CMSC 202 1

Recursion

Recursive Definition – one that defines something in terms of itself

Recursion – A technique that allows us to break down a problem in to one or more subproblems that are similar in form to the original problem.Either the problem or the associated data can be recursive in nature

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Iterative FactorialIterative definition

N! = N * (N-1) * (N-2) * … * 3 * 2 * 1

int factorial (int n) { int i, result; result = 1; for (i = 1; i <= n; i++) { result = result * i; } return ( result );}

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Recursive FactorialRecursive N! definition N! = 1 if N = 0 = N * (N-1)! Otherwise

int factorial ( int n) { if (n == 0) return (1);

return (n * factorial(n - 1) );}

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Iterative vs Recursive factorial

Iterative

1. 2 local variables

2. 3 statements

3. Saves solution in an intermediate variable

Recursive

1. No local variables

2. One statement

3. Returns result in single expression

Recursion simplifies factorial by making the computer do the work.

What work and how is it done?

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How does it work?

Each recursive call creates an “activation record” which contains

local variables and parameters

return address

and is saved on the stack.

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Iterative Power

Iterative definition XN = X * X *X ….. * X (N factors)

double power(double number, int exponent){ double p = 1;

for (int i = 1; i <= exponent; i++) p = p * p; return (p);}

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Recursive Power

Recursive definitionXN = 1 if N = 0

= X * X(N-1) otherwisedouble power(double number, int exponent)// Precondition: exponent >= 0{ if (exponent == 0) return (1);

return (number * power(number, exponent-1));}

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Recursive String Reversal

void RString (char *s, int len){ if (len <= 0) return;

RString (s+1, len-1);

cout << *s ;}

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Recursive Data Structures

Array -- a set of data elements store in contiguous memory cells

Array -- zero elements OR

a single data element OR

an array followed by a single element

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Iteratively Sum an Array

int SumArray (int a[ ], int size)

{

int j, sum = 0;

for ( j = 0; j < size; j++ )

sum += a[ j ];

return sum;

}

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Recursively Sum an Arrayint SumArray ( int a [ ], int size)

{

if (size == 0)

return 0;

else

return array[ size – 1] + SumArray (a, size – 1);

}

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Approach to Writing Recursive Functions

Using “factorial” as an example,

1. Write the function header so that you are sure what the function will do and how it will be

called.

[For factorial, we want to send in the integer for which we want to compute the factorial. And we want to receive the integer result back.]

int factorial(int n)

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Approach (cont’d)

2. Decompose the problem into subproblems (if necessary).

For factorial, we must compute (n-1)!

3. Write recursive calls to solve those subproblems whose form is similar to that of the original problem.

There is a recursive call to write:

factorial(n-1) ; ]

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Approach (cont’d)

4. Write code to combine, augment, or modify the results of the recursive call(s) if necessary to construct the desired return value or create the desired side effects.

When a factorial has been computed, the result must be multiplied by the current value of the number for which the factorial was taken:

return (n * factorial(n-1));

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Approach (cont’d)

5. Write base case(s) to handle any situations that are not handled properly by the recursive portion of the program.

The base case for factorial is that if n=0, the factorial is 1:

if (n == 0) return(1);

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Ensuring that Recursion Works

Using “factorial” as an example,

1. A recursive subprogram must have at least one base case and one recursive case (it's OK to have more than one base case and/or more than one recursive case).

The first condition is met, because if (n==0) return 1 is a base case, while the "else" part includes a recursive call (factorial(n-1)).

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Does It Work? (cont’d)

2. The test for the base case must execute before the recursive call.

If we reach the recursive call, we must have already evaluated if (n==0); this is the base case test, so this criterion is met.

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Does It Work? (cont’d)

3. The problem must be broken down in such a way that the recursive call is closer to the base case than the top-level call.

The recursive call is factorial(n-1). The argument to the recursive call is one less than the argument to the top-level call to factorial. It is, therefore, “closer” to the base case of n=0.

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Does It Work? (cont’d)

4. The recursive call must not skip over the base case. Because n is an integer, and the recursive call reduces n by just one, it is not possible to skip over the base case.

