3 recursion

Data Structures and Algorithms in Java
3. Recursion
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Objectives
• Recursive definition
• Recursive program/algorithm
• Recursion application
• Method calls and recursion implementation
• Anatomy of a recursive call
• Classify recursions by number of recursive calls
• Tail recursion
• Non-tail recursion
• Indirect recursion
• Nested recursion
• Excessive recursion
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Recursive definition
• Wikipedia: “A recursive definition or inductive definition is one that
defines something in terms of itself (that is, recursively). For it to
work, the definition in any given case must be well-founded,
avoiding an infinite regress”.
• A recursive definition consists of at least 2 parts:
1) A base case (anchor or the ground case) that does not contain a
reference to its own type.
2) An inductive case that does contain a reference to its own type.
For example: Define the set of natural numbers
N
set
the
in
objects
other
no
are
there
N
n
then
N
n
if
N
.
3
)
1
(
,
.
2
0
.
1




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Some other examples for recursive definition
1 if n = 0 (anchor)
n*(n-1)! if n>0 (inductive step)
n! =
• The Fibonacci sequence of natural numbers:
n if n<2
fibo(n-1) +fibo(n-2) otherwise
fibo(n) =
• The Factorial of a natural number:
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Data Structures and Algorithms in Java 5/27
Recursive program/algorithm - 1
One way to describe repetition within a computer program is the
use of loops, such as Java’s while-loop and for-loop constructs. An
entirely different way to achieve repetition is through a process
known as recursion. Recursion is a technique by which a method
makes one or more calls to itself during execution, or by which a
data structure relies upon smaller instances of the very same type
of structure in its representation. In computing, recursion provides
an elegant and powerful alternative for performing repetitive tasks.
Most modern programming languages support functional recursion
using the identical mechanism that is used to support traditional
forms of method calls. When one invocation of the method makes a
recursive call, that invocation is suspended until the recursive call
completes. Recursion is an important technique in the study of data
structures and algorithms.

Recursive program/algorithm - 2
A recursive program/algorithm is one that calls itself again.
There are three basic rules for developing recursive algorithms.
• Know how to take one step.
• Break each problem down into one step plus a smaller
problem.
• Know how and when to stop.
Example for recursive program:
public static void DecToBin(int n)
{ int q = n/2; // One step
int r = n%2; // One step
if (q > 0)
{DecToBin(q); // smaller problem
}
System.out.print(r); // after all recursive calls have been
// made last remainder printed first
}

Recursion application
• Recursive definitions are used in defining
functions or sequences of elements
• Purpose of recursive definition:
– Generating a new elements
– Testing whether an element belongs to a set (*)
• (*) The problem is solved by reducing it to a
simpler problem

Method calls and recursion implementation - 1
Each time a method is called, an activation record (AR) is allocated for it.
This record usually contains the following information:
• Parameters and local variables used in the called method.
• A dynamic link, which is a pointer to the caller's activation record.
• Return address to resume control by the caller, the address of the
caller’s instruction immediately following the call.
• Return value for a method not declared as void. Because the size of the
activation record may vary from one call to another, the returned value is
placed right above the activation record of the caller.
Each new activation record is placed on the top of the run-time stack
When a method terminates, its activation record is removed from the top
of the run-time stack
Thus, the first AR placed onto the stack is the last one removed

Creating an activation record whenever a method is
called allows the system to handle recursion
properly. Recursion is calling a method that happens
to have the same name as the caller. Therefore, a
recursive call is not literally a method calling it-self,
but rather an instantiation of a method calling
another instantiation of the same original. These
invocation are represented internally by different
activation records and are thus differentiated by the
system.
Method calls and recursion implementation - 2

Anatomy of a recursive Call
N = 4
N <= 1? NO
return (4 * factorial (3)) =
N = 3
N <= 1? NO
N = 2
N <= 1? NO
N = 1
N <= 1? YES
Return (1)
factorial(4)
factorial(3)
factorial(2)
factorial(1)
2
6
24
1
1
2
6
24
First call

Classification of recursive functions by number
of recursive calls
Considering the maximum number of recursive calls
within the body of a single activation, there are 3 types
of recursions.
• Linear recursion: Only 1 recursive call (to itself) in side
the recursive function (e.g. binary search).
• Binary recursion: There exactly 2 recursive calls (to
itself) in side the recursive function (e.g. Fibonacci
number) .
• Multiple recursion: There are 3 or more recursive calls
(to itself) in side the recursive function.

Tail recursion
• There is only one recursive call at the very end
of a method implementation
Other classification of recursions
class Main
{static void tail(int n)
{if(n >0)
{ System.out.print(n + " ");
tail(n-1);
}
}
public static void main(String [] args)
{tail(10);
System.out.println();
}
}
void nonTail (int i)
{ if (i > 0)
{tail(i-1);
System.out.print (i + "");
tail(i-1);
}
}

Non-tail recursion
• The recursive call is not at the very end of a method
implementation
public class Main
{public static void reverse() throws Exception
{char ch = (char) System.in.read();
if(ch != 'n')
{reverse();
System.out.print(ch);
}
}
public static void main(String [] args) throws Exception
{System.out.println("nEnter a string to be reversed:");
reverse();
System.out.println("n");
}
}

Convert recursion implementation
to iterative implementation using stack
{public static void nonRecursiveReverse() throws Exception
{MyStack t = new MyStack();
char ch;
while(true)
{ch = (char) System.in.read();
if(ch == 'n') break;
t.push(ch);
}
while(!t.isEmpty())
System.out.print(t.pop());
}

Indirect recursion
• If f() calls itself, it is direct recursive
• If f() calls g(), and g() calls f(). It is indirect recursion. The chain of
intermediate calls can be of an arbitrary length, as in:
f() -> f1() -> f2() -> ... -> fn() -> f()
• Example: sin(x) calculation
Recursive call tree for sin(x)
sin(x)
sin(x/3) tan(x/3) tan(x/3)
sin(x/3) cos(x/3) sin(x/3) cos(x)
sin(x/6) sin(x/6)

Nested recursion
• A function is not only defined in terms of itself but also is
used as one of the parameters
• Consider the following examples:
0 if n=0
n if n>4
h(2 +h(2n)) if n<=4
Another example of nested recursive recursion is
Ackermann’s function:
A(0, y) = y + 1
A(x, 0) = A(x - 1, 1)
A(x, y) = A(x - 1, A(x, y - 1