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here are the notes on "Data Structures and Algorithms: Linear vs Binary Search" in Markdownformat:
Importance of Best, Worst, and Average-case Analysis
When analyzing algorithms, it is essential to consider their best, worst, and average-case time
complexities to understand their efficiency and performance.
Linear Search vs Binary Search
Linear Search: An algorithm that searches for a specific value in an array by iterating through
it sequentially until the desired value is found.
Binary Search: A search algorithm that operates on a sorted array, repeatedly dividing it in
half until it finds the target value or determines it's not in the array.
Unique Features of Sorted Arrays for Binary Search
Binary search is possible only on sorted arrays, where the elements are in ascending or descending
order. The sorted array enables binary search to divide the array into two halves recursively, reducing
the search space by half in each iteration.
Importance of Array Sorting in Binary Search
Sorting the array before performing binary search is crucial because binary search assumes that the
array is already sorted. An unsorted array will result in incorrect search results, and the algorithm
efficiency will significantly deteriorate.
Time Complexity of Linear and Binary Search
Linear Search: The worst-case time complexity is O(n) because it has to iterate through the
entire array.
Binary Search: The worst-case time complexity is O(log n) because it reduces the search
space by half in each iteration.
Understanding Binary Search Algorithm - Code Example
Here's an example of the binary search algorithm in Python:
def binary_search(array, target):
left = 0
right = len(array) - 1
while left <= right:
mid = (left + right) // 2
mid_value = array[mid]
if mid_value == target:
return mid
elif mid_value < target:
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