Software Engineer III, Performance, Google Cloud

Google

Given an unsorted array of integers, write a function to sort the array in ascending order using the merge sort algorithm. Explanation of Merge Sort:** Briefly explain the merge sort algorithm, highlighting its divide-and-conquer approach. Implementation:** Provide a step-by-step implementation of the merge sort algorithm. This includes: A mergeSort function that recursively divides the array into smaller subarrays. A merge function that merges two sorted subarrays into a single sorted array. Example:** Input array: [38, 27, 43, 3, 9, 82, 10] Expected output: [3, 9, 10, 27, 38, 43, 82] Efficiency:** Discuss the time and space complexity of merge sort. Why is merge sort considered an efficient sorting algorithm? How does it compare to other sorting algorithms like bubble sort or quicksort in terms of performance (best, average, and worst-case scenarios)? Constraints:** You are not allowed to use built-in sorting functions. The array can contain positive and negative integers. The solution must be implemented in a language of your choice (e.g., Python, Java, C++). Follow-up:** How would you modify the merge sort algorithm to sort the array in descending order? Could you implement an iterative version of merge sort instead of the recursive one? What are the trade-offs?

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.