Bloomberg·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

Bloomberg SWE interview with a linked list problem that looked manageable on the surface but had enough depth to trip you up if you weren't careful about the traversal order.

Questions Asked (1)

Given a linked list where each node has both a next pointer and a down pointer (the down pointer leads to a nested sub-list), flatten the entire structure into a single list using only next pointers. The order must follow a depth-first traversal, meaning you fully descend into each down list before continuing along the next pointer.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

My first instinct was to just splice recursively and it worked, but I fumbled explaining the time complexity.

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AI HintsAI Generated

Suggested Approach

Clarify the structure and constraints, then propose a recursive depth-first traversal that flattens each sub-list and connects it to the parent's next pointer. Discuss iterative alternatives and trade-offs, and analyze time/space complexity.

Pro tip: Emphasize that the down pointers should be set to null after flattening to avoid cycles, and mention that an iterative approach using a stack can achieve O(1) extra space if recursion depth is a concern.

1. Clarify the Problem

Confirm the structure: each node has next and down pointers, and down leads to a sub-list. Ensure the flattening order is depth-first and that only next pointers are used in the result.

2. Choose an Approach

Decide between recursive and iterative solutions. Recursive is simpler but may risk stack overflow; iterative with a stack is more robust for deep lists.

3. Implement the Flattening

For recursion: flatten the down list, then recursively flatten the next list, and connect the tail of the down list to the flattened next list. For iteration: use a stack to process nodes, pushing next before down to ensure depth-first order.

4. Handle Edge Cases

Consider empty lists, single node, and lists with only down pointers. Ensure down pointers are set to null to avoid cycles.

5. Analyze Complexity

Time complexity is O(N) where N is total nodes. Space complexity is O(D) for recursion depth or O(D) for stack in iterative, where D is maximum nesting depth.

Key Points to Mention

Depth-first traversal order: fully process down before next.
Recursive vs iterative trade-offs: recursion simplicity vs stack overflow risk; iterative with explicit stack for O(1) extra space if tail recursion optimized.
In-place modification: reuse existing nodes, set down pointers to null.
Time complexity O(N), space complexity O(D) where D is depth.
Handling edge cases: empty list, single node, deep nesting.
Potential follow-up: flattening a multilevel doubly linked list or handling cycles.

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