![]() If we’re placing the number 4 at row 2, column 5, we need to check the Sudoku property for row 2, for column 5, and for the 3x3 box at “big row” 0, “big column” 1. Of course, we don’t need to check all rows, columns and boxes, but just those for the cell we’re filling. Of course, this is an imperative style, “algorithmic” approach - we’ll build up a recursive solution in Scala for Sudoku shortly, but first, we need to be able to validate whether a value we’re placing in an empty cell is “correct”, i.e. If it is not solvable, put the number you just removed back and either try. Check if the current puzzle is solvable using a Sudoku solving algorithm. move to the next cell to the right, try out all possible solutions from there A different approach to generating Sudokus is to fill the entire grid first with a valid and completed Sudoku puzzle, and then (pseudocode following): Remove a number.check if it satisfies the Sudoku property.if there’s a zero, we’ll try all numbers from 1-9:.(Source Wikipedia) Generator: Generates random Sudoku Grid s of various complexity. The objective is to fill a 9×9 grid with digits so that each column, each row, and each of the nine 3×3 sub-grids that compose the grid (also called 'boxes') contains all of the digits from 1 to 9. check if there is a non-zero value there if it is, that’s part of the original puzzle Sudoku is a logic-based, combinatorial number-placement puzzle.The way we’re going to build up our solution will be: We did something similar in the N-Queens problem. The most important aspect of a constraint satisfaction problem is how to maintain the constraints as we’re building the solution. Writing a Sudoku Validation Function in Scala That’s more like it - we can now identify things in the Sudoku matrix easily. ![]()
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