ServiceNow·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

Pure coding round at what seemed like an acquired subsidiary under ServiceNow. One question, LeetCode-style, nothing behavioral at all.

Questions Asked (1)

Given a sorted integer array, a target value, and an integer k, find the k closest elements to the target in the array.

Algorithms & Data Structures

Author's notes

Classic binary search plus two-pointer setup.

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AI HintsAI Generated

Suggested Approach

Use binary search to find the insertion point of the target, then use two pointers to expand outward and collect the k closest elements. Alternatively, use a sliding window of size k and move it to minimize the distance to the target. Discuss time and space complexity and handle edge cases like duplicates and ties.

Pro tip: Clarify tie-breaking rules (e.g., prefer smaller elements when distances are equal) and mention that the array is sorted, so binary search is optimal. Also, consider if k is larger than the array size and handle that gracefully.

1. Clarify requirements and edge cases

Ask about tie-breaking, whether the result should be sorted, and constraints like k > array length. Confirm the array is sorted and contains integers.

2. Choose an approach

Decide between binary search + two pointers or sliding window. Explain why binary search is efficient for sorted arrays, achieving O(log n + k) time.

3. Implement the algorithm

Write code to find the closest elements. For binary search, find the insertion point, then compare distances from left and right pointers, adding the closer element to the result until k elements are collected.

4. Analyze complexity and test

State time and space complexity. Walk through examples, including edge cases like target smaller than all elements, larger than all, and duplicates.

Key Points to Mention

Binary search to find the closest position in O(log n) time.
Two-pointer technique to expand outward and select k closest elements.
Handling ties by preferring the smaller element (if specified).
Time complexity: O(log n + k) and space complexity: O(k) for the output.
Edge cases: k >= array length, target outside array range, duplicates.
Alternative approach: sliding window of size k with O(n) time, but binary search is better for large n.

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