iOS Software Engineer - AppleTV App

Apple

Let's explore dynamic programming with a classic problem: the knapsack problem. Imagine you have a knapsack with a limited weight capacity, and a collection of items, each with its own weight and value. Your goal is to select the items to put into the knapsack to maximize the total value, without exceeding the weight capacity. Specifically: Problem Statement: You are given a knapsack with a maximum weight capacity W. You are also given n items. Each item i has a weight wi and a value vi. Determine the maximum total value of items that can be placed in the knapsack without exceeding its weight capacity. Example: Knapsack capacity W = 10 Items: Item 1: weight = 6, value = 30 Item 2: weight = 3, value = 14 Item 3: weight = 4, value = 16 Item 4: weight = 2, value = 9 What is the maximum value you can obtain by putting items into the knapsack, and which items should you choose? Explain how you would approach this problem using dynamic programming. Be sure to define the subproblems, the recurrence relation, and the base cases. Also, discuss the time and space complexity of your dynamic programming solution.

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Let's delve into the fascinating world of computer systems. I'd like you to design a simplified operating system. Assume you're building this OS for a resource-constrained embedded system, like a smart thermostat or a simple microcontroller-based device. Your design should address the following key aspects: Memory Management: Describe your approach to memory allocation and deallocation. How would you prevent memory leaks and fragmentation in this environment? Would you use static allocation, dynamic allocation, or a combination of both? Explain your reasoning, giving specific examples of how your chosen methods would work in practice. Process/Task Scheduling: How would you schedule tasks to run on the processor? Would you opt for a preemptive or non-preemptive scheduler? What scheduling algorithm (e.g., Round Robin, Priority-based) would you use, and why? Consider the trade-offs between responsiveness, fairness, and overhead. Imagine you have three tasks: Task A (high priority, short bursts), Task B (medium priority, longer computation), and Task C (low priority, background task). How would your scheduler handle these tasks? Interrupt Handling: Explain how your OS would handle interrupts from hardware devices (e.g., a temperature sensor, a button press). How would you ensure that interrupt handlers are efficient and don't disrupt the normal operation of the system? Describe the steps involved in processing an interrupt, from the moment it occurs to the point where the interrupted task resumes execution. File System (Optional): If your embedded system requires persistent storage, outline a simple file system design. How would you organize files and directories? What data structures would you use to track file metadata (e.g., name, size, location)? How would you handle file creation, deletion, and reading/writing operations? Assume the storage medium is a small flash memory chip with limited write cycles. Inter-Process Communication (IPC): How would different tasks or processes communicate with each other within your OS? Would you use message queues, shared memory, or another mechanism? Explain the advantages and disadvantages of your chosen approach. For example, consider a scenario where one task needs to send sensor data to another task for processing. How would you implement this communication? Remember to justify your design choices based on the constraints of the embedded system, such as limited memory, processing power, and energy consumption. Aim for simplicity, efficiency, and reliability in your design. Your explanation should demonstrate a solid understanding of operating system principles and their practical application in a real-world scenario.

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