Binary Search Algorithm
Binary Search is a search algorithm that finds the position of a target value within a sorted array. It efficiently locates the target value by repeatedly dividing the search interval in half. It is a highly efficient algorithm compared to linear search, especially for large datasets.
How Binary Search Works
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Array Partitioning:
- Compare the target value with the middle element of the array.
- If the target value matches the middle element, the position is returned.
- If the target value is less than the middle element, search the left half of the array.
- If the target value is greater, search the right half of the array.
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Repeated Search:
- Repeat the process in the selected half of the array until the target value is found or the array becomes empty.
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Completion:
- The search is complete when the target value is found or when the entire array is searched.
Key Features
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Efficient Searching: Binary Search provides efficient search capabilities, especially on large, sorted datasets.
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Divide and Conquer: It uses a divide-and-conquer strategy to quickly find the target value.
Efficiency
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Time Complexity: Binary Search has a time complexity of O(log n), where n is the number of elements in the array.
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Space Complexity: The space complexity is O(1) as it uses a constant amount of extra space.
Applications
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Searching in Databases: It is commonly used in computer science and information systems for searching through sorted databases.
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Efficient Searching: Binary Search is valuable in applications like searching in libraries, search engines, and array-based data structures.
Advantages
- Efficiency: It is much more efficient than linear search, especially for large datasets.
- Applicability: Binary Search works on sorted arrays and is simple to implement.
Disadvantages
- Sorted Data Requirement: The input array must be sorted, which can be a limitation in certain scenarios.
- Limited Applicability: It might not be suitable for unsorted or constantly changing datasets.
Binary Search Algorithm Implementation in JavaScript
Here's an example of Binary Search implemented in JavaScript:
function binarySearch(arr, target) {
let left = 0;
let right = arr.length - 1;
while (left <= right) {
const mid = Math.floor((left + right) / 2);
if (arr[mid] === target) {
return mid;
} else if (arr[mid] < target) {
left = mid + 1;
} else {
right = mid - 1;
}
}
return -1;
}
// Example usage
const sortedArray = [2, 3, 5, 8, 12, 18, 21, 30, 37];
const targetValue = 12;
const position = binarySearch(sortedArray, targetValue);
console.log("Target value found at position:", position);