What if you could find the smallest number in a twisted list without checking every single one?
Why Find Minimum in Rotated Sorted Array in DSA C?
Imagine you have a list of numbers sorted from smallest to largest, but then someone rotated it. For example, instead of 1, 2, 3, 4, 5, you get 3, 4, 5, 1, 2. Now, you want to find the smallest number quickly.
If you check each number one by one from the start, it will take a long time if the list is very big. This slow method wastes time and can cause mistakes if you lose track.
Using a smart method called binary search, you can find the smallest number fast by cutting the list in half repeatedly. This way, you don't check every number, just a few, saving time and effort.
int findMin(int* arr, int size) {
int min = arr[0];
for (int i = 1; i < size; i++) {
if (arr[i] < min) min = arr[i];
}
return min;
}int findMin(int* arr, int size) {
int left = 0, right = size - 1;
while (left < right) {
int mid = left + (right - left) / 2;
if (arr[mid] > arr[right]) left = mid + 1;
else right = mid;
}
return arr[left];
}This method lets you quickly find the smallest number in a rotated list, even if the list is very large.
Think about a circular queue of tasks that got shifted. Finding the earliest task quickly helps in scheduling without checking all tasks.
Manual search checks every element, which is slow.
Binary search cuts the search space in half each time, making it fast.
Useful for rotated sorted lists to find the minimum efficiently.
Practice
[4, 5, 6, 7, 0, 1, 2]?Solution
Step 1: Understand the rotated sorted array
A rotated sorted array is originally sorted but then shifted. The smallest element is where the rotation happened.Step 2: Identify the minimum element
The minimum element is the smallest number and marks the rotation point in the array.Final Answer:
To find the smallest element which is the rotation point -> Option AQuick Check:
Minimum element = rotation point [OK]
- Looking for the largest element instead
- Trying to count rotations instead of finding minimum
- Sorting the array again unnecessarily
nums of size n?Solution
Step 1: Set pointers to array bounds
In C, array indices start at 0, so left should be 0 and right should be n-1.Step 2: Declare mid variable
Mid is used to find the middle index between left and right.Final Answer:
int left = 0, right = n - 1; int mid; -> Option CQuick Check:
Array indices start at 0, so left=0 and right=n-1 [OK]
- Setting left or right outside valid index range
- Using right = n which is out of bounds
- Starting left at 1 instead of 0
int nums[] = {4, 5, 6, 7, 0, 1, 2};
int left = 0, right = 6, mid;
while (left < right) {
mid = left + (right - left) / 2;
if (nums[mid] > nums[right]) {
left = mid + 1;
} else {
right = mid;
}
}
printf("%d", nums[left]);Solution
Step 1: Understand the binary search logic
The code compares middle element with right element to decide which half contains the minimum.Step 2: Trace the loop to find minimum
Loop narrows down to index 4 where value is 0, the smallest element.Final Answer:
0 -> Option BQuick Check:
Minimum element found = 0 [OK]
- Printing nums[mid] instead of nums[left]
- Confusing greater than and less than in condition
- Not updating left or right correctly
nums of size n:
int left = 0, right = n - 1, mid;
while (left <= right) {
mid = left + (right - left) / 2;
if (nums[mid] > nums[right]) {
left = mid + 1;
} else {
right = mid - 1;
}
}
return nums[left];Solution
Step 1: Analyze loop condition
Using left <= right can cause infinite loop or out-of-bound access because left can surpass right.Step 2: Correct loop condition
Changing to left < right ensures the loop stops when left meets right, correctly locating minimum.Final Answer:
The loop condition should be left < right, not left <= right -> Option DQuick Check:
Loop condition left < right avoids infinite loops [OK]
- Using <= in loop condition causing infinite loops
- Incorrectly adjusting right pointer by mid - 1
- Returning nums[left] without proper loop exit
nums that may contain duplicates, which modification to the binary search approach helps correctly find the minimum element?
A) Always move left pointer when nums[mid] == nums[right]
B) Increase left pointer by one when nums[mid] == nums[right]
C) Decrease right pointer by one when nums[mid] == nums[right]
D) Return nums[mid] immediately when nums[mid] == nums[right]Solution
Step 1: Understand duplicates in rotated array
Duplicates can cause ambiguity when nums[mid] equals nums[right], so normal binary search fails.Step 2: Adjust right pointer carefully
When nums[mid] == nums[right], decreasing right by one helps skip duplicate safely without missing minimum.Final Answer:
Decrease right pointer by one when nums[mid] == nums[right] -> Option AQuick Check:
Handle duplicates by reducing right pointer [OK]
- Moving left pointer instead causing missed minimum
- Returning mid value prematurely
- Not handling duplicates causing wrong answer
Ready to prove it?
Pass the test and this pattern moves unknown
