The problem titled “Element Appearing More Than 25% In Sorted Array” on Leetcode poses an interesting challenge. It may initially seem simple due to the sorted nature of the array, but the constraints related to time complexity make it a noteworthy problem to explore in detail. In this guide, we will discuss various ways to solve this problem using Python.
Table of Contents
- Problem Description
- Naive Approach: Brute-force Algorithm
- Optimized Approach 1: Counting Sequences
- Testing and Validation
- Time and Space Complexity Analysis
- Conclusion
1. Problem Description
You’re given a sorted integer array, arr
, where the condition is that an integer x
will appear more than 25% of the time in the array. Your task is to find and return that integer x
.
Constraints:
- The array is non-empty and has a length in the range [1,10^4].
- The array contains integers in the range [−10^5,10^5].
Example:
Input: arr = [1, 2, 2, 6, 6, 6, 6, 7, 10]
Output: 6
2. Naive Approach: Brute-force Algorithm
Algorithm:
- Initialize a counter variable to keep track of occurrences.
- Iterate through the sorted array and count consecutive similar numbers.
- If a number occurs more than 25% of the time, return that number.
Python Code:
def findSpecialInteger(arr):
threshold = len(arr) // 4
count = 1
for i in range(1, len(arr)):
if arr[i] == arr[i - 1]:
count += 1
if count > threshold:
return arr[i]
else:
count = 1
return arr[0]
print(findSpecialInteger([1, 2, 2, 6, 6, 6, 6, 7, 10])) # Output should be 6
3. Optimized Approach 1: Counting Sequences
Since the array is sorted, if a number occurs more than 25% of the time, then one of its instances will definitely appear at an index that is a multiple of the array’s length divided by 4.
Algorithm:
- Calculate the threshold index
threshold_idx = len(arr) // 4
. - Check the numbers at indices
threshold_idx, 2 * threshold_idx, 3 * threshold_idx
and so on.
Python Code:
def findSpecialInteger(arr):
threshold_idx = len(arr) // 4
for i in range(threshold_idx, len(arr)):
if arr[i] == arr[i - threshold_idx]:
return arr[i]
return -1 # Should never reach this point based on problem constraints
print(findSpecialInteger([1, 2, 2, 6, 6, 6, 6, 7, 10])) # Output should be 6
4. Testing and Validation
While testing, ensure that:
- The array is sorted.
- Test with edge cases like minimum and maximum array lengths.
- Include negative numbers in your test cases.
5. Time and Space Complexity Analysis
- Naive Approach:
- Time Complexity: O(n)
- Space Complexity: O(1)
- Optimized Approach 1:
- Time Complexity: O(n)
- Space Complexity: O(1)
6. Conclusion
In this guide, we have discussed multiple approaches to solve the “Element Appearing More Than 25% In Sorted Array” problem on Leetcode. We started with a naive approach and then discussed an optimized method. It’s always crucial to consider time and space complexities to come up with the most efficient solution.