Linear search, also known as search, is a simple searching algorithm that checks each element of a list in order until a match is found or the entire list has been . The algorithm begins by starting at the beginning of the list and comparing the value with the element. If a match is found, the search is successful, and the position of the element is returned. If there is no match, the search moves to the next element in the list, repeating the comparison until a match is found or the end of the list is reached.
The time complexity of linear search is because it potentially needs to check each item in the list once, where n is the size of the list. The space complexity is typically O(1) since it uses a amount of additional memory, regardless of the size of the input data. This means that while you may use a few variables for control and temporary storage, the usage remains constant and does not depend on the size of the input data.
There are several advantages to using linear search, such as being and easy to understand, making it effective for both sorted and unsorted lists. It works well for small data sets and is particularly useful if the expected item is near the of the list. However, there are also disadvantages, including being inefficient for data sets, having a time complexity of O(n), and being slower compared to other more advanced search algorithms.
Keywords
current | o(n) | beginning | traversed | target | constant | memory | simple | sequential | large |
