Description: Binary search is an efficient algorithm for finding an element in a sorted list of elements. This method is based on the divide and conquer strategy, where the data set is halved in each iteration. It starts by comparing the sought element with the middle element of the list. If the sought element is equal to the middle one, the element has been found. If the sought element is smaller, the search is restricted to the lower half of the list; if it is larger, the search continues in the upper half. This process is repeated until the element is found or it is determined that it is not present. The time complexity of binary search is O(log n), making it significantly faster than linear search, which has a complexity of O(n). This algorithm is widely used in computer science and programming and is fundamental in data structures like binary search trees. Its implementation is straightforward and can be done in various programming languages, making it an essential tool for developers and programmers in optimizing searches in large data sets.
History: Binary search was first described in 1946 by John Mauchly in the context of computer programming. Since then, it has evolved and become a fundamental algorithm in computer science, especially in handling sorted data structures.
Uses: Binary search is used in various applications, such as in databases for fast queries, in search algorithms in libraries, and in the implementation of data structures like binary search trees.
Examples: A practical example of binary search is its use in searching for a number in a sorted set of numbers, such as in a list of product prices or in a book index.
