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Paradromics·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jun 2026

Summary

Coding round for a software engineer role at Paradromics where the main task was building a hash table from scratch. Nothing too exotic but the design discussion around bucket structure went deeper than I expected.

Questions Asked (1)

Q1

Implement a hash table from scratch with a constructor, put(key, value), and get(key) method. No delete required.

Algorithms & Data StructuresTechnical Trade-offsSystem Design
Author's notes

I went with separate chaining using linked lists for the buckets.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then describe a design using an array of buckets with a hash function and collision handling (e.g., separate chaining). Implement the class with put and get methods, and analyze time/space complexity and trade-offs.

Pro tip: Mention that you would handle edge cases like null keys and resizing, and discuss how the load factor affects performance. This shows you think about robustness and scalability.

1. Clarify requirements and constraints

Ask about expected key/value types, performance requirements, and whether resizing is needed. Confirm that delete is not required.

2. Choose data structures and collision resolution

Decide on an array of buckets (e.g., linked lists or dynamic arrays) and a hash function. Explain why separate chaining is a good default.

3. Implement the class

Write the constructor to initialize the bucket array, and implement put and get by hashing the key, finding the bucket, and inserting/retrieving the value.

4. Analyze complexity and trade-offs

Discuss average O(1) time for put/get, worst-case O(n), and the impact of load factor and resizing. Mention alternatives like open addressing.

5. Test and handle edge cases

Walk through examples, including collisions and null keys. Mention potential resizing strategy if the load factor exceeds a threshold.

Key Points to Mention

  • Hash function design and distribution
  • Collision resolution techniques (separate chaining vs. open addressing)
  • Load factor and resizing (rehashing)
  • Time and space complexity analysis
  • Handling of null keys and values
  • Trade-offs between different implementations

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