← Capital One Interview Insights

Capital One·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Capital One software engineer interview with a digit-counting array problem. Pretty focused on the algorithmic side, nothing behavioral from what I can tell. The problem itself looks deceptively simple but has a few gotchas worth thinking through.

Questions Asked (1)

Q1

Given a non-negative integer array, count how many elements have the digit '0' appearing an odd number of times in their decimal representation. Also discuss the time complexity of your solution.

Algorithms & Data Structures
Author's notes

My first instinct was to just convert each number to a string and loop over the characters, which works fine.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Clarify the problem and edge cases, then propose a solution that iterates through each number, converts it to a string, counts the occurrences of '0', and checks if the count is odd. Discuss the time complexity as O(n * d) where n is the array length and d is the average number of digits per number.

Pro tip: Mention that you can optimize by using arithmetic operations (modulo and division) instead of string conversion to avoid extra space and potentially improve constant factors, and always test with edge cases like 0 and numbers with multiple zeros.

1. Clarify the problem

Restate the problem in your own words and ask clarifying questions about input constraints, such as the maximum value of elements and array size, to determine the optimal approach.

2. Outline the approach

Explain that you will iterate through each element, count the number of '0' digits in its decimal representation, and increment a counter if the count is odd.

3. Detail the implementation

Describe how to count zeros: either convert the number to a string and count '0' characters, or use a while loop with modulo 10 and division by 10. Handle the special case of 0 itself.

4. Analyze complexity

State that the time complexity is O(n * d) where n is the number of elements and d is the average number of digits per element, and space complexity is O(1) if using arithmetic, or O(d) if using string conversion per element.

5. Test with examples

Walk through a small example, such as [0, 10, 100, 1000], to verify the logic and edge cases.

Key Points to Mention

  • Edge case: the number 0 has one zero, which is odd, so it should be counted.
  • Time complexity analysis: O(n * d) where d is the number of digits, which is effectively O(n log(max_value)).
  • Space complexity: O(1) extra space if using arithmetic operations, or O(d) if using string conversion per element.
  • Alternative approaches: using string conversion is simpler but may have overhead; arithmetic avoids string allocation.
  • Optimization: early termination if the count of zeros exceeds the number of digits? Not applicable, but can mention that we only need parity, so we can toggle a boolean instead of counting.
  • Handling large integers: if numbers can be very large, string conversion might be necessary, but in typical integer ranges arithmetic is fine.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.