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Largest Number At Least Twice of Others

Easy
12.5%
Updated 8/1/2025

Asked by 2 Companies

Largest Number At Least Twice of Others

1. What is this problem about?

The Largest Number At Least Twice of Others coding problem involves scanning an array of integers to find the largest element. Once found, you must verify if this maximum value is at least twice as large as every other number in the array. If it satisfies this condition, you return its index; otherwise, you return -1.

2. Why is this asked in interviews?

Google and Bloomberg often use this "Easy" level question to screen for basic array traversal skills and edge-case awareness. While the logic is straightforward, it requires the candidate to maintain state (tracking both the largest and the second-largest values, or doing a two-pass approach) and handle arrays with very few elements correctly. It tests your ability to write clean, bug-free code for a simple specification.

3. Algorithmic pattern used

This problem fits the Array and Sorting interview pattern, though a single-pass linear scan is the most efficient solution. The most common approach is to iterate through the array once to find the maximum value and its index. Then, perform a second pass to check if max_val >= 2 * current_val for all other elements. Alternatively, you can track the largest and second-largest values in a single pass.

4. Example explanation

Array: [3, 6, 1, 0]. Step 1: The maximum value is 6 at index 1. Step 2: Check other elements:

  • 6 >= 2 * 3 (6 >= 6, True)
  • 6 >= 2 * 1 (6 >= 2, True)
  • 6 >= 2 * 0 (6 >= 0, True) Since 6 is at least double every other number, the answer is index 1.

5. Common mistakes candidates make

Candidates often fail to handle the case where the array has only one element (the answer should be 0, as there are no "other" elements to compare against). Another mistake is comparing the largest number to itself during the verification phase, which could lead to an incorrect result if not handled with an index check. Using sorting is a valid but less efficient O(N log N) approach that might be frowned upon if a linear O(N) solution is expected.

6. Interview preparation tip

For "Array, Sorting interview pattern" questions, always aim for the most efficient time complexity. Even for easy problems, explain your choice of a linear scan over sorting. It shows you prioritize performance and understand the underlying data structure.

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