To perform a Depth First Search (DFS) on a 2D array in C++, you can use recursion.

Here is some sample code to perform a DFS on a 2D array:

c++
 
 
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const int ROW = 3;
const int COL = 3;

// Helper function to perform a DFS on a 2D array
void dfs(int arr[][COL], bool visited[][COL], int row, int col) {
    // Check if current cell is inside the boundaries of the array
    if (row < 0 || row >= ROW || col < 0 || col >= COL) {
        return;
    }

    // Check if current cell has been visited or its value is 0
    if (visited[row][col] || arr[row][col] == 0) {
        return;
    }

    // Mark current cell as visited
    visited[row][col] = true;
    cout << arr[row][col] << " ";

    // Visit all neighbors
    dfs(arr, visited, row - 1, col); // up
    dfs(arr, visited, row + 1, col); // down
    dfs(arr, visited, row, col - 1); // left
    dfs(arr, visited, row, col + 1); // right
}

int main() {
    int arr[ROW][COL] = {
        {1, 0, 1},
        {0, 1, 0},
        {1, 0, 1}
    };
    bool visited[ROW][COL];

    // Initialize all cells as not visited
    memset(visited, false, sizeof(visited));

    // Perform DFS on all unvisited cells
    for (int i = 0; i < ROW; i++) {
        for (int j = 0; j < COL; j++) {
            if (!visited[i][j] && arr[i][j] == 1) {
                dfs(arr, visited, i, j);
            }
        }
    }
    return 0;
}

This code will run a DFS on a 2D array containing 1s and 0s, where 1s represent cells that should be visited and 0s represent cells that should be ignored.

The code initializes all cells as unvisited and loops through all cells in the array, calling the dfs function on each unvisited cell with a value of 1. During the DFS, the code recursively visits all neighboring cells with a value of 1 and marks them as visited, outputting their values as it goes.

Here is an example function that prompts the user with a yes or no question and returns a boolean value depending on their answer:

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// JavaScript function that prompts for a yes or no answer
function askYesNoQuestion(question) {
  let answer = prompt(question + " (yes or no)");
  if (answer.toLowerCase() === "yes") {
    return true;
  } else if (answer.toLowerCase() === "no") {
    return false;
  } else {
    // If the user enters an invalid response, prompt again
    alert("Please enter 'yes' or 'no'");
    return askYesNoQuestion(question);
  }
}

// Example usage
let answer = askYesNoQuestion("Do you like pizza?");
if (answer) {
  alert("Great, me too!");
} else {
  alert("Oh no, I love pizza!");
}

In this function, prompt() is used to ask the user a yes or no question, and the user's response is compared to the strings "yes" and "no" using toLowerCase(). If the user enters an invalid response, the function prompts again by calling itself recursively. Finally, the function returns a boolean value of true or false depending on the user's answer.

Recursion is a technique in programming where a function calls itself as a subroutine to solve a particular problem. The recursive function can be called with a smaller version of the problem which leads to a smaller version of the solution, and the solution for the original problem is derived by combining the solutions of smaller subproblems.

In order to use recursion, there must be a well-defined base case, that is, a condition that causes the function to stop calling itself and return a value. Without a base case, the function will continue calling itself indefinitely, leading to a stack overflow error in most programming languages.

Recursive functions are useful for solving certain types of problems, such as searching algorithms, tree traversals, and sorting algorithms. However, recursion can be less efficient than iterative approaches, as each recursive call adds a new stack frame to the call stack, which can consume significant amounts of memory.

Here's an example of a recursive function in JavaScript that calculates the factorial of a number:

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function factorial(num) {
  if (num === 0) {
    return 1;
  } else {
    return num * factorial(num - 1);
  }
}

console.log(factorial(5)); // returns 120

In this example, the function calls itself with a smaller value of num until num reaches 0, which is the base case. Once the base case is reached, the function begins returning values from the call stack, multiplying them together to get the final result.

Recursion is a method of solving a problem where the solution depends on solutions to smaller instances of the same problem. Specifically, when a function calls itself, it is known as recursion.

The process of recursion follows a few steps:

1. A base case: this is the simplest form of the problem, and when reached, the recursion stops
2. A recursive call: this is where the function calls itself to work on a smaller version of the same problem
3. A return statement: when all the recursive calls have returned, the results are combined and returned

To illustrate this, here is an example of a recursive function written in JavaScript to calculate factorials:

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function factorial(x) { 
  // base case 
  if (x === 0) { 
    return 1; 
  } 
  // recursive call
  return x * factorial(x-1); 
} 

Here, the base case is when x equals 0, and the recursive call is x * factorial(x-1). The return statement at the end returns the recursive call once all recursive calls are complete.

A helpful way to think about recursion is through the analogy of climbing a staircase: the base case is the bottom of the staircase, the recursive call is climbing the next step, and the return statement is when you reach the top.

For more resources on recursion, visit this MDN article.

A recursive function is a function that calls itself in its definition. To write a recursive function:

1. Establish a base case – this is a condition that ends the recursive function call when it is met.
2. Establish a recursive case – this is a condition that makes the recursive call, usually calling the same function.

For example, below is a recursive JavaScript function to compute a factorial:

javascript
 
 
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function factorial(n){
  // Base case
  if (n === 0) {
     return 1;
  }
  // Recursive case
  else {
     return n * factorial(n - 1);
  }
}

You can learn more about recursive functions from this MDN article.