Senior Staff Software Engineer, Google Cloud

Google

Let's simulate a coding interview scenario. I'd like you to solve a problem and articulate your thought process as you go. Imagine you're given an array of integers. Your task is to write a function that finds the length of the longest strictly increasing subsequence in that array. A strictly increasing subsequence is a sequence of numbers from the array such that each number is greater than the previous one, and their original order in the array is maintained. For example, in the array [1, 3, 2, 4, 5], one possible increasing subsequence is [1, 2, 4, 5], and the longest increasing subsequence is [1, 2, 4, 5], which has a length of 4. Another possible increasing subsequence is [1, 3, 4, 5] which has length of 4. Your function should return 4 in this case. Another example is [10, 9, 2, 5, 3, 7, 101, 18]. The longest increasing subsequence is [2, 3, 7, 18], which has a length of 4. Your function should return 4. Can you describe your approach and then implement the function? Consider edge cases, like an empty array or an array with only one element. How would your approach handle those? What is the time and space complexity of your solution?

Google

Let's design a cache. Consider the following requirements: Basic Functionality: Implement a cache with put(key, value) and get(key) methods. Eviction Policy: Implement an LRU (Least Recently Used) eviction policy. When the cache is full, the least recently accessed item should be evicted to make space for the new item. Thread Safety: Ensure the cache is thread-safe to handle concurrent access from multiple threads. Generics: The cache should be able to store any type of key and value (using generics). Time Complexity: get and put operations should have an average time complexity of O(1). Example Usage: Cache cache = new Cache(5); // Cache with capacity 5 cache.put(1, one); cache.put(2, two); cache.get(1); // Access key 1, moves it to the most recently used cache.put(3, three); cache.put(4, four); cache.put(5, five); cache.put(6, six); // This will evict key 2 (LRU) System.out.println(cache.get(2)); // Output: null (because it was evicted) Discuss the data structures you would use, the implementation details for each method, and how you would address thread safety.

Google

Describe a time you faced a tough technical problem. What made it so difficult, and how did you approach solving it? What resources did you consult, and what was the final outcome? What did you learn from this experience, and how has it shaped your problem-solving skills since then? For example, perhaps you were tasked with optimizing a slow-running query in a large database. The initial attempts to improve performance, such as adding indexes, didn't yield the desired results. You then had to dive deep into the query execution plan, identify bottlenecks, and rewrite the query using more efficient techniques, like leveraging window functions or temporary tables. You could also describe the challenges faced while integrating a new feature into a legacy system with poorly documented code. You might have had to reverse engineer parts of the system, deal with unexpected dependencies, and carefully test the integration to avoid breaking existing functionality. Elaborate on the specific tools and methodologies you employed during these challenges, such as debuggers, profilers, or version control systems. Also, explain how you collaborated with team members or sought assistance from external resources like online forums or documentation to overcome the obstacles.