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Does It Work? (cont’d)

5. The non-recursive portions of the subprogram must operate correctly.

Assuming that the recursive call works properly, we must now verify that the rest of the code works properly. We can do this by comparing the code with our definition of factorial. This definition says that if n=0 then n! is one. Our function correctly returns 1 when n is 0. If n is not 0, the definition says that we should return (n-1)! * n. The recursive call (which we now assume to work properly) returns the value of n-1 factorial, which is then multiplied by n. Thus, the non--recursive portions of the function behave as required.

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Recursion vs. Iteration

Recursion

Usually less code – algorithm can be easier to follow (Towers of Hanoi, binary tree traversals, flood fill)

Some mathematical and other algorithms are naturally recursive (factorial, summation, series expansions, recursive data structure algorithms)

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Recursion vs. Iteration (cont’d)

Iteration

Use when the algorithms are easier to write, understand, and modify (especially for beginning programmers)

Generally, runs faster because there is no stack I/O

Sometimes are forced to use iteration because stack cannot handle enough activation records (power(2, 5000))

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Direct RecursionA C function is directly recursive if it contains an explicit call to itself

Int foo (int x)

{

if ( x <= 0 ) return x;

return foo ( x – 1);

}

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Indirect RecursionA C function foo is indirectly recursive if it contains a call to another function that ultimately calls foo.

int foo (int x){

if (x <= 0) return x;

return bar(x);

}

int bar (int y)

{

return foo (y – 1);

}

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Tail Recursion

A recursive function is said to be tail recursive if there is no pending operations performed on return from a recursive call

Tail recursive functions are often said to “return the value of the last recursive call as the value of the function”

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factorial is non-tail recursive

int factorial (int n){ if (n == 0) return 1; return n * factorial(n – 1);}

Note the “pending operation” (namely the multiplication) to be performed on return from each recursive call

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Tail recursive factorialint fact_aux (int n, int result) {

if (n == 1) return result;return fact_aux (n – 1, n * result);

}

factorial (int n) {

return fact_aux (n, 1);

}

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Linear Recursion A recursive function is said to be linearly recursive when no pending operation invokes another recursive call to the function.

int factorial (int n){ if (n == 0) return 1; return n * factorial ( n – 1);}

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Linear Recursive Count_42s

int count_42s(int array[ ], int n){ if (n == 0) return 0;

if (array[ n-1 ] != 42) { return (count_42s( array, n-1 ) ); }

return (1 + count_42s( array, n-1) );}

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Tree Recursion

A recursive function is said to be tree recursive (or non-linearly recursive when the pending operation does invoke another recursive call to the function.

The Fibonacci function fib provides a classic example of tree recursion.

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Fibonacci NumbersThe Fibonacci numbers can be recursively defined by the rule:

fib(n) = 0 if n is 0, = 1 if n is 1, = fib(n-1) + fib(n-2) otherwise

For example, the first seven Fibonacci numbers are Fib(0) = 0 Fib(1) = 1 Fib(2) = Fib(1) + Fib(0) = 1 Fib(3) = Fib(2) + Fib(1) = 2 Fib(4) = Fib(3) + Fib(2) = 3 Fib(5) = Fib(4) + Fib(3) = 5 Fib(6) = Fib(5) + Fib(4) = 8

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Tree Recursive Fibonacci// Note how the pending operation (the +)// needs a 2nd recursive call to fib

int fib(int n){ if (n == 0) return 0;

if (n == 1) return 1;

return ( fib ( n – 1 ) + fib ( n – 2 ) );}

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Tree Recursive Count_42sint count_42s(int array[ ], int low, int high){ if ((low > high) || (low == high && array[low] != 42)) { return 0 ; }

if (low == high && array[low] == 42) { return 1; }

return (count_42s(array, low, (low + high)/2) + count_42s(array, 1 + (low + high)/2, high)) );}

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Converting Recursive Functions to Tail Recursion

A non-tail recursive function can often be converted to a tail recursive function by means of an “auxiliary” parameter that is used to form the result.

