"It's not that the questions are hard, it's that follow-up doesn't give you a break."
This year's fall recruiting Apple Newcomer posts are really getting harder with the naked eye. Our cadet's VO experience was typical:
The coding itself is solid, but there are so many follow-ups that you could have a small workshop on it.
Overall, though, the pacing was solid, the delivery was smooth, the logic was clean, and the interviewer was very buy-in throughout.
Here's a complete recap of the round's experience for you, following the real process.
Background of trainees
- Master in CS, American University
- Internship in backend + data cleansing related
- Volume of questions 250+
- Familiarity with double pointers, binary search, sliding window
- English expression is not bad, just on the fast side, we did a couple of tempo drills ahead of time
- VO coaching by Programhelp for this round (structured narrative + follow-up preview)
This round of questions eats up a lot of basic skills + thought structure, which just happens to be his strong suit.
Opening experience: American relaxation, but watching you from the shadows
The interviewer is a typical American guy, with a bright voice and a few pleasantries right off the bat. But here's the thing about Apple VOs:
Even if the atmosphere is relaxed, he's still judging whether your delivery is clear, organized, and on-topic.
The opening five minutes were spent talking about all of this:
- What modules did the internship
- The trickiest bug I've ever encountered
- Why you left your last company
- What's the main thing you've been working on lately?
- Which Apple teams are interested?
The trainees answered naturally, without piling up keywords or signs of memorization.
Lao listens quite attentively, then laughs a little:
"Alright, let's get to the coding part."
It's official.
Coding: Squares of a Sorted Array
Title Content:
Given a sorted integer array, return a new array of the squares of each number, sorted in non-decreasing order.
The trainee first verbally walked through the ideas (very critical):
- Original array is sorted
- Possibly larger after squaring the negative area
- Shrink to the center with the left and right double pointers
- Whoever squares the larger number starts at the end of the result.
"Makes sense."
The trainee begins to write code.
def sortedSquares(nums).
left, right = 0, len(nums) - 1
res = [0] * len(nums)
idx = len(nums) - 1
while left abs(nums[right]).
res[idx] = nums[left] * nums[left]
left += 1
else: res[idx] = nums[left] * nums[right].
res[idx] = nums[right] * nums[right]
res[idx] = nums[right] * nums[right]
right -= 1
return res
I also volunteered to test two cases after writing it:[-4,-1,0,3,10] → [0,1,9,16,100][-7,-3,2,3,11] → [4,9,9,49,121]
The interviewer nods, "Good. now let's explore some variations."
The result is a straight-forward, Apple-inspired follow-up, with three consecutive follow-up questions.
Follow-up Full process (all really asked)
Follow-up 1: Can we do O(1) Space? arrays allow modification
The trainee gives the program on the spot:
- Finding the positive and negative index
- Decreasing absolute value of the left negative area
- The right non-negative region is increasing
- With the double pointer merge
- Because it's in-place, you need to use insertion + local shift
Then the in-place version is knocked out on site.
The interviewer was very pleased, especially as the trainee had clearly stated:
- in-place adds complexity
- Decreased code readability
- But the space meets the requirements
Very plus.
Follow-up 2: Lots of zeros in an array, can it be optimized?
The points given by the trainees were spot on:
- Count the number of zeros first.
- zero squared is still zero, just batch fill the front part
- The remaining positive and negative areas are merged.
- More stable time, no need to compare zero side
The interviewer nodded again, "Good observation."
Follow-up 3: Can we do O(n) if the inputs are not sorted?
The logic of the trainee's response was very standard:
- If there is no value range restriction:
→ No, optimality still requires ordering O(n log n) - If the range is limited and the integers are not large:
→ can do O(n) with counting array - Decide if you can optimize based on domain
The presentation is structured without being wordy.
Overall VO performance: stable, fast, clear and logical
Throughout the round, the rhythm was a "solid" one:
- First the idea and then the code.
- follow up Structured answers to each question
- Code is easy to read, not showy
- Active complementary complexity and trade-off
- No haste, no flutter, no nonsense
The interviewer is "persuaded" throughout.
An evaluation was also given at the end:
"I like how you articulate your thoughts."
Overall, they are of the steady-over type.
How Programhelp VO Assist Works
The biggest difficulty with Apple's coding VOs isn't the questions at all:
- follow-up High density
- fast-paced
- Requires structured expression
- You can't panic, you can't answer randomly, you can't talk too much.
Programhelp in VO assist On can help you:
- Real-time voice alerts (clarify / edge case / trade-off)
- Simulate Apple's high-frequency follow-up so you can step over the pitfalls ahead of time
- Helps you train your "structured response rhythm".
- Adjust the speed of speech and sentence patterns to sound more professional
- The coding site prompts for clearer naming and more concise comments.
So even though the number of follow-ups in this round was exaggerated, the trainees were still steady throughout.
