In technical interviews at top companies like TikTok, Google, and Meta, having technical skills alone is not enough. More importantly, candidates must be able to think quickly under pressure, communicate solutions clearly, and maintain composure when faced with follow-up questions from the interviewer. Today, we will take you through a real TikTok technical interview, showing how a candidate, with the help of CSOAHELP remote interview assistance, managed to successfully complete the challenge despite limited experience. By using real-time assistance with complete answers and code prompts, the candidate was able to pass the interview smoothly.

At the start of the interview, the candidate faced technical issues with audio, making communication difficult. After some adjustments, they confirmed that the audio and screen sharing were working properly. The interviewer began with a simple request: "Please introduce yourself."

The candidate was not particularly confident in speaking, but CSOAHELP's remote assistance team had prepared a full introduction script in advance. The candidate simply followed the script:
"Hello, I am a software engineer with five years of development experience, mainly in backend engineering. I am currently working at a well-known tech company, focusing on optimizing payment systems and transaction data flow. My primary tech stack includes Golang, Kafka, and distributed databases. Previously, I had experience in frontend development using React and TypeScript."

The interviewer followed up: "What has been the most challenging project you worked on recently?" The candidate was not entirely sure how to describe their project in detail, but CSOAHELP provided a complete, structured response for them to follow:
"Recently, I worked on a critical project involving the migration of a promotional pricing system. The main challenges were ensuring data consistency, avoiding conflicts with parallel migrations, and addressing race conditions in the legacy system. To guarantee data consistency, I utilized Kafka for message queue processing and optimized database transaction mechanisms to prevent data conflicts."

The interviewer pressed further: "What was your specific contribution to this project?" The candidate, initially unsure, relied on CSOAHELP’s structured response:
"I was responsible for refactoring the pricing rule calculation module, optimizing the data storage structure, and implementing a Redis-based caching mechanism to improve query efficiency. Additionally, I developed a data consistency verification tool to ensure correctness after migration."

This well-organized and professional response left a positive impression on the interviewer regarding the candidate's engineering abilities.

The interview moved to the technical portion, where the interviewer presented a topological sorting problem, asking the candidate to determine the correct order of tasks and extend the solution to generate all possible valid orders.

Problem Statement: Given a set of prerequisite relationships between tasks, determine all possible valid execution orders.

Example Input:

Prerequisites:  
1 → 0  
7 → 0  
2 → 0  
3 → 1  

Example Output:

7 0 2 3  
7 0 3 2  

The candidate was not very familiar with topological sorting, but CSOAHELP's remote assistance team immediately provided a complete code template, allowing them to follow the guidance step by step while coding.

from collections import deque

def find_all_task_orders(tasks, prerequisites):
    adj_list = {i: [] for i in range(tasks)}
    in_degree = {i: 0 for i in range(tasks)}

    for pre, task in prerequisites:
        adj_list[pre].append(task)
        in_degree[task] += 1

    def backtrack(path, sources):
        if len(path) == tasks:
            result.append(list(path))
            return
        
        for node in list(sources):
            next_sources = sources - {node}
            path.append(node)

            for neighbor in adj_list[node]:
                in_degree[neighbor] -= 1
                if in_degree[neighbor] == 0:
                    next_sources.add(neighbor)

            backtrack(path, next_sources)

            for neighbor in adj_list[node]:
                in_degree[neighbor] += 1

            path.pop()

    result = []
    sources = {node for node in in_degree if in_degree[node] == 0}
    backtrack([], sources)

    return result

prerequisites = [(1, 0), (7, 0), (2, 0), (3, 1)]
tasks = 4
print(find_all_task_orders(tasks, prerequisites))

During the interview, the candidate typed in the code while simultaneously explaining the algorithm using CSOAHELP’s detailed breakdown. They described how to build an adjacency list and in-degree dictionary to store task dependencies, utilize backtracking to explore all possible execution sequences, and ensure that at each step, they only select tasks with no remaining dependencies.

Once the code was submitted, the interviewer increased the difficulty by asking the candidate to identify potential edge cases and optimize the algorithm for larger input sizes. The candidate once again relied on CSOAHELP’s guidance to provide the following response:
"Possible edge cases include an empty task list (return an empty list), circular dependencies (detect cycles in the DAG), and single-task scenarios (return the task directly)."

For optimization, CSOAHELP’s remote assistance provided a strategic explanation:
"The current algorithm has a time complexity of O(V!), which works well for small-scale inputs. If the number of tasks increases significantly, we could use dynamic programming to optimize state storage or implement a topological sorting approach combined with memoized recursion to reduce redundant computations."

These well-structured answers demonstrated the candidate’s comprehensive problem-solving skills, earning approval from the interviewer.

In this TikTok interview, the candidate initially faced several challenges: unfamiliarity with topological sorting, the risk of getting stuck during coding, difficulty responding to follow-up questions in depth, and a lack of well-thought-out considerations for edge cases and optimizations. However, CSOAHELP’s remote assistance provided a complete introduction script, real-time response suggestions, structured coding guidance, debugging strategies, and edge-case analysis. By simply following the provided answers and writing code accordingly, the candidate was able to showcase a much higher level of performance than they originally would have.

CSOAHELP remote interview assistance ensures you never get stuck at any stage by providing complete answer suggestions. With extensive coverage of high-frequency interview topics, personalized 1-on-1 mock interviews to help you refine your responses, and training in system design and code optimization, you can improve your overall interview performance. If you are preparing for technical interviews at TikTok, Google, Meta, Amazon, or other top-tier companies, don’t go in unprepared. CSOAHELP remote interview assistance gives you professional real-time support, significantly increasing your chances of passing the interview!

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.