-time application of data structures here.
Comparison Factor | Linear Search | Binary Search |
---|---|---|
Algorithm | Sequential searching | Divide and conquer approach |
Sorted List | Not mandatory | mandatory |
Working | Checks every element sequentially as long as a match can’t be found | Divides a list in two halves from the middle on every iteration as long as the position of a target value cannot be spotted |
Implementation | Useful for data structures that enable traversal in a single way like arrays and linked list | Useful only for data structures supporting two way traversal |
Simplicity and Complexity | Simple and less complex | More complicated than linear search |
Time Required | 0 (n) | 0 (log n) |
Efficiency | Not useful for large datasets | More efficient for finding elements in large datasets |
Best Case | When an element can be found in the first position of an array | When an element can be found at first split, the middle element of an array |
Also Called | Sequential search | Half-interval search or logarithmic search |
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