In Google’s technical interviews, candidates are expected to showcase their algorithmic problem-solving skills while clearly articulating their thought processes and reasoning. This blog shares a real-life Google interview question, highlighting how csoahelp’s guidance empowered the candidate to perform exceptionally well under pressure.
Original Interview Question
Below is the exact question from the Google interview:
There is a chess contest between N players. Each chess player has a distinct rank (positive integer number from 1 to N).
Assume that in a chess game between two players, the higher-ranked player always wins. The rank remains constant during the contest. Best player would have rank 1 and worst player would have rank N. Rank 1 > Rank 2 > ... > Rank N.
Unfortunately, we don't know the player ranks. But we know the outcome of M games in the following format:
Player #X won Player #Y.Given the results of M games above, are there any players whose rank can be precisely determined? If so, return the player numbers and ranks of such players.
Example:
N=5, M=5
Player #4 won #3
Player #4 won #2
Player #3 won #2
Player #1 won #2
Player #2 won #5
Answer:
The rank of 2 players can be determined precisely:
- Player #2 (rank is 4): they lost to players #1, #3, #4 and won against player #5.
- Player #5 (rank is 5): they lost to player #2, and since player #2 already lost to #1, #3, and #4, their rank is definitive.
Reconstructed Interview Process
1. Clarification Stage
At the start of the interview, the candidate, guided by csoahelp, asked critical clarification questions to confirm the requirements:
Candidate: "Can I assume that all the game results provided are valid? For example, there won't be contradictory outcomes, like one player simultaneously beating and losing to another?"
Interviewer: "Yes, you can assume the data is valid, and there are no circular win/loss relationships."
Candidate: "Would it be acceptable to use a game graph and apply topological sorting to help determine the rankings?"
Interviewer: "That sounds like a valid approach. Please proceed with your explanation."
In this stage, csoahelp’s preparation proved instrumental. The coaches trained the candidate with templates for common clarification questions, helping them quickly zero in on the key details and gain the interviewer’s approval.
2. Explaining the Approach
With a clear understanding of the problem, the candidate began describing their approach:
Candidate: "I plan to model the game results as a directed graph, where players are the nodes, and a win relationship is represented as a directed edge. By analyzing each node’s in-degree and out-degree, we can determine whether a player’s rank is definitive."
Interviewer: "How exactly would you use the in-degree and out-degree to determine rankings?"
Candidate: "If a player’s in-degree is solely from players with clearly higher rankings and their out-degree points only to players with lower rankings, then their rank can be determined."
At this stage, csoahelp’s tailored coaching had prepared the candidate for similar scenarios. Through extensive mock interviews, the candidate learned how to clearly explain graph-based solutions, boosting their confidence and clarity during the real interview.
3. Handling Follow-Up Questions
As the implementation discussion progressed, the interviewer probed further to assess the candidate’s depth of understanding:
Interviewer: "If the number of matches isn’t sufficient to cover all relationships between players, how would your algorithm handle this?"
Candidate: "In such cases, I would only return the ranks of players that can be fully determined based on the available data. Specifically, I would start from nodes with zero in-degree and use BFS or DFS to update reachable nodes' rankings incrementally."
Interviewer: "How would your algorithm handle multiple strongly connected components in the graph?"
Candidate: "That’s a great question. After constructing the directed graph, I would run either Tarjan’s algorithm or Kosaraju’s algorithm to identify strongly connected components. If a strongly connected component consists of nodes that cannot be further separated in terms of ranking, their ranks cannot be precisely determined."
This part of the interview highlighted the candidate’s ability to think critically and adapt their solution dynamically. These problem-solving strategies were honed during csoahelp’s training, where the candidate practiced responding to unexpected questions.
4. Time and Space Complexity Analysis
After explaining the solution, the candidate summarized the algorithm’s time and space complexity:
Candidate: "Building the graph has a time complexity of O(M), where M is the number of match results. Determining the rankings involves graph traversal, which has a complexity of O(N + M). Therefore, the total time complexity is O(N + M), and the space complexity is O(N + M) due to graph storage requirements."
Interviewer: "Good. Your summary covers all the important points."
csoahelp’s coaching emphasized concise and accurate complexity analysis. Through repeated practice, the candidate was well-prepared to articulate these details effectively during the interview.
5. Behavioral Questions
In the final stage, the interviewer assessed the candidate’s behavioral skills:
Interviewer: "Can you describe a time when you worked on solving a complex problem? How did you approach it?"
Candidate: "During a university project, I worked on optimizing a pathfinding algorithm for a large dataset. The dataset size caused significant performance issues. I led the team in redesigning the data structures and introducing heuristic-based search strategies, which reduced processing time by 70%. This experience taught me the importance of pinpointing key bottlenecks and systematically resolving them."
csoahelp’s expert coaches worked closely with the candidate to refine and optimize their answers to behavioral questions, ensuring they presented their experiences in a compelling and structured manner.
Conclusion
This interview case highlights the importance of clear problem clarification, thoughtful solution design, detailed complexity analysis, and effective behavioral responses. The candidate’s success wouldn’t have been possible without csoahelp’s comprehensive guidance. From mock interviews to personalized coaching, csoahelp equipped the candidate with the tools to excel in every stage of the process.
If you’re preparing for a technical interview and looking for expert assistance, csoahelp is here to help you achieve your career goals. Let’s work together to make your dream job a reality!
经过csoahelp的面试辅助，候选人获取了良好的面试表现。如果您需要面试辅助或面试代面服务，帮助您进入梦想中的大厂，请随时联系我。
If you need more interview support or interview proxy practice, feel free to contact us. We offer comprehensive interview support services to help you successfully land a job at your dream company.
