Technical Sourcing Recruiter, Worldwide Amazon Stores

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What are the time complexities of different sorting algorithms, such as quicksort and mergesort? Explain the best, average, and worst-case scenarios for each, and provide examples of when you might choose one algorithm over another. Additionally, discuss the space complexity of each algorithm.

Amazon

Let's design a turnstile. A turnstile is a type of gate which allows one person to pass at a time. Consider a turnstile at a subway station. There are two panels that rotate to allow a single person passage. The turnstile has two states, Locked and Unlocked, and the customer can either Push the turnstile or Insert a token/card. Here is the state transition table: | Event | Current State | Action | Next State | | :----- | :------------ | :------------- | :--------- | | Push | Locked | | Locked | | Token | Locked | Unlock | Unlocked | | Push | Unlocked | Pass through | Locked | | Token | Unlocked | (discarded) | Unlocked | Requirements: Model the state and behavior of a simple turnstile. Implement two methods: insert_token() push() Consider edge cases and error handling. What happens if someone tries to push without inserting a token? What happens if the system malfunctions? Example: turnstile = Turnstile() print(turnstile.state) # Output: Locked turnstile.push() print(turnstile.state) # Output: Locked turnstile.insert_token() print(turnstile.state) # Output: Unlocked turnstile.push() print(turnstile.state) # Output: Locked How would you approach this design and implementation, keeping in mind scalability, maintainability, and potential future extensions such as different types of tokens or remote unlocking?

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Tell me about a time you exemplified one of Amazon's leadership principles. For example, consider the 'Customer Obsession' principle. Can you describe a situation where you went above and beyond to meet a customer's needs, even when it was challenging or required you to think outside the box? What specific actions did you take, and what was the outcome? Alternatively, let's explore the 'Bias for Action' principle. Share an instance where you had to make a quick decision with limited information. What was the situation, what factors did you consider, and how did you mitigate the risks associated with acting swiftly? Or perhaps you can elaborate on a time you demonstrated 'Ownership.' Describe a project or task where you took full responsibility for the outcome, even when things didn't go as planned. How did you handle the setbacks, and what did you learn from the experience? Another good principle to discuss could be 'Invent and Simplify.' Tell me about a time you created an innovative solution to a complex problem, while keeping it simple and easy to use. What was the problem, what was your solution, and how did you ensure its simplicity? Finally, tell me about a time where you had to 'Learn and Be Curious'.