NURO·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Apr 2026

Summary

Nuro SWE interview threw a graph problem dressed up in autonomous vehicle flavor. Basically LC 269 with a coat of paint, which I only realized mid-solve when the adjacency structure clicked.

Questions Asked (1)

Given a list of priority-ordered observations of autonomous delivery vehicles, derive a single consistent global ordering of vehicle priorities across all observations, or report that no valid ordering exists.

Algorithms & Data Structures

Author's notes

It's LC 269 wearing a disguise.

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AI HintsAI Generated

Suggested Approach

Model each observation as a directed edge in a graph where vehicles are nodes, then perform a topological sort to find a global ordering. If a cycle is detected, report that no valid ordering exists.

Pro tip: Clarify whether the observations are strict total orders or partial orders; this affects whether you need to handle ties or multiple valid orderings. Also, mention that topological sort can be done with DFS or Kahn's algorithm, and discuss trade-offs.

1. Understand the problem

Confirm that each observation is a list of vehicles in priority order, meaning earlier vehicles have higher priority. The goal is to find a total order consistent with all observations.

2. Build the graph

Create a directed graph where an edge from A to B means A has higher priority than B. For each observation, add edges between consecutive vehicles (or all pairs) to capture the ordering constraints.

3. Detect cycles and find ordering

Use topological sorting (e.g., Kahn's algorithm or DFS) to produce a linear order. If the graph has a cycle, no consistent global ordering exists.

4. Handle edge cases and validate

Consider empty observations, single-vehicle lists, duplicate edges, and disconnected components. Ensure the output is a valid permutation of all vehicles.

Key Points to Mention

Graph representation: nodes as vehicles, directed edges for priority constraints.
Topological sort algorithms: Kahn's (BFS-based) and DFS-based, with time complexity O(V+E).
Cycle detection: if a cycle exists, no valid ordering; can be detected during topological sort.
Transitive closure: adding all pairs from each observation ensures all constraints are captured, but may be redundant.
Handling multiple valid orderings: if the graph is not a total order, any topological sort is acceptable unless additional constraints are given.
Space and time complexity: O(V+E) for building graph and sorting, where V is number of vehicles and E is number of priority relations.

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