What is Recursive Function/Method?
A Method can call another methods but it can also call itself. When a mathod calls itself, it'll be named recursive method.
A Recursive usuallly, has the two specifications:
- Recursive method calls itself so many times until being satisfied.
- Recursive method has parameter(s) and calls itself with new parameter values.
So, what is recursive function? There is no difference between function and method except that functions are not utilizable outside of their classes. In C# we had only method but anonymous function has been added to C#, since .NET Framework 3.5. (more information)
So, it's better to say Recursive method instead of Recursive function and I say Recursive in this artcile.
Why, when and how to use Recursive in our application?
"Any program that can be written using assignment, the if-then-else
statement and the while
statement can also be written using assignment, if-then-else
and Recursion". (Fundamentals of Data Structure in C by Ellis Horowitz)
Recursive solution is a powerful and simple approach for complicated developments, but it can worsen performance because of using call stack again and again (sometimes scandal performance).
Look at the Diagram:
Call Stack Diagram
I'm going to give examples for a better conseption of its risks and rewards:
1. The Factorial
We know that the factorial (!) of a positive integer number is the product of all positive integers less than or equal to the number.
0! = 1
1! = 1
2! = 2 * 1! = 2
3! = 3 * 2! = 6
...
n! = n * (n - 1)!
The following code is a method to compute the Factorial (no recursive):
public long Factorial(int n)
{
if (n == 0)
return 1;
long value = 1;
for (int i = n; i > 0; i--)
{
value *= i;
}
return value;
}
Computing the Factorial by a recursive method. Shorter and clearer than previous code :
public long Factorial(int n)
{
if (n == 0) return 1;
return n * Factorial(n - 1);
}
You know, the factorial of n
is actually the factorial of (n-1)
mutiplied by n
, if n
> 0.
Or:
Factorial(n) returns Factorial(n-1) * n
That is the returned value of the method; and before that, we need a condition:
If n = 0 Then Return 1
I think, the program logic is now clear and we can understand it.
2. The Fibonacci Numbers
The Fibonacci numbers are the numbers in the following sequence:
0,1,1,2,3,5,8,13,21,34,55,…
If F0 = 0 and F1= 1 then:
Fn = Fn-1 + Fn-2
The following code is a method to compute Fn
(no recursive and high performance):
public long Fib(int n)
{
if (n < 2)
return n;
long[] f = new long[n+1];
f[0] = 0;
f[1] = 1;
for (int i = 2; i <= n; i++)
{
f[i] = f[i - 1] + f[i - 2];
}
return f[n];
}
If we use recursive method, our code will be more simple, but a very poor performance:
public long Fib(int n)
{
if (n == 0 || n == 1) return n;
return Fib(k - 2) + Fib(k - 1);
}
3. Boolean Compositions
Sometimes solving the problem is more complicated than the Fibonacci. For example, we want to show all possible compositions for n Boolean variables. In other words, if n = 3
, then we must have the following output:
true, true, true
true, true, false
true, false, true
true, false, false
false, true, true
false, true, false
false, false, true
false, false, false
Solving this problem without a recursive function is not so easy and not simple, when we have quantities for n
.
public void CompositionBooleans(string result, int counter)
{
if (counter == 0)
return;
bool[] booleans = new bool[2] { true, false };
for (int j = 0; j < 2; j++)
{
StringBuilder stringBuilder = new StringBuilder(result);
stringBuilder.Append(string.Format("{0} ", booleans[j].ToString())).ToString();
if (counter == 1)
Console.WriteLine(stringBuilder.ToString());
CompositionBooleans(stringBuilder.ToString(), counter - 1);
}
}
Now, we can use and call this method:
CompositionBoolean(string.Empty, 3);
For using Recursive, Ian Shlasko suggested this:
public void BooleanCompositions(int count)
{
BooleanCompositions(count - 1, "true");
BooleanCompositions(count - 1, "false");
}
private void BooleanCompositions(int counter, string partialOutput)
{
if (counter <= 0)
Console.WriteLine(partialOutput);
else
{
BooleanCompositions(counter - 1, partialOutput+ ", true");
BooleanCompositions(counter - 1, partialOutput+ ", false");
}
}
4. InnerExceptions
Recursive methods are useful for getting the last innerException
:
public Exception GetInnerException(Exception ex)
{
return (ex.InnerException == null) ? ex : GetInnerException(ex.InnerException);
}
Why the last innerException
?! That's beside the point. The subject of our talk is, if you want to get the last innerException
, you can count on Recursive method.
This code:
return (ex.InnerException == null) ? ex : GetInnerException(ex.InnerException);
is abridgment of and equivalent to the following code:
if (ex.InnerException == null) return ex;
return GetInnerException(ex.InnerException);
Now, when we have an exception, we can find the last innerException
of the exception. For example:
try
{
throw new Exception("This is the exception",
new Exception("This is the first inner exception.",
new Exception("This is the last inner exception.")));
}
catch (Exception ex)
{
Console.WriteLine(GetInnerException(ex).Message);
}
I decided to write about Anonymous Recurcive Methods, but I could't explain that better this article.
5. Find Files
I used Recursive in the sample project that you can download it. It's able to search a path and get all files form the current folder and subfolders.
private Dictionary<string, string> errors = new Dictionary<string, string>();
private List<string> result = new List<string>();
private void SearchForFiles(string path)
{
try
{
foreach (string fileName in Directory.GetFiles(path)) {
result.Add(fileName);
}
foreach (string directory in Directory.GetDirectories(path)) {
SearchForFiles(directory); }
}
catch (System.Exception ex)
{
errors.Add(path, ex.Message); }
}
The method seems not to have any satisfy condition because it will be satisfied in each directory automatically, if it iterates all files and doesn't find any subfolder there.
Consequently
We can use iterative algorithms instead of recursive and have a better performance but we may also have time expense and None-Recursive Function. The point is we have to choose the best approach which depends on situations.
Dr. James McCaffrey believes that don't use Recursive unless necessary. Read his article.
I prefer to:
A) Avoid using Recursive when the performance is a very-very important critical subject.
B) Avoid of using Recursive, when the iterative is not very "complicated".
C) Do not procrastinate about using Recursive, if (!A && !B)
For example:
Section 1 (Factorial): The iterative is not complicated then avoid recursion.
Section 2 (Fibonacci): Recursive like that is not recommended.
Of course it doesn't reduce the value of Recursive; I can remind Minimax algorithm (an important chapter in Artificial Intelligence) that Recursive is its all.
But if you decided to use a recursive method, it's better to try optimizing it with Memoization.
Good luck!