Senior Security Engineer, Google Distributed Cloud Compliance

Google

Let's explore some string manipulation algorithms. Suppose you are given a string s and you need to reverse the order of words in the string. Each word is separated by a single space, and there are no leading or trailing spaces. For example, if the input string s is the sky is blue, the expected output is blue is sky the. Write a function that takes a string s as input and returns a new string with the words in reversed order. Explain your approach. What is the time and space complexity of your algorithm? Provide example test cases to demonstrate that your function works correctly, including edge cases such as an empty string or a string with only one word. As a follow-up, consider a more complex scenario where the input string s might contain leading or trailing spaces, or multiple spaces between words. How would you modify your algorithm to handle these cases while still producing the correct reversed word order? For instance, given the input hello world , the output should be world hello. Describe the changes needed and analyze the updated time and space complexity.

Google

Let's design a rate limiter for an API. The rate limiter should: Limit the number of requests a user can make to an API within a given time window. Support different rate limits for different users or API endpoints. For example, a free tier user might be limited to 10 requests per minute, while a premium user can make 100 requests per minute. Similarly, some API endpoints might have lower rate limits than others due to resource constraints. Be highly performant to avoid adding significant latency to API requests. Be scalable to handle a large number of users and API requests. Be reliable and prevent accidental overloads that could cause service disruptions. Describe the architecture, algorithms, and data structures you would use to implement such a rate limiter. Consider the following: How would you store the rate limit counters for each user or endpoint? What algorithm would you use to determine whether a request should be allowed or throttled? How would you handle distributed rate limiting across multiple servers? How would you ensure the rate limiter is resilient to failures? As an example, imagine a scenario where a social media platform wants to prevent users from spamming their API with excessive requests to post updates. The platform has millions of users and thousands of API endpoints. Some users pay for premium access with higher request limits. How would you design a robust and efficient rate limiter to handle this scale and these varying requirements?

Google

Where do you see yourself in 5 years?