Software Engineering Manager, Google Classroom

Google

Given a tree data structure, and a set of nodes within that tree, how do you find all of their common parents? For example, consider a tree where node A is the root, and it has children B and C. Node B has children D and E, and node C has a child F. If the input set of nodes is {D, E, F}, then the common parents would be {B, C, A}. If the input set of nodes is {D, E}, then the common parents would be {B, A}. Design an algorithm to efficiently find these common parents, considering potential optimizations for different tree structures and sizes.

Google

Let's design a rate limiter. This is a crucial component in many systems to prevent abuse and ensure fair usage. Your rate limiter should meet these requirements: Functionality: It should limit the number of requests a user can make within a specific time window. For example, allow a user to make 10 requests per minute. Scalability: The rate limiter needs to handle a large number of users and requests concurrently. Imagine millions of users accessing the system. Accuracy: It should accurately track and enforce the rate limits. A small degree of error is acceptable, but significant deviations are not. Low Latency: The rate limiter must not introduce significant delays in request processing. The overhead should be minimal. Fault Tolerance: The system should continue to function correctly even if some components fail. It should be resilient to outages. Cost-Effectiveness: The solution should be cost-effective in terms of resources used (e.g., memory, CPU, network bandwidth). Consider these scenarios and constraints: Users are identified by a unique ID. The time window is configurable (e.g., seconds, minutes, hours). The rate limit is also configurable per user or group of users. You can use any data structures and algorithms you deem appropriate. Assume you have access to a distributed cache (e.g., Redis, Memcached). Walk me through your design. Discuss different approaches, their trade-offs, and how you would address the requirements. Specifically, consider the following: Data structures for storing request counts. Algorithms for incrementing and checking request counts. Handling concurrency and race conditions. Strategies for distributing the rate limiter across multiple servers. How to handle exceeding the rate limit (e.g., returning an error code). Monitoring and alerting. For example, if a user with ID user123 tries to make 11 requests within a minute when their limit is 10, the rate limiter should reject the 11th request. How would your system achieve this efficiently and reliably at scale?

Google

Tell me about a time you had to work with a signed contract. Describe the situation, your role, and the outcome. What were the key clauses or provisions that were most relevant to the situation? What challenges, if any, did you face in interpreting or adhering to the contract terms? How did you ensure that your actions were in compliance with the contract, and what steps did you take to mitigate potential risks or disputes? For example, consider a scenario where you were managing a project with a vendor, and the contract outlined specific deliverables, timelines, and payment terms. A conflict arose when the vendor failed to meet a critical deadline, potentially impacting the project's overall timeline and budget. How did you leverage the contract to address the issue, protect your company's interests, and find a resolution that was fair to both parties? Or, imagine you were involved in a negotiation where the other party wanted to change certain terms after the contract was signed. How did you handle the situation, ensuring that any modifications were properly documented and agreed upon by all parties involved? What did you learn from this experience, and how has it influenced your approach to working with contracts in subsequent projects or situations?