Google·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026

Summary

Google SWE coding round, one problem the whole time. Pretty focused session, the kind where you can tell they want to see how deep you go on a single thing rather than rushing through a bunch of questions.

Questions Asked (1)

You're given two arrays and an integer k. Delete elements from the second array so that its first k elements (after deletion) have no values in common with the first k elements of the first array. Return the minimum number of deletions needed, or the resulting array.

Algorithms & Data Structures

Author's notes

My first instinct was to just iterate both arrays and compare, which is obviously slow.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and edge cases, then propose an efficient algorithm using hash sets to track common elements and a greedy strategy to delete elements from the second array. Analyze time and space complexity, and discuss potential optimizations or alternative approaches.

Pro tip: Demonstrate strong communication by restating the problem in your own words and walking through a small example before coding. This ensures alignment with the interviewer and showcases structured thinking.

1. Clarify the problem

Ask questions to confirm the exact requirements: Are we deleting elements from the second array only? Do we need to return the minimum deletions or the resulting array? What if k is larger than the array length? Are there duplicate values?

2. Identify common elements

Use a hash set to store the first k elements of the first array for O(1) lookups. Then iterate through the second array to find which elements are common with this set.

3. Determine deletions

Greedily delete common elements from the second array, prioritizing deletions that are not among the first k elements to minimize impact. Count the minimum deletions needed so that the first k remaining elements have no common values with the first array's first k elements.

4. Construct result if needed

If the problem asks for the resulting array, simulate the deletions or build a new array with the remaining elements, ensuring the first k elements satisfy the condition.

5. Analyze complexity and test

State the time and space complexity (typically O(n+m) time and O(k) space). Walk through edge cases like k=0, no common elements, or all elements common.

Key Points to Mention

Use of hash sets for efficient membership testing.
Greedy strategy to minimize deletions by prioritizing removal of elements not in the first k positions.
Handling duplicates and ensuring the first k elements after deletion are considered.
Time and space complexity analysis.
Edge cases: k=0, k larger than array length, no common elements, all elements common.
Clear communication and step-by-step reasoning.

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