LeetCode 36 Master Valid Sudoku

LeetCode 36: Master Valid Sudoku

LeetCode problem 36 “Valid Sudoku” is a classic example of a backtracking problem. The goal is to determine if a 9 x 9 Sudoku board is valid based on specific rules. This problem requires strong algorithmic skills and a good understanding of the rules of Sudoku. The significance of this problem lies in the fact that Sudoku is a popular game with its own set of rules, and it is a great exercise for strengthening one’s problem-solving skills in programming.

Understanding the LeetCode 36 Problem

What is a Valid Sudoku?

A valid Sudoku is a 9 x 9 grid with 81 cells divided into nine sub-grids, where each row, column, and sub-grid contains unique digits from 1 to 9. Only the filled cells need to be validated according to the following rules:

  • Each row must contain the digits 1–9 without repetition.
  • Each column must contain the digits 1–9 without repetition.

Case Studies: Solving the LeetCode 36 Problem

Case 1: Solving a Sudoku with Fully Filled Cells

To validate a completely filled 9×9 Sudoku board:

  • Iterate through each row and column to check if there are any duplicate digits.
  • Divide the board into nine 3 x 3 sub-grids and check if each sub-grid only contains unique digits.
  • If all rows, columns, and sub-grids contain unique digits, return true as the Sudoku board is valid.

Case 2: Solving a Sudoku with Blank Spaces

To validate a partially filled 9×9 Sudoku board with blank cells:

  • Iterate through each row and column to check if there are any duplicate digits.
  • Divide the board into nine 3 x 3 sub-grids and check if each sub-grid only contains unique digits.
  • For each blank cell, check all possible digits that could fill the cell without violating the Sudoku rules.
  • If all rows, columns, and sub-grids contain unique digits and all blank cells can be filled according to the Sudoku rules, return true as the Sudoku board is valid.

Case 3: Handling Invalid Sudokus

To detect invalid Sudokus and return false:

  • If any row, column, or sub-grid contains duplicate digits, return false.
  • If any blank cell cannot be filled with a digit without violating the Sudoku rules, return false.

Solving the LeetCode 36 Problem

The LeetCode 36 problem is a data structure problem that determines whether a 9 x 9 Sudoku board is valid or not. Solving this problem involves validating every row, column, and 3×3 grid in the Sudoku board.

Step 1: Checking the Rows

To validate every row in the Sudoku board, we need to check if each row contains the digits 1-9 without repetition. We can achieve this by using hash sets to keep track of digits already in a row. If we encounter a repeated digit or a digit greater than 9, then we can return false because the row is invalid. If all rows pass this check, then the Sudoku board is still valid.

Step 2: Checking the Columns

Validating every column in the Sudoku board requires a similar approach to checking the rows. We can iterate through each column and maintain a hash set to keep track of digits already present in a column. If we encounter a repeated digit or a digit greater than 9, then we return false because the column is invalid. If all columns pass this check, then the Sudoku board is still valid.

Step 3: Checking the 3×3 Grids

Validating every 3×3 grid in the Sudoku board is slightly different from checking the rows and columns. We need to iterate through all the 3×3 grids and maintain a hash set to keep track of digits already present in a particular grid. To find the starting index of each grid, we can use modulus to find the row and column indices that correspond to a particular grid. If we encounter a repeated digit or a digit greater than 9 in one of the grids, then we return false because that particular grid is invalid. If all the 3×3 grids pass this check, then the entire Sudoku board is valid.

Optimizing Time and Space Complexity

Time Complexity Analysis

The LeetCode 36 problem requires us to determine if a 9×9 Sudoku board is valid. We can achieve this by checking each row, column, and sub-square to ensure that they do not contain any repeated values from 1 to 9. The time complexity of this algorithm is O(n^2), where n is the size of the board (9×9=81). We iterate through the board once for each check we perform, resulting in a time complexity of O(3n^2) or O(n^2).

To optimize the time complexity of this algorithm, we can use set data structures to keep track of the numbers in each row, column, and sub-square. This will allow us to quickly determine if a value has been repeated, without having to iterate through the entire row or column each time. By using this technique, we can achieve a time complexity of O(n), which is much faster than our original O(n^2) solution.

Space Complexity Analysis

The space complexity of the LeetCode 36 problem depends on the size of the input (9×9 Sudoku board), as well as the space required for our data structures. The largest data structure that we use is the set, which has a space complexity of O(n). Therefore, the space complexity of our algorithm is O(n) as well, since we are only using a single set for each row, column, and sub-square check.

To optimize the space complexity of this algorithm, we can use bit manipulation techniques to represent the numbers in each row, column, and sub-square. By using a single 9-bit integer to represent the numbers from 1 to 9, we can reduce the space required for each set to just 1 integer. This will greatly reduce the overall space complexity of our algorithm, while still allowing us to achieve the same result.

References

LeetCode problem statement for “36. Valid Sudoku”

Wikipedia page on Sudoku

  • Set a timer to create a sense of urgency and help you stay focused
  • Focus on a single row, column, or square to spot patterns and progress more quickly
  • Practice one new technique at a time for five minutes each to build your skillset gradually
  • Get a fast start by locating the numbers that appear most frequently in the grid
  • Look for single candidate values to eliminate possibilities and narrow down your choices
  • Work on scanning techniques to quickly identify patterns and fill in missing values
  • Avoid focusing too long on a single spot by switching it up frequently
Being a web developer, writer, and blogger for five years, Jade has a keen interest in writing about programming, coding, and web development.
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