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In-Depth Analysis of Recent Apple Interview Questions: A Complete Technical Experience from Clarification to Optimization – interview support – interview proxy

Introduction:

Recently, I had the opportunity to attend an interview at Apple, where I was presented with a series of algorithmic challenges. Throughout the process, I engaged in a detailed back-and-forth with the interviewer, ensuring a clear understanding of each problem before moving into coding and optimization. This article will walk you through the interview experience, focusing on the technical questions asked, the clarifications requested, and the solutions developed. It aims to provide a complete picture of what to expect during a technical interview at Apple.

Problem 1: Best Time to Buy and Sell Stock with Transaction Fee

Problem Description (in English):
You are given an array prices where prices[i] represents the price of a given stock on the ith day, and an integer fee representing a transaction fee. Find the maximum profit you can achieve. You may complete as many transactions as you like, but you need to pay the transaction fee for each transaction. You may not engage in multiple transactions simultaneously (i.e., you must sell the stock before you buy again).

  • Input: prices = [1,3,2,8,4,9], fee = 2
  • Output: 8

Interview Conversation:
As the interviewer presented this problem, I began by asking a clarifying question:

Candidate: “Can the stock prices go down continuously, and how do we handle the case where no transactions are profitable?”

Interviewer: “Yes, the prices can go down, and in that case, you would make no transaction. The solution should return zero profit if no trade is possible.”

After the clarification, I proceeded to explain my approach using dynamic programming.

Problem 2: Task Scheduling with Dependencies

Problem Description (in English):
You are working on a project with n tasks labeled from 0 to n-1. Each task has some dependencies in the form of a directed graph, where dependency[i] = [a, b] means task b must be completed before task a. Return the ordering of tasks you should take to finish the project. If there are multiple valid orders, return any one of them. If there is no valid order, return an empty list.

  • Input: tasks = [0, 1, 2, 3, 4, 5], dependencies = [[1, 0], [2, 1], [3, 2], [4, 3], [5, 4]]
  • Output: [0, 1, 2, 3, 4, 5]

Interview Conversation:
Before diving into the code, I wanted to clarify the task dependencies.

Candidate: “So the task dependencies are like prerequisites, right? If A depends on B, I need to finish B before A?”

Interviewer: “Exactly, it’s a topological sort problem.”

I confirmed my understanding and proceeded with the solution using Kahn’s algorithm for topological sorting. During the implementation, the interviewer asked how I would detect cycles, and I explained the in-degree approach I was using.

Problem 3: Simplifying Parentheses Expressions

Problem Description (in English):
Given a formula consisting of letters and parentheses, simplify the formula by removing parentheses.

  • Input: a-(b+c)
  • Output: a-b-c
  • Input: a-(a-b)
  • Output: b

Interview Conversation:
For this question, I clarified whether the input formula could contain other operators besides subtraction.

Candidate: “Does this formula contain only subtraction, or can there be multiplication or division as well?”

Interviewer: “Only subtraction and addition, but focus on how subtraction behaves when parentheses are removed.”

After that clarification, I implemented a stack-based solution that handled both addition and subtraction while simplifying the expression.

Conclusion:

The interview covered a variety of fundamental algorithmic concepts, from dynamic programming to topological sorting and string manipulation. By thoroughly clarifying each question before proceeding, I was able to ensure that my solutions aligned with the interviewer’s expectations. I was asked follow-up questions about optimization and edge cases, which provided opportunities to demonstrate deeper algorithmic thinking. This interview experience highlighted the importance of communication and understanding before diving into implementation.

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In this Google interview, I demonstrated my understanding of common algorithmic problems and my problem-solving abilities. Each problem presented different challenges, but all could be solved through logical algorithm strategies.

If you need more interview support or interview proxy practice, feel free to contact us. We offer comprehensive interview support services to help you successfully land a job at your dream company.

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