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Number of People That Can Be Seen in a Grid

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Linda Zhou edited this page Apr 5, 2023 · 8 revisions

Problem Highlights

1: U-nderstand

Understand what the interviewer is asking for by using test cases and questions about the problem.

  • Established a set (2-3) of test cases to verify their own solution later.
  • Established a set (1-2) of edge cases to verify their solution handles complexities.
  • Have fully understood the problem and have no clarifying questions.
  • Have you verified any Time/Space Constraints for this problem?
Example 1
Input: heights = [[3,1,4,2,5]]
Output: [[2,1,2,1,0]]
Explanation:
- The person at (0, 0) can see the people at (0, 1) and (0, 2).
  Note that he cannot see the person at (0, 4) because the person at (0, 2) is taller than him.
- The person at (0, 1) can see the person at (0, 2).
- The person at (0, 2) can see the people at (0, 3) and (0, 4).
- The person at (0, 3) can see the person at (0, 4).
- The person at (0, 4) cannot see anybody.


Example 2
Input: heights = [[5,1],[3,1],[4,1]]
Output: [[3,1],[2,1],[1,0]]
Explanation:
- The person at (0, 0) can see the people at (0, 1), (1, 0) and (2, 0).
- The person at (0, 1) can see the person at (1, 1).
- The person at (1, 0) can see the people at (1, 1) and (2, 0).
- The person at (1, 1) can see the person at (2, 1).
- The person at (2, 0) can see the person at (2, 1).
- The person at (2, 1) cannot see anybody.

2: M-atch

Match what this problem looks like to known categories of problems, e.g. Linked List or Dynamic Programming, and strategies or patterns in those categories.

  • Stack: What could we push onto a stack to make this problem easier? Stacks don’t allow us to keep track of data based on keys.
  • Queue: Queues fall into the same category as Stacks, do we need to maintain any sense of ordering to solve this problem?
  • HashMap: HashMaps allow us to store data for quick access. What could we store in a HashMap to make this problem easier?
  • Heap: Do we need some sort of ordering to our data that a Heap could provide?

3: P-lan

Plan the solution with appropriate visualizations and pseudocode.



⚠️ Common Mistakes


    

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4: I-mplement




Implement the code to solve the algorithm.








5: R-eview




Review the code by running specific example(s) and recording values (watchlist) of your code's variables along the way.




    

  • Trace through your code with an input to check for the expected output
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  • Catch possible edge cases and off-by-one errors
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6: E-valuate




Evaluate the performance of your algorithm and state any strong/weak or future potential work.




    

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Time Complexity:
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Space Complexity:
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