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Openai·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say
May 2026Remote

Summary

Got a multi-part coding problem at OpenAI for a SWE role, all centered around IPv4 addresses and CIDR blocks. Three parts, each building on the last, and by part three I was definitely sweating a little.

Questions Asked (3)

Q1

Implement two functions to convert an IPv4 address string to a 32-bit unsigned integer and back again.

Algorithms & Data Structures
Author's notes

This part was fine.

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AI HintsAI Generated

Suggested Approach

Clarify the requirements (e.g., input validation, error handling, endianness) and then implement the conversion using bitwise operations for efficiency. For string to integer, split by dots, validate each octet, and combine using shifts; for integer to string, extract each octet with shifts and masks, then join with dots.

Pro tip: Mention that you would use unsigned 32-bit integer to avoid sign issues and discuss how to handle invalid inputs gracefully, showing attention to robustness.

1. Clarify requirements and edge cases

Ask about input validation, error handling, and expected output format. Consider edge cases like leading zeros, out-of-range octets, and non-numeric characters.

2. Design the string-to-integer conversion

Split the string by '.', validate each part is a number between 0 and 255, then combine using bitwise left shifts and addition.

3. Design the integer-to-string conversion

Extract each octet using right shifts and bitwise AND with 0xFF, then convert to string and join with dots.

4. Implement and test

Write clean code with appropriate error handling. Test with valid addresses, boundary cases (0.0.0.0, 255.255.255.255), and invalid inputs.

5. Analyze complexity and optimizations

Discuss time and space complexity (O(1) for fixed-size IPv4) and potential optimizations like avoiding string splitting for performance-critical code.

Key Points to Mention

  • Bitwise operations: left shift (<<) and bitwise OR/AND for combining and extracting octets.
  • Input validation: ensuring each octet is an integer between 0 and 255, and handling invalid formats.
  • Use of unsigned 32-bit integer to avoid sign issues and ensure correct representation.
  • Endianness: clarify that the conversion is independent of host endianness as it's a logical mapping.
  • Edge cases: 0.0.0.0, 255.255.255.255, leading zeros, and empty strings.
  • Time and space complexity: O(1) due to fixed number of octets, and potential optimizations.

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

Q2

Given a start and end IPv4 address, iterate through every address in the range in increasing order. Discuss the complexity and how you'd handle very large ranges.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

I jumped straight to returning a list and they pushed back immediately asking what happens when the range is like half the address space.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., inclusive/exclusive, input format, memory limits) and then present a solution that treats IPv4 addresses as 32-bit unsigned integers, incrementing from start to end. Discuss the time complexity as O(N) where N is the number of addresses, and address handling large ranges by streaming or using generators to avoid memory issues, and consider parallelization or chunking for extreme cases.

Pro tip: Mention that you would use a generator or iterator to yield addresses one by one, which keeps memory usage constant regardless of range size. Also, note that for extremely large ranges, you might need to consider distributed processing or external sorting if the output must be ordered.

1. Clarify requirements and constraints

Ask about inclusivity of endpoints, input format (string vs integer), expected output format, and any memory or time constraints. This shows attention to detail and avoids incorrect assumptions.

2. Represent addresses as integers

Convert IPv4 addresses to 32-bit unsigned integers using bitwise operations or built-in functions (e.g., inet_aton). This simplifies iteration and arithmetic.

3. Implement iteration with a generator

Use a loop or generator to yield each address from start to end, converting back to dotted-decimal format. This ensures O(1) memory usage and allows early termination.

4. Analyze complexity and scalability

State that time complexity is O(N) where N is the number of addresses, and space is O(1) with a generator. For very large N (e.g., billions), discuss trade-offs: streaming, chunking, parallel processing, or using external storage if output must be persisted.

5. Discuss edge cases and optimizations

Handle edge cases like start > end, same address, or full range (0.0.0.0 to 255.255.255.255). Mention potential optimizations like skipping reserved ranges if applicable, or using SIMD for bulk conversion.

Key Points to Mention

  • IPv4 addresses are 32-bit integers, so iteration is simply incrementing an integer.
  • Time complexity is O(N) where N is the number of addresses in the range; space complexity is O(1) with a generator.
  • For large ranges, use lazy evaluation (generators) to avoid loading all addresses into memory.
  • Consider parallelization or chunking to speed up processing if the operation per address is expensive.
  • Be mindful of integer overflow when incrementing near 255.255.255.255; use unsigned 32-bit or 64-bit integers.
  • If the output must be ordered and stored, consider external sorting or writing to disk in chunks.

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

Q3

Given a starting IPv4 address and a count n, return the minimum set of CIDR blocks that exactly covers those n consecutive addresses.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

This is where it got hard.

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AI HintsAI Generated

Suggested Approach

Clarify that the goal is to partition the range [start, start+n-1] into the fewest aligned CIDR blocks. Use a greedy algorithm: at each step, find the largest block that starts at the current address, fits within the remaining range, and is properly aligned (block size divides the address). Repeat until the range is covered.

Pro tip: Mention that this is the classic IP range aggregation problem and that the greedy approach is optimal because any CIDR block covering the current address must start at or before it; choosing the largest aligned block minimizes the count. Also note edge cases like n=0, overflow, and the special case of a single address (/32).

1. Clarify requirements and constraints

Confirm that the input is a starting IPv4 address (as a 32-bit integer) and a count n, and that the output should be a list of CIDR blocks in any order. Discuss edge cases: n=0, n=1, and potential overflow when start + n exceeds 2^32.

2. Represent addresses as integers

Convert the IPv4 address to a 32-bit unsigned integer for easier bit manipulation. Explain that CIDR blocks correspond to ranges where the first k bits are fixed and the remaining 32-k bits vary.

3. Greedy block selection

While n > 0, compute the largest block size (power of two) that: (a) does not exceed n, (b) is aligned to the current address (i.e., address % block_size == 0), and (c) fits within the 32-bit space. Add that block to the result, advance the address by block_size, and reduce n by block_size.

4. Convert blocks to CIDR notation

For each selected block, compute the prefix length as 32 - log2(block_size). Format the block as 'address/prefix'. Ensure the address is the network address (already aligned).

5. Analyze complexity and correctness

Argue that the greedy choice is optimal: any valid cover must include a block starting at the current address, and choosing the largest possible block cannot increase the total number of blocks. The algorithm runs in O(log n) time and uses O(log n) space for the output.

Key Points to Mention

  • CIDR blocks must be aligned: the block size (power of two) must divide the starting address.
  • Greedy algorithm: at each step, pick the largest aligned block that fits within the remaining range.
  • Bit manipulation: use bitwise operations to find the largest block size (e.g., lowbit of address, or trailing zeros).
  • Edge cases: n=0 (return empty list), n=1 (return /32), and overflow when start + n > 2^32.
  • Complexity: O(log n) iterations, each O(1), so very efficient.
  • Proof of optimality: exchange argument or induction showing greedy minimizes block count.

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