What is the optimal time complexity of solving Contains Duplicate?

The optimized solution achieves a time complexity of O(n) by using sorting, mathematical shortcuts, or hash table lookups.

What is the auxiliary space complexity for Contains Duplicate?

The space complexity is O(n) since we only use a minimal/constant amount of extra memory for tracking variables (or auxiliary space if dynamic structures are allocated).

What are the typical edge cases we must handle in Contains Duplicate?

Key edge cases include empty collections, negative or large bounds causing integer overflow, arrays with only one element, or inputs where target criteria are not met.

How can we optimize the brute force approach for Contains Duplicate?

Brute force methods often inspect all possible combinations. We optimize this by sorting the input list to enable binary search, or tracking processed items in a set to avoid redundant nested loop lookups.

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Contains Duplicate

Learn how to solve the 'Contains Duplicate' problem. This detailed resource details brute force and optimized approaches.

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Problem Statement

Easy

Given an integer array nums, return true if any value appears at least twice in the array, and return false if every element is distinct.

Constraints

•1 <= nums.length <= 10^5
•-10^9 <= nums[i] <= 10^9

Examples

Example 1

Input

nums = [1,2,3,1]

Output

true

Example 2

Input

nums = [1,2,3,4]

Output

false

Need a Hint?

Analyze the input constraints. Try sorting first (O(n log n)) or using a hash map/set to track seen elements in O(n) time.

Edge Cases to Watch

Empty list or null input variables
Single item lists/arrays
Extremely large input bounds causing integer or stack overflow

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