The Java Logic Hub
Sudoku Solver Sudoku is a logic puzzle played on a 9 by 9 grid divided into 3 by 3 subgrids. The objective is to fill the grid with numbers 1 to 9 so that each number appears exactly once in every row, column, and subgrid. The primary method used is recursive backtracking. This algorithm visits empty cells and tries numbers from 1 to 9 while checking if the move is valid. If a number leads to a dead end, the algorithm backtracks by clearing the cell and trying the next digit. To improve performance, solvers use heuristics like the Minimum Remaining Value. This strategy prioritizes filling cells with the fewest possible legal options first, which makes solving expert puzzles much faster 1, 2, 3, 4, 16, 28.
Boyer Moore Majority Vote Algorithm This algorithm is designed to find the majority element in an array, which is an element that appears more than N divided by 2 times. It operates in two main phases. In the first phase, the algorithm identifies a potential candidate. It maintains a counter that increases when the same element is encountered and decreases when a different one appears. If the counter hits zero, a new candidate is selected from the current position. In the second phase, the algorithm traverses the array again to verify if the candidate truly appears more than half the time. This method is very efficient as it runs in linear time and uses constant extra space 35, 36, 37, 86.
Kadanes Algorithm Kadane's algorithm is the most efficient way to find the maximum sum of a contiguous subarray. It works by iterating through the array while keeping track of a running sum. The core rule of this algorithm is that if the running sum ever becomes negative, it is immediately reset to zero. This is because a negative sum will only reduce the potential maximum sum of any future subarray. During the iteration, the algorithm constantly updates the maximum sum found so far. This approach allows the problem to be solved in linear time with a single pass through the array 77, 82, 84, 96, 108, 119.
Stock Buy and Sell The stock buy and sell strategy for multiple transactions focuses on achieving the maximum possible profit by capturing every price increase. The logic is simple: if the price of a stock today is higher than it was yesterday, the difference represents a profit that can be added to the total. By summing up all these daily price gaps, you effectively simulate buying at every local minimum and selling at every local maximum. This strategy ensures the highest possible gain across the entire period and can be calculated in a single pass through the price data 123, 124, 126, 127.
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