← Early-stage Startup Interview Insights

Early-stage Startup·Software Engineer·Technical Phone Screen·Junior

Junior
Apr 2026

Summary

One coding round, one problem. Not much to say except it was quick and pretty bare bones.

Questions Asked (1)

Q1

Given two arrays, write a function to merge them.

Algorithms & Data Structures
Author's notes

Pretty straightforward on the surface.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the problem: ask about array types, sortedness, duplicates, and whether to merge in-place or return a new array. Then discuss the optimal approach based on the constraints, such as two-pointer for sorted arrays or concatenation for unsorted, and analyze time and space complexity. Finally, write clean code and test with edge cases.

Pro tip: In an early-stage startup, they value pragmatism and communication. Show that you can adapt your solution to real-world constraints (e.g., memory limits, streaming data) and that you consider trade-offs, not just the textbook answer.

1. Clarify requirements

Ask about the nature of the arrays: Are they sorted? Can they contain duplicates? What data types? Should the merge be in-place or return a new array? What are the size constraints?

2. Discuss approaches

Propose multiple solutions: e.g., concatenate and sort (O((n+m) log(n+m))), two-pointer merge for sorted arrays (O(n+m)), or using a heap for merging multiple sorted arrays. Explain trade-offs.

3. Choose and justify

Select the most appropriate approach based on the clarified requirements and explain why it's optimal for the given scenario, considering time and space complexity.

4. Implement and test

Write clean, modular code with meaningful variable names. Walk through an example and test edge cases: empty arrays, one array empty, different lengths, duplicates, and large inputs.

Key Points to Mention

  • Time and space complexity analysis for each approach
  • Handling edge cases: empty arrays, null inputs, different lengths, duplicates
  • In-place vs. out-of-place merging and memory considerations
  • Stability of the merge (preserving order of equal elements)
  • Scalability: how the solution performs with large datasets or streaming data
  • Language-specific optimizations (e.g., using built-in functions like System.arraycopy in Java or list concatenation in Python)

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