Sliding Window on graph

Last updated: October 30, 2025

Quick Overview

Given a graph represented as an adjacency list, implement a sliding window technique to find the maximum number of nodes that can be visited within a specified distance from a starting node. The function should return the count of unique nodes reachable within that distance. Input consists of the graph and the starting node, while the output is an integer representing the maximum count of reachable nodes.

Roblox
Coding & Algorithms
Software Engineer
Roblox
October 30, 2025
Software Engineer
Onsite
Coding & Algorithms
Hard

138

14

1,318 solved


Given a graph represented as an adjacency list, implement a sliding window technique to find the maximum number of nodes that can be visited within a specified distance from a starting node. The function should return the count of unique nodes reachable within that distance. Input consists of the graph and the starting node, while the output is an integer representing the maximum count of reachable nodes.

This coding problem is frequently asked during Onsite at Roblox. The interviewer is testing your ability to translate a problem into clean, working code while discussing time and space complexity. Roblox expects candidates to write production-quality code, not just solve the puzzle.

What the Interviewer Expects
  • Quickly identify the optimal approach and its theoretical basis
  • Handle complex algorithm design with multiple interacting components
  • Write concise, elegant code under time pressure
  • Prove correctness of your approach and discuss alternative solutions
  • Optimize beyond the obvious: discuss constant factor improvements
  • Address follow-up variations and explain how the solution generalizes
Key Topics to Cover
Sorting and searching
Hash maps and frequency counting
Binary search and divide and conquer
Tree structures and recursion
How to Approach This
  1. Clarify input constraints and edge cases before writing code.
  2. Walk through your approach verbally and confirm with the interviewer before coding.
  3. Start with a brute force solution, then optimize. Mention time and space complexity.
  4. Test your solution with examples, including edge cases like empty input or duplicates.
  5. Consider common patterns: sliding window, two pointers, hash map, BFS/DFS, dynamic programming.
Possible Follow-up Questions
  • What is the worst-case input for your solution?
  • Can you solve this iteratively instead of recursively (or vice versa)?
  • How would you parallelize this solution?
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Sample Answer
Problem Analysis

This problem involves exploring a graph represented as an adjacency list, where we need to traverse nodes within a specified distance from a starting node. The optimal approach here is using a Breadth...

Approach
  1. Initialize a queue to facilitate BFS, starting with the given starting node and a distance of 0.
  2. Maintain a set to track visited nodes to avoid counting duplicates.
  3. While there are nodes in t...

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