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Compute delivery order via BFS

Last updated: Mar 29, 2026

Quick Overview

This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Compute delivery order via BFS states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  • Medium
  • Akuna Capital
  • Coding & Algorithms
  • Data Scientist

Compute delivery order via BFS

Company: Akuna Capital

Role: Data Scientist

Category: Coding & Algorithms

Difficulty: Medium

Interview Round: Technical Screen

A city road network is an unweighted, undirected graph G(V, E) with a depot node s and D delivery requests located at nodes r1..rD, each with an integer priority p and a unique ID. Produce the service order that sorts deliveries by increasing shortest-hop distance from s, breaking ties by higher priority first, then by smaller ID. Design an algorithm that runs in O(V+E + D log D) by performing a BFS from s to compute distances and then sorting the requests by (distance asc, priority desc, ID asc). Explain correctness, handle unreachable nodes, and provide pseudocode.

Quick Answer: This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Compute delivery order via BFS states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

Solution

# Solution Alignment The prompt asks for an implementation-level answer. The safest way to present it is to define the state, maintain clear invariants, then walk through complexity and tests. ## Problem Restatement A city road network is an unweighted, undirected graph G(V, E) with a depot node s and D delivery requests located at nodes r1..rD, each with an integer priority p and a unique ID. Produce the service order that sorts deliveries by increasing shortest-hop distance from s, breaking ties by higher priority first, then by smaller ID. Design an algorithm that runs in O(V+E + D log D) by performing a BFS from s to compute distances and then sorting the requests by (distance asc, priority desc, ID asc). Explain correctness, handle unreachable nodes, and provide pseudocode. ## Recommended Approach Model each reachable configuration as a graph state and choose the traversal by edge cost: BFS for unweighted shortest paths, Dijkstra for non-negative weighted paths, or topological DP for DAGs. Track visited states at the correct granularity so cycles do not cause repeated work. ## Correctness The implementation should maintain an invariant after each loop or operation that directly matches the problem statement. At termination, that invariant implies the returned value has considered every valid candidate exactly once, or has preserved the required data-structure state after every API call. ## Complexity BFS is O(V + E) time and O(V) space for a standard graph. Expanded-state problems multiply those bounds by the number of state dimensions. ## Edge Cases and Tests Disconnected graph, source equals target, cycles, duplicate edges, unreachable target, and whether the answer counts nodes, edges, moves, or transfers.

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|Home/Coding & Algorithms/Akuna Capital

Compute delivery order via BFS

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Akuna Capital
Aug 10, 2025, 12:00 AM
MediumData ScientistTechnical ScreenCoding & Algorithms
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0

Compute delivery order via BFS

A city road network is an unweighted, undirected graph G(V, E) with a depot node s and D delivery requests located at nodes r1..rD, each with an integer priority p and a unique ID. Produce the service order that sorts deliveries by increasing shortest-hop distance from s, breaking ties by higher priority first, then by smaller ID. Design an algorithm that runs in O(V+E + D log D) by performing a BFS from s to compute distances and then sorting the requests by (distance asc, priority desc, ID asc). Explain correctness, handle unreachable nodes, and provide pseudocode.

Constraints & Assumptions

  • Preserve the scope, facts, inputs, and requested outputs from the prompt above.
  • If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.
  • Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.

Clarifying Questions to Ask

  • Clarify input sizes, value ranges, mutability, return format, and tie-breaking.
  • State the target time and space complexity before coding.
  • Call out edge cases such as empty inputs, duplicates, invalid values, overflow, and boundary sizes.

What a Strong Answer Covers

  • A clear algorithm with the right data structures and enough pseudocode or code-level detail to implement it.
  • A correctness argument that explains why the algorithm covers all required cases.
  • Time and space complexity, plus at least one alternative approach when relevant.
  • Focused tests for normal cases, edge cases, and failure modes.

Follow-up Questions

  • How would the approach change if the input were streaming or too large for memory?
  • What invariants would you assert in production code?
  • Which tests would catch off-by-one, duplicate, or tie-breaking bugs?

Submit Your Answer to Earn 20XP

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