Apple has indeed adjusted its hiring strategy in recent years. Many job seekers mistakenly think the interview has become "easier." But our recent experience supporting a candidate in an actual Apple interview proves otherwise. The difficulty hasn't lessened—it’s just changed form. It’s no longer about solving the hardest algorithms, but whether you can explain, structure, and implement solutions that reflect real-world thinking.

This was a technical interview at Apple. The question didn’t look complicated at first glance, but it subtly pressed into the core of engineering thinking.

Now, you need to return a new array of the same length where the elements are the indices of the original elements in a sorted version of the array.
Input: [5, 6, 1, 2, 4]
Output: [3, 4, 0, 1, 2]

Modify your solution to instead find the element or elements that appear most frequently in the array. Return the index or indices of these most frequent elements as if the array were sorted.
Input: [5, 6, 1, 2, 2, 4]
Output: [1, 2]

Our candidate was nearly frozen at the beginning. He understood the question, but was slow to react and couldn’t organize his thoughts clearly. As the interview started, our real-time support team quietly went live on a second device. When we saw him pause, we immediately sent a side-screen prompt: "Start with the example and try tracing it yourself to understand the relationship between sorting and frequency."

The interviewer asked, “Can you walk me through your approach?”

We instantly pushed a message: First, count frequencies, then find the most frequent elements, then compute their index ranges in the sorted array.

The candidate repeated aloud: “I’ll first count the frequencies, then identify the most frequent elements, and determine their positions in the sorted array.” The interviewer nodded: “Alright, how would you implement that?”

We quickly provided the next line of guidance: "Use a dictionary to count frequencies, find the max value, then iterate to find all keys matching that frequency." The candidate nearly quoted us word for word.

Then came another question from the interviewer: “Where would these most frequent elements appear in the sorted array?” This was the core, and we were ready.

We updated the prompt immediately: For each target number, count how many elements are smaller—this gives the starting index in the sorted array. The range follows from that point.

The candidate repeated smoothly: “We can iterate through the array, count how many values are smaller than the target, then construct a continuous index range.”

The interviewer then asked: “Can you write the full function?” We supplied a step-by-step code template with explanatory comments. The candidate simply read and copied while paraphrasing each step:

This was a pre-prepared standard solution. Our goal was to help the candidate articulate each step clearly.

The interviewer followed up: “What’s the time complexity of this code?”

We quickly filled in the answer: Building the dictionary is O(n), finding max is O(n), scanning for each key is O(n), so total is O(n^2), but can be optimized.

The candidate responded accordingly: “Currently it's O(n^2) since we loop through the array for each frequent element, but this could be optimized using sorting or caching.”

The interviewer dug deeper: “What if sorting is allowed—how would you improve it?” We immediately shifted to the sorted-pair solution: construct value-index pairs, sort them, create a mapping, then trace the target’s sorted index.

The candidate recited the thought process and wrote:

The interviewer followed up: “If multiple values tie for highest frequency, can your sorted solution still return correct positions?”

We quickly suggested: track the first appearance of each value in the sorted array, then use frequency to calculate index range. The candidate hesitated slightly, but explained: “We can record the first position each value appears after sorting, and then calculate based on that.”

Then came another angle: “If you were interviewing someone, how would you test this function?”

We prompted: design edge cases—empty array, all identical, multiple max frequency, negative values, already sorted input. The candidate said: “I’d design test cases including an empty array, a single-element array, arrays with all elements the same, and cases where multiple elements tie for highest frequency.”

Final blow from the interviewer: “If this function runs in a backend API processing tens of millions of requests per day, what optimizations would you consider?” We switched to performance mode: use collections.Counter for frequency; process less_count with a sorted pass.

With the prompt, the candidate replied: “I’d use Python’s built-in Counter for faster frequency counts, then build a value-to-index map after sorting to avoid repeated scans.”

The interview lasted nearly 40 minutes. From algorithm to performance, implementation to testing, the interviewer kept probing, and the candidate handled it better than he ever had in practice.

This was because at every question, CSOAHELP had already predicted the next move, structured the thought process, and framed the explanation. The candidate only needed to stay calm and articulate clearly.

You might think Apple interviews have become easier. In reality, they’ve stopped obsessing over brute-force algorithms. They now want engineers who can solve real problems, explain their thinking, and understand system and product context.

CSOAHELP’s real-time interview support isn’t about giving answers. It’s about making sure you answer like an actual professional. You speak—we think. You respond—we cover the gaps.

If you're facing interviews at Apple, Google, Meta, or Stripe, let us be your behind-the-scenes partner. From prep sessions, question strategies, and expression training, to real-time live support during the interview—we’re with you.

You just need to be ready to face the interviewer. We’ll handle the logic, structure, and pace. The next person to pass confidently could be you.

经过csoahelp的面试辅助，候选人获取了良好的面试表现。如果您需要面试辅助或面试代面服务，帮助您进入梦想中的大厂，请随时联系我。

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.