The application of recursion in C++: practical guidance in simple terms

Recursion is a programming technique in which a function calls itself, suitable for divide and conquer problems. In C, a recursive function is defined as: returnType functionName(parameters), which requires a clear baseline (termination condition) and recursive call (calling itself after updating parameters). Factorial calculation is a classic case of recursion. The code is as follows: `cpplong factorial(int n) { if (n == 0) {return 1;} else {return n * factorial(n-1);}}

Application of recursion in C

Introduction

Recursion is a powerful programming technique , which allows functions to call themselves. It is often used to solve problems that have a divide-and-conquer nature, i.e. the problem can be broken down into smaller sub-problems that can be solved recursively.

Syntax

In C, recursive functions are defined using the following syntax:

returnType functionName(parameters) {
  // 基线情况：当递归终止时要满足的条件
  if (base_case) {
    return result;
  }

  // 递归调用：函数调用自己，传入更新后的参数
  return functionName(updated_parameters);
}

Practical case: factorial

Finding the factorial of a non-negative integer is a classic example of recursion. Factorial is defined as:

factorial(n) = 1,                   if n = 0
              = n * factorial(n-1), if n > 0

The following code implements a recursive function to calculate factorial:

#include <iostream>

long factorial(int n) {
  if (n == 0) {
    return 1;
  } else {
    return n * factorial(n-1);
  }
}

int main() {
  int n;
  std::cout << "Enter a non-negative integer: ";
  std::cin >> n;

  std::cout << "The factorial of " << n << " is: " << factorial(n) << std::endl;

  return 0;
}

Other applications

Recursion can also be used to solve various problems Problems, including:

• Traversing trees and graphs
• Quick sort and merge sort
• Dynamic programming
• Backtracking method

Tip

• # Ensure that recursive functions have clear baseline conditions to prevent infinite recursion.
• Use recursion with caution as it may cause stack overflow.
• For recursive problems with a large number of subproblems, you can use memo or tail recursion optimization to improve efficiency.

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