Algorithmic Problems and Interview Questions in Java

Introduction 1 lecture 01:36 Introduction Introduction 1 lecture 01:36 Introduction Introduction Introduction Introduction Introduction Recursion 9 lectures 52:16 Recursion introduction Adding numbers: iteration vs recursion House building problem Factorial function Euclidean algorithm - greatest common divisor Linear and binary search introduction Linear and binary search implementation Towers of Hanoi problem introduction Tower of Hanoi problem implementation Recursion 9 lectures 52:16 Recursion introduction Adding numbers: iteration vs recursion House building problem Factorial function Euclidean algorithm - greatest common divisor Linear and binary search introduction Linear and binary search implementation Towers of Hanoi problem introduction Tower of Hanoi problem implementation Recursion introduction Recursion introduction Recursion introduction Recursion introduction Adding numbers: iteration vs recursion Adding numbers: iteration vs recursion Adding numbers: iteration vs recursion Adding numbers: iteration vs recursion House building problem House building problem House building problem House building problem Factorial function Factorial function Factorial function Factorial function Euclidean algorithm - greatest common divisor Euclidean algorithm - greatest common divisor Euclidean algorithm - greatest common divisor Euclidean algorithm - greatest common divisor Linear and binary search introduction Linear and binary search introduction Linear and binary search introduction Linear and binary search introduction Linear and binary search implementation Linear and binary search implementation Linear and binary search implementation Linear and binary search implementation Towers of Hanoi problem introduction Towers of Hanoi problem introduction Towers of Hanoi problem introduction Towers of Hanoi problem introduction Tower of Hanoi problem implementation Tower of Hanoi problem implementation Tower of Hanoi problem implementation Tower of Hanoi problem implementation Selection Algorithms 6 lectures 42:21 Selection algorithms introduction Quickselect introduction - Hoare algorithm Quickselect simulation Quickselect implementation Advanced selection - median of medians, introselect Online selection - the secretary problem Selection Algorithms 6 lectures 42:21 Selection algorithms introduction Quickselect introduction - Hoare algorithm Quickselect simulation Quickselect implementation Advanced selection - median of medians, introselect Online selection - the secretary problem Selection algorithms introduction Selection algorithms introduction Selection algorithms introduction Selection algorithms introduction Quickselect introduction - Hoare algorithm Quickselect introduction - Hoare algorithm Quickselect introduction - Hoare algorithm Quickselect introduction - Hoare algorithm Quickselect simulation Quickselect simulation Quickselect simulation Quickselect simulation Quickselect implementation Quickselect implementation Quickselect implementation Quickselect implementation Advanced selection - median of medians, introselect Advanced selection - median of medians, introselect Advanced selection - median of medians, introselect Advanced selection - median of medians, introselect Online selection - the secretary problem Online selection - the secretary problem Online selection - the secretary problem Online selection - the secretary problem Backtracking 22 lectures 02:22:42 Backtracking introduction N-queens problem introduction N-queens problem implementation I N-queens problem implementation II Hamiltonian cycle introduction Hamiltonian cycle illustration Hamiltonian cycle implementation I Hamiltonian cycle implementation II Coloring problem introduction Coloring problem implementation I Coloring problem implementation II Knight's tour introduction Knight's tour implementation I Knight's tour implementation II UPDATE: Knight's Tour Hi! Unfortunately I made a mistake in the implentation: in the for loop we consider all the possible moves so instead of boardSize.length we should use xMoves.length (so the number of possible moves)public boolean solveProblem(int stepCount, int x, int y) { if (stepCount == Constants.BOARD_SIZE * Constants.BOARD_SIZE) { return true; } for (int i = 0; i < xMoves.length; ++i) { int nextX = x + xMoves[i]; int nextY = y + yMoves[i]; if ( isValidMove(nextX, nextY) ) { this.solutionMatrix[nextX][nextY] = stepCount; if ( solveProblem(stepCount + 1, nextX, nextY) ) { return true; // good solution, keep going } this.solutionMatrix[nextX][nextY] = Integer.MIN_VALUE; } } return false; } Sorry for the inconvenience! Maze problem introduction Maze problem implementation I Maze problem implementation II Sudoku introduction Sudoku implementation I Sudoku implementation II NP-complete problems Backtracking 22 lectures 02:22:42 Backtracking introduction N-queens problem introduction N-queens problem implementation I N-queens problem implementation II Hamiltonian cycle introduction Hamiltonian cycle illustration Hamiltonian cycle implementation I Hamiltonian cycle implementation II Coloring problem introduction Coloring problem implementation I Coloring problem implementation II Knight's tour introduction Knight's tour implementation I Knight's tour implementation II UPDATE: Knight's Tour Hi! Unfortunately I made a mistake in the implentation: in the for loop we consider all the possible moves so instead of boardSize.length we should use xMoves.length (so the number of possible moves)public boolean solveProblem(int stepCount, int x, int y) { if (stepCount == Constants.BOARD_SIZE * Constants.BOARD_SIZE) { return true; } for (int i = 0; i < xMoves.length; ++i) { int nextX = x + xMoves[i]; int nextY = y + yMoves[i]; if ( isValidMove(nextX, nextY) ) { this.solutionMatrix[nextX][nextY] = stepCount; if ( solveProblem(stepCount + 1, nextX, nextY) ) { return true; // good solution, keep going } . this.solutionMatrix[nextX][nextY] = Integer ...