This time it went well. Google VO, the overall form is a combination of Behavioral + Coding.
Difficulty is not particularly high, but the focus is not really on the code, but on the Behavioral Questioning (BQ) -- the answer must be clear and logical, the interviewer will be very important to your communication style and thinking process.
The Coding section is probably of medium difficulty, and can be covered by normal LeetCode brushing. The key is to quickly clear your mind on the spot, and don't forget to add complexity analysis and edge cases after writing.
Next, I will share my real questions and solutions, hoping to give some reference to students who are preparing for Google interviews.
Google Interview Process Review
This VO is divided into two parts, and the overall pace is relatively tight:
Part I: Behavioral (BQ Behavioral side)
The main purpose of this session is to examine the logic of communication and the way of thinking. Interviewers are not waiting for a "standard answer", but to see whether you can make your experience clear in a short period of time and structure your thoughts. For example, they may ask "how to handle disagreements within the team" or "how you respond to unexpected situations", paying more attention to whether you are organized and whether you can reflect and grow, rather than memorizing templates.
Part II: Coding (algorithmic questions)
The technical part is usually two algorithmic questions plus some follow-ups, the difficulty of the questions themselves is not very high, it's more about whether you can quickly understand the meaning of the questions, give reasonable solutions, and further analyze the complexity and optimization space after implementation. Some of the follow-ups will lead you to think about scalability or edge case, and if you can take the initiative to add these points under the premise of clear logic, you will often leave a good impression on the interviewer.
Interview process recollection
This VO was split into two parts: first BQ, then coding.
Part BQ
For the first question, the interviewer asked me:
"How do you face a sudden opportunity to drop what you're doing and work on a new project?"
I paused for a while, thinking about how to balance "opportunity" and "responsibility". My senior reminded me to emphasize on "assessment + communication" instead of directly saying "let go" or "insist". So I replied: I would first quickly assess the value and urgency of the opportunity, and then communicate with my team to see if I could find a solution. If the opportunity is really important, I'll prioritize and ensure that my current work doesn't fall through the cracks while taking on new challenges.
The second question is:
"How do you convince a colleague who is more senior than you but has an older technical program to accept your new program?"
At first, I almost said "prove it with data", but my senior reminded me of "respect and co-creation". So I changed my answer: I would first understand the other person's thinking, recognize the value of his proposal, then compare the data with the experimental results, and invite him to discuss how to combine the new method with the existing experience. This avoids confrontation and makes him feel that he is co-optimizing rather than overthrowing.
Coding section
First question:
"Check whether a given sequence of numbers is a subsequence of a binary tree traversed in middle order."
I started out with the idea of using mid-sequence traversal. I got stuck writing the DFS because I had to check that the sequences would match up while traversing. I almost finished traversing the whole tree first, and then went through the sub-sequences individually, but that would have used more space. I was reminded by my senior on-line that I could "synchronize the matching" by maintaining a pointer during the recursion so that I could advance directly during the traversal. The final logic is: when traversing to a node, if it is equal to the current value of the target sequence, then move the pointer; if the pointer just walks through the whole sequence, then return True. this point is a key breakthrough.
Second question:
"Given an array, modify up to 3 elements to minimize the amplitude of the array."
Ideas I started with sorting and then considered deleting the elements at both ends. At first I was thinking of doing a brute force enumeration of all possible combinations of deletions, which would be too complex. I was reminded by my senior on-line that "it's essentially just deleting 3 elements or less from both ends", so there are at most 4 cases: deleting 3 lefts, deleting 2 lefts and 1 right, deleting 1 left and 2 rights, and deleting 3 rights. For each case, calculate the remaining amplitude and take the minimum value. This reduces the complexity directly to O(n log n) sorting + O(1) judgment. After writing it out, the interviewer was quite satisfied.
Follow-up section
The interviewer pursued the question:
1. What is the time complexity of your solution? Can it be further optimized?
I answered: now it's O(n log n), mainly in the sorting step. If the input is an unordered array, there's not much room for optimization; if the input itself is ordered, it gets down to O(1).
2. How does your algorithm scale if you allow k modifications?
I was a bit stuck, I didn't know how to generalize "k times". My senior reminded me on-line that I could generalize it to "remove up to k elements from both ends", so the problem becomes "find a continuous sub-interval of length n-k in the sorted array that minimizes the amplitude of the interval". This can be done with a sliding window with complexity O(n). After I explained the logic clearly, the interviewer nodded his head in approval.
Summarize feelings
The overall difficulty of this interview is medium, the BQ part is about logic and communication, while the coding part is a typical thought transformation question. I almost fell into brute force a few times in the middle of the interview, but fortunately my senior woke me up in time in the on-line, such as "synchronized matching sequence" and "deletion of elements at both ends of the enumeration", so that I could quickly jump out of the ineffective thinking. In the end, the overall performance is relatively smooth, and also took the praise.
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