← Citadel Interview Insights

Citadel·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Citadel SWE interview with a coding question that was a slightly toned-down version of a known LeetCode problem. Nothing too wild, but you still need to know your data structures.

Questions Asked (1)

Q1

Solve a coding problem involving efficient data lookup and list traversal, similar in structure to a well-known LeetCode problem but slightly simplified.

Algorithms & Data Structures
Author's notes

Easier than the version I'd seen before, which honestly made me second-guess myself for a second.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and examples first, then discuss a brute-force solution before optimizing with a hash map for O(1) lookups and a single pass for traversal. Walk through the code, test edge cases, and analyze time/space complexity.

Pro tip: At Citadel, interviewers value clean, efficient code and strong communication; verbalize your thought process and trade-offs, and always consider edge cases like empty inputs or duplicates.

1. Understand and Clarify

Restate the problem in your own words, ask clarifying questions about input size, data types, and expected output, and confirm with examples.

2. Discuss Brute Force

Propose a straightforward solution (e.g., nested loops) and analyze its time and space complexity to establish a baseline.

3. Optimize with Data Structures

Identify that a hash map can provide O(1) lookups and design an algorithm that traverses the list once while storing needed information.

4. Code and Test

Write clean, modular code, then walk through it with normal and edge cases (empty list, single element, duplicates) to verify correctness.

5. Analyze and Conclude

State the final time and space complexity, discuss potential improvements or trade-offs, and summarize the solution.

Key Points to Mention

  • Hash map for O(1) average-time lookups
  • Single-pass traversal to achieve O(n) time complexity
  • Handling edge cases: empty input, single element, duplicates
  • Space-time trade-off: using extra space for speed
  • Clear variable naming and modular code
  • Complexity analysis: O(n) time, O(n) space

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