When an entity calls itself
, the program is called recursive
.
When there is a loop (or repetition)
, the program is called an iterative call
.
Example: Program to find the factorial of a number
## Time complexity comparison
The time complexity of finding recursion is more difficult than that of iteration.
Recursion: The time complexity of recursion can be found by finding the value of the nth recursive call based on the previous calls. Therefore, finding the target case based on the base case, and solving it based on the base case, allows us to understand the time complexity of the recursive equation.
Iteration: The time complexity of an iteration can be found by finding the number of loops repeated within the loop.
Usage comparison
Overhead
Recursion: Recursion has the overhead of repeated function calls, that is, due to
repeated calls to the same function,
the time complexity of the code Increased many times.
Iteration: Iteration does not involve any such overhead.
Infinite Repetition
Infinite Repetition in recursion will cause CPU crash, but in During the iteration, it stops when memory is exhausted.
Recursion: In Recursion, infinite recursive calls may occur due to errors in the specified basic conditions, and continuous calls will never be false. function, which may cause the system CPU to crash.
Iteration: Infinite iteration due to an iterator assignment or increment error or a termination condition error will result in an infinite loop, which may or may not cause the system to Error, but will definitely stop further execution of the program.
##Recursion |
Iteration | |
---|---|---|
The function calls itself. | A set of instructions that are executed repeatedly. | |
for functions. | For loops. | |
Through the base case, there will be no function calls here. | When the iterator's termination condition is no longer met. | |
Use when code size needs to be small and time complexity is not an issue. | Use when time complexity needs to be balanced against expanded code size | |
Less code | More code | |
Very high (usually exponential) time complexity. | The time complexity is relatively low (generally polynomial-logarithm). | |
The space complexity is higher than iteration. | The space complexity is low. | |
The stack here is used to store local variables when functions are called. | Do not use the stack. | |
Execution is slow because it has the overhead of maintaining and updating the stack. | Generally, it is faster than recursion because it does not use the stack. | |
Recursion uses more memory compared to iteration. | There is no overhead because there are no function calls in the iteration. | |
Have the overhead of repeated function calls. | There is no overhead because there are no function calls in the iteration. | |
If a recursive function does not satisfy the termination condition or is undefined or the base case is never reached, it will result in a stack overflow error and the system may run indefinitely Crash in recursion. | If the control condition of the iteration statement is never false or the control variable does not reach the terminal value, it will cause an infinite loop. In an infinite loop, it uses CPU cycles again and again. |
public class Test { // ----- 递归 ----- // 求给定数的阶乘的方法 static int factorialUsingRecursion(int n) { if (n == 0) return 1; // 递归呼叫 return n * factorialUsingRecursion(n - 1); } // -----迭代 ----- //求给定数的阶乘的方法 static int factorialUsingIteration(int n) { int res = 1, i; // 迭代 for (i = 2; i <= n; i++) res *= i; return res; } public static void main(String[] args) { int num = 5; System.out.println("Factorial of " + num + " using Recursion is: " + factorialUsingRecursion(5)); System.out.println("Factorial of " + num + " using Iteration is: " + factorialUsingIteration(5)); } }
Factorial of 5 using Recursion is: 120 Factorial of 5 using Iteration is: 120
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