Topics: Breadth-First Search, Depth-First Search, Heap, System Design
Location: Mountain View, CA
Interview date: 2026-01-18
Summary
Round 1: Technical Phone
Question: I was asked a question similar to the Rotten Oranges problem, involving BFS on a matrix to find the shortest distance from each cell to the nearest taxi. There was a follow-up question about designing a system for taxis that randomly go online or offline.
Details
The coding question I received was similar to the Rotten Oranges problem.
The question involved a matrix with several taxis, and I needed to find the shortest distance from each cell to any taxi using BFS.
The follow-up questions were:
Are there alternative ways to solve this BFS problem? I suggested DFS, but noted that BFS is always the optimal solution for finding the shortest distance.
If some taxis randomly go online or offline, how would you design the system? I answered by using DFS for each car and storing the shortest distance from each car to the cell in a heap. If a taxi goes online, a record is added, and if it goes offline, the record is deleted. I later thought that I should have added a dictionary to store the online cars and use lazy deletion when access is needed.
My approach:
Implemented BFS to find the shortest distance.
Used heap to store the shortest distance for each cell.
Key insights:
BFS is optimal for shortest distance problems.
Consider lazy deletion for dynamic system design problems.