Search Algorithm Algorithm
A search algorithm is a computational technique designed to explore and retrieve information from a dataset, usually in response to a specific query or problem. Search algorithms are essential in various applications, such as database management, artificial intelligence, web searching, and optimization problems. These algorithms can be broadly classified into two categories: uninformed search algorithms and informed search algorithms. Uninformed search algorithms, such as depth-first search, breadth-first search, and uniform cost search, do not have any additional knowledge about the problem, while informed search algorithms, like A* and best-first search, utilize heuristics to guide the search process.
The efficiency of search algorithms is determined by factors such as time complexity, space complexity, and optimality. Time complexity measures the amount of time an algorithm takes to search through the data, while space complexity refers to the amount of memory used. Optimality is a measure of whether the algorithm can find the best possible solution to the problem. Some search algorithms prioritize finding the solution quickly, while others focus on minimizing the resources used during the search process. As a result, the choice of a search algorithm depends on the specific requirements and constraints of the problem at hand, as well as the available resources, such as computational power and memory.
package Searches;
/**
* The common interface of most searching algorithms
*
* @author Podshivalov Nikita (https://github.com/nikitap492)
**/
public interface SearchAlgorithm {
/**
* @param key is an element which should be found
* @param array is an array where the element should be found
* @param <T> Comparable type
* @return first found index of the element
*/
<T extends Comparable<T>> int find(T array[], T key);
}
