How I passed Meta onsite

Interview Questions: Pow(x, n) from

Objective: Based on my experience, it is not necessary to perfectly solve every problem to pass a Meta interview. I did not complete every question, but I still passed. Here are some tips I found helpful during my Meta coding interview.

Show Your Thought Process: Instead of just writing code, I demonstrated my problem-solving approach. For example, one problem was Pow(x, n).

The interviewer stated that we needed to implement Pow(x, n) where x and n are integers. Here's my approach:

Ask Clarifying Questions: I asked clarifying questions to ensure I understood the requirements. For example:

Question: Will we need to handle floating-point numbers? (I know that 2^1.23 can be challenging.) Interviewer Reply: Let's assume x and n are positive and negative integers.

Initial Thoughts: My initial thoughts included:

• a^(b/2) * a^(b/2) = a^b, and
• a^b * a = a^(b+1)

I explained this recursive relationship and suggested a recursive solution, initially ignoring negative values of b.

I ensured the interviewer understood my approach before beginning to code.

Initial Solution: My initial recursive solution was: def pow(x, n): if n == 0: return 1 if n % 2 == 0: return pow(x, n//2) * pow(x, n//2) else: return pow(x, n//2) * pow(x, n//2) * x

Iterative Solution and Optimization: I hadn't prepared optimally, so I didn't initially know the best solution. The interviewer suggested that the implementation could be similar to a for loop (O(n)).

I then considered adding a cache to avoid repeated computations: cache = {} def pow(x, n, cache): if (x, n) in cache: return cache[(x, n)] if n == 0: return 1 if n % 2 == 0: res = pow(x, n//2, cache) * pow(x, n//2, cache) cache[(x, n)] = res return res else: res = pow(x, n//2, cache) * pow(x, n//2, cache) * x cache[(x, n)] = res return res

I noted that Python dictionaries are passed by reference, allowing efficient cache retrieval. However, this was still not optimal, and the interviewer provided further guidance. I then arrived at the optimal recursive solution after receiving hints.

We discussed why the initial solutions were not optimal (recursive stack overflow, memory usage).

Time and Space Complexity: I analyzed the time and space complexity of my solutions.

Testing: We tested the solution with edge cases.

Conclusion: I had approximately 15 minutes remaining for the second question, so I didn't have time to fully complete everything. However, I still passed. The interviewers seemed to focus on my overall approach and problem-solving skills rather than perfect code execution. Don't rush; thorough discussion is important.