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Let me evaluate each solution one by one:

Problem 1.sql:

  1. Correctness: The solution correctly calculates the dense rank of scores, which would handle ties appropriately.
  2. Time Complexity: O(n log n) due to the sorting operation for ranking.
  3. Space Complexity: O(n) for storing the result set.
  4. Code Quality: Simple and clean, follows best practices.
  5. Efficiency: No obvious improvements needed.

Problem 2.sql:

  1. Correctness: Correctly swaps adjacent seats and handles the edge case of odd number of seats.
  2. Time Complexity: O(n) for scanning the table and O(n log n) for sorting.
  3. Space Complexity: O(n) for the result set.
  4. Code Quality: Well-structured with clear CASE logic.
  5. Efficiency: Could potentially use a window function approach, but current solution is fine.

Problem 3.sql:

  1. Correctness: Correctly identifies root, leaf, and inner nodes in a tree structure.
  2. Time Complexity: O(n^2) due to the subquery in the CASE statement.
  3. Space Complexity: O(n) for the result set.
  4. Code Quality: Clear logic, though the subquery could be extracted for better readability.
  5. Efficiency: The subquery is executed for each row, which could be optimized with a JOIN.

Problem 4.sql:

  1. Correctness: Correctly finds the top 3 salaries in each department.
  2. Time Complexity: O(n log n) for the ranking operation.
  3. Space Complexity: O(n) for the CTEs and result set.
  4. Code Quality: Well-structured with clear CTEs, though the JOIN could be done in the first CTE.
  5. Efficiency: Could potentially combine the CTEs into a single query.

General strengths:

  • Consistent formatting and style
  • Appropriate use of SQL features (window functions, CTEs, CASE statements)
  • Handles edge cases well

Areas for improvement:

  • Problem 3 could be optimized to avoid the O(n^2) complexity
  • Some queries could be slightly more concise
  • Consider adding comments for complex logic

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