Count longest subsequence in graph
Last updated: December 11, 2025
Quick Overview
Given a directed graph represented by its adjacency list, write a function to count the length of the longest subsequence of nodes that can be traversed without revisiting any node. The function should take the graph as input and return an integer representing the length of the longest subsequence.
Tesla
December 11, 2025146
8
527 solved
Given a directed graph represented by its adjacency list, write a function to count the length of the longest subsequence of nodes that can be traversed without revisiting any node. The function should take the graph as input and return an integer representing the length of the longest subsequence.
Coding interviews at Tesla focus on problem-solving approach as much as the final solution. The interviewer wants to see you break down the problem, consider edge cases, and optimize iteratively. Communication throughout the process is key.
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
How to Approach This
- Clarify input constraints and edge cases before writing code.
- Walk through your approach verbally and confirm with the interviewer before coding.
- Start with a brute force solution, then optimize. Mention time and space complexity.
- Test your solution with examples, including edge cases like empty input or duplicates.
- Consider common patterns: sliding window, two pointers, hash map, BFS/DFS, dynamic programming.
Possible Follow-up Questions
- How would you parallelize this solution?
- How would you modify your solution to handle streaming input?
- Can you optimize the space complexity of your solution?
- Can you solve this iteratively instead of recursively (or vice versa)?
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Problem Analysis
To solve the problem of counting the length of the longest subsequence in a directed graph, we can utilize Depth-First Search (DFS) along with memoization. The reason DFS is applicable here is that we...
Approach
- Graph Representation: Start by using an adjacency list to represent the directed graph. Each node will point to a list of its direct successors.
- DFS Function: Define a recursive DFS fu...
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