C++ recursion practical experience sharing: summary of code optimization and skills

Recursion optimization techniques: Tail recursion optimization: The compiler performs all calculations before the function itself is called to improve efficiency. Memory: Stores previously calculated outputs to avoid repeated calculations. Iteration: Use iteration algorithm instead of recursion to improve readability and avoid stack overflow.

C Sharing of practical experience with recursion: summary of code optimization and techniques

In actual development, recursion is often used to solve complex problems question. It allows functions to call themselves, creating nested call stacks. However, excessive recursive calls may cause stack overflow and program crash.

The following are some tips for optimizing recursive code, with practical cases:

1. Tail recursion optimization

Tail recursion means that the function is All calculations are performed before calling itself, and calling itself is the last action of the function. For tail recursive calls, the compiler can optimize it by replacing the function pointer in the call stack instead of pushing a new stack frame.

int factorial(int n) {
  return n == 0 ? 1 : n * factorial(n - 1);
}

By using the tail-call optimization flag, the compiler can recognize this recursion as tail recursion and optimize it.

int factorial(int n) __attribute__ ((tailcall));

2. Memory

Memory is a technique used to store the output of the same input presented previously. When recursion keeps repeating the same computation, memoization can significantly improve performance.

int fib(int n) {
  static std::map<int, int> memo;
  if (memo.count(n) > 0) {
    return memo[n];
  }
  return memo[n] = n < 2 ? n : fib(n - 1) + fib(n - 2);
}

This code uses std::map memo to store previously calculated Fibonacci numbers.

3. Iteration

In some cases, recursive problems can be replaced by iterative algorithms. Doing so avoids the risk of stack overflow and improves code readability.

int factorial(int n) {
  int result = 1;
  while (n > 0) {
    result *= n--;
  }
  return result;
}

This code calculates the factorial iteratively instead of using recursion.

Practical Case

Fibonacci Sequence

Calculating the Fibonacci number at a given index can be done as A classic practical case of recursion. The recursive implementation using memoization is as follows:

int fib(int n) {
  static std::map<int, int> memo;
  if (memo.count(n) > 0) {
    return memo[n];
  }
  return memo[n] = n < 2 ? n : fib(n - 1) + fib(n - 2);
}

Using this code, we can efficiently calculate large Fibonacci numbers without worrying about stack overflow.

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