The idea is to incorporate the pending operation into the auxiliary parameter in such a way that the recursive call no longer has a pending operations (is tail recursive)

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Tail Recursive Fibonacciint fib_aux ( int n, int next, int result ) { if ( n == 0 ) return result; return ( fib_aux ( n - 1, next + result, next ));}

int fib ( int n ){ return fib_aux ( n, 1, 0 );}

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Converting Tail Recursive Functions to Iterative

Let’s assume that any tail recursive function can be expressed in the general form

F ( x ) {

if ( P( x ) ) return G( x );

return F ( H( x ) );

}

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Tail Recursive to Iterative(cont’d)

P( x ) is the base case of F(x)

If P(x) is true, then the value of F(x) is the value of some other function, G(x).

If P(x) is false, then the value of F(x) is the value of the function F on some other value H(x).

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Tail Recursive to Iterative(cont’d)

F( x ) {

int temp_x; while ( P(x) is not true ) {

temp_x = x;x = H (temp_x);

} return G ( x );

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Example – tail recursive factorial

int fact_aux (int n, int result){ if (n == 1) return result; return fact_aux (n – 1, n * result)}

F = fact_auxx is really two params – n and resultvalue of P(n, result) is value of (n == 1)value of G(n, result) is resultvalue of H(n, result) is (n – 1, n * result)

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Iterative factorialint fact_aux (int n, int result) { int temp_n, temp_result;

while ( n != 1 ) { // while P(x) not truetemp_n = n; // temp_x = x (1)

temp_result = result; // temp_x = x (2)n = temp_n – 1; // H (temp_x) (1) result = temp_n * temp_result; // H (temp_x) (2)

} return result; // G (x)

}

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Converting Iteration to Tail Recursion

Just like it’s possible to convert tail-recursion into iteration, it’s possible to convert any iterative loop into the combination of a recursive function and a call to that function

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A while-loop exampleThe following code fragment uses a while loop to read values into an integer array until EOF occurs, counting the number of integers read.

nt nums [MAX];int count = 0;

while (scanf (“%d”, &nums[count]) != EOF)count++;

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While loop example (cont’d)

The key to implementing the loop using tail recursion is to determine which variables capture the “state” of the computation and use these variables as parameters to the tail recursive subprogram.

count – the number of integers read so farnums -- the array that stores the integers

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While loop example (cont’d)

Since we are interested in getting the final value for count, we will write a function that returns count as its result.If the termination condition (EOF) is not true, the function increments count, reads a number into nums and calls itself recursively to to input the remainder of the numbers.If the termination condition is true, the function simply returns the final value of count.

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While loop example (cont’d)

int read_nums (int count, int nums[ ] ){ if (scanf (“%d”, &nums[count] != EOF))

return read_nums (count + 1, nums); return count;}

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While loop example (cont’d)

To call the function, we must pass in the appropriate initial values

count = read_nums (0, nums);

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Converting Iteration to Tail recursion

• Determining the variables used by the loop

• Writing tail-recursive function with one parameter for each variable

• Using the loop-termination condition as the base case

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Converting Iteration to Tail recursion (cont’d)

•Determining how each variable changes from one iteration to the next and handing the sequence of expressions that represent those changes to the recursive call

• Replacing the iterative loop with a call to the tail recursive function with appropriate initial values

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An exercise for the StudentConvert the following for loop that finds the maximum value in an array to be tail recursive. Assume that the function max( ) returns the larger of the two parameters returned to it.

int nums[MAX]; // filled by some other functionint max_num = nums[ 0 ];for (j = 0; j < MAX; j++)

max_num = max (max_num, nums[ j ] );

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Floodfill

void Image::floodfill(int x, int y){ if (x < 0 || x >= numRows || y < 0 || y >= numCols) return;

if (a[x][y] == '1') return;

if (a[x][y] == '0') a[x][y] = '1';

floodfill(x+1, y); // Go up floodfill(x-1, y); // Go down floodfill(x, y-1); // Go left floodfill(x, y+1); // Go right}