I sat at my home desk in North America and connected with the TikTok interviewer via video on the HackerRank platform. The problem appeared on the HackerRank interface:

Problem:
Given the root of a binary tree, return the most frequent subtree sum. If there is a tie, return all values with the highest frequency in any order. The subtree sum of a node is defined as the sum of all node values in the subtree rooted at that node (including itself).

In other words, for each node you compute the total of its own value plus all values in its left and right subtrees, track how often each sum occurs, and return the sum(s) that appear most frequently.

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I first confirmed with the interviewer that I could use Python. Compared to C++ and other languages, Python allows faster implementation, fewer lines of code, and played to the strengths of the CSOahelp instructors’ guidance. In these sessions, candidates usually solve two problems in 45 minutes, so speed is critical.

This time I used the CSOahelp interview assistance service. Since I hadn’t practiced algorithm questions in a while, the instructors greatly reduced my prep time. Before the interview, they helped me set up all hardware and software environments. During the live session, my assistant monitored the interview and problem prompts, and provided real-time hint texts on my iPad, which I had discreetly placed out of the camera’s view. Feeling nervous, I also installed an AI-powered eye-contact tool so that glancing at the iPad wouldn’t be detected.

Although I didn’t fully understand the problem at first, several clarification prompts had already appeared in the CSOahelp interface. Following our practice drills, I began by asking these three questions:

1. “Do I need to define the binary tree structure myself?”
2. “Does ‘subtree sum’ mean the sum of all values in both the left subtree and the right subtree plus the node’s own value?”
3. “Can I assume each node’s value is an integer?”

The interviewer replied:

1. “No need—we already provide the TreeNode definition in the environment. Use it directly.”

        
class TreeNode:
    def __init__(self, val=0, left=None, right=None):
    self.val = val
    self.left = left
    self.right = rig


        
    

1. “Exactly. Add the current node’s value to the sums of its left and right subtrees.”
2. “Yes, treat all node values as integers.”

After this polite exchange—about five minutes in—I glanced at my iPad. The assistant had already drafted a full screen of code with bilingual comments. Some Chinese terms felt unfamiliar to me in English, but the assistant also supplied their English equivalents, which I could read aloud.

When the interviewer signaled me to start coding, I transcribed the code line by line. Using Python spared me from worrying about missing semicolons or misplacing parentheses. A simplified version looked like this:

        
from collections import defaultdict
from typing import Optional, List

class TreeNode:
    def __init__(self, val: int = 0, left: 'TreeNode' = None, right: 'TreeNode' = None):
        self.val = val
        self.left = left
        self.right = right

def find_frequent_tree_sum(root: Optional[TreeNode]) -> List[int]:
    # Hash map to count each subtree sum
    count = defaultdict(int)
    
    # Post-order traversal to compute subtree sums
    def dfs(node: Optional[TreeNode]) -> int:
        if node is None:
            return 0
        left_sum = dfs(node.left)
        right_sum = dfs(node.right)
        total = left_sum + right_sum + node.val
        count[total] += 1
        return total

    dfs(root)
    if not count:
        return []
    max_freq = max(count.values())
    return [s for s, freq in count.items() if freq == max_freq]

        
    

It took me about ten minutes to finish. Thanks to the AI eye-contact tool, the interviewer noticed nothing out of the ordinary. After typing, the interviewer asked me to walk through the solution. My assistant prompted me to “read the comments one by one,” so I narrated the logic based on the comments in English. The interviewer seemed pleased.

In the final phase, the interviewer asked if I had any questions. My assistant displayed several suitable ones on the screen and reminded me to select just a few so as not to run out of time. I don’t recall the exact responses.

When I later received the notification that I had passed, I felt deeply grateful. To this day, I still don’t fully understand every nuance of the problem, but thanks to the CSOahelp interview assistance service, I took another step toward landing a role at a major North American tech company. I’ve heard that, though the interviews are difficult, the actual work at junior positions is relatively straightforward—especially with powerful AI tools available. I now eagerly anticipate starting my new career in North America.

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If you’re preparing for algorithm or system design interviews at firms like Point72, Meta, or TikTok but aren’t sure how to break down problems or handle edge cases, add WeChat csvohelp to receive North American interview strategies. We also offer mock interviews, live assistance, and OA writing services to help you secure your next role!

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