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.