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Bloomberg·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Two coding problems back to back for a Bloomberg SWE round. The first was a string decoding thing with nested brackets, the second was a grid pathfinding problem with a fuel mechanic. Both leaned pretty heavily on knowing your data structures.

Questions Asked (2)

Q1

Given an encoded string where k[substring] means the substring is repeated k times (and encodings can be nested), write a function to return the fully decoded string.

Algorithms & Data Structures
Author's notes

Stack-based solution is the move here.

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AI HintsAI Generated

Suggested Approach

Use a stack to handle nested encodings: push the current string and repeat count when encountering '[', and on ']' pop and repeat the substring. Alternatively, use recursion to parse each bracket pair. Clarify constraints and edge cases before coding.

Pro tip: Mention that a stack-based solution runs in O(n) time and space, and that recursion depth could be an issue for deeply nested inputs—showing awareness of trade-offs. Also, test with nested cases like '3[a2[c]]' to demonstrate correctness.

1. Clarify the problem

Ask about input constraints (e.g., valid encoding, character set, max nesting depth) and expected output format. Confirm that k is a positive integer and brackets are balanced.

2. Choose a data structure

Decide between using a stack (iterative) or recursion. Explain that a stack naturally handles nested structures by storing previous strings and repeat counts.

3. Outline the algorithm

Iterate through the string: build digits for k, push current string and k onto stack when '[' is found, and on ']' pop and append the repeated substring to the current string.

4. Analyze complexity

State that time complexity is O(n) where n is the length of the decoded string, and space complexity is O(n) for the stack and output. Mention that recursion uses call stack space.

5. Test with examples

Walk through simple cases like '3[a]' and nested cases like '3[a2[c]]' to verify the logic. Discuss edge cases such as empty string or no brackets.

Key Points to Mention

  • Stack-based approach for handling nested brackets
  • Parsing multi-digit repeat counts
  • Time and space complexity analysis
  • Edge cases: empty string, no brackets, deeply nested
  • Alternative recursive solution and its trade-offs
  • String concatenation efficiency (e.g., using StringBuilder)

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

Q2

Given an m x n grid with a start cell, target cell, blocked cells, and gas station cells, find the minimum number of steps to reach the target. Moving costs 1 fuel, gas stations refill your tank, and you start with a full tank of given capacity. Return -1 if unreachable.

Algorithms & Data Structures
Author's notes

This one looked like a plain BFS until you realize the same cell can be visited multiple times with different fuel levels, so your state has to be (row, col, fuel) not just (row, col).

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AI HintsAI Generated

Suggested Approach

Model the problem as a shortest path on a state graph where each state is (cell, fuel remaining). Use BFS with a deque (0-1 BFS) or Dijkstra, since moving costs 1 step and refueling at gas stations is free. Return the minimum steps when the target is reached, or -1 if unreachable.

Pro tip: Clarify whether refueling at a gas station is optional or mandatory, and whether you can pass through a gas station without refueling. This affects state transitions and can be a common source of bugs.

1. Clarify problem constraints and rules

Ask about grid size, fuel capacity, whether refueling is optional, and if gas stations can be revisited. Confirm movement is 4-directional and blocked cells cannot be entered.

2. Define state representation

Represent each state as (row, col, fuel_left). The start state is (start_row, start_col, capacity). Use a visited set or 2D array of fuel levels to avoid revisiting states.

3. Choose algorithm and transitions

Use BFS with a deque (0-1 BFS) because moving costs 1 step and refueling costs 0. For each state, try moving to adjacent cells if fuel_left > 0; if the new cell is a gas station, set fuel_left to capacity at no extra cost.

4. Handle edge cases and termination

If start equals target, return 0. If target is blocked or unreachable, return -1. Ensure fuel never goes negative and capacity is respected.

5. Analyze complexity and optimize

Time complexity is O(m * n * capacity) and space is O(m * n * capacity). Mention that if capacity is large, consider alternative approaches or pruning.

Key Points to Mention

  • State space expansion: (cell, fuel) pairs to track fuel levels.
  • 0-1 BFS or Dijkstra for shortest path with 0-cost refueling edges.
  • Visited array dimensioned by fuel level to avoid redundant states.
  • Handling of gas stations: refuel to full capacity at no step cost.
  • Edge cases: start equals target, unreachable target, blocked cells.
  • Complexity analysis: O(m * n * capacity) time and space.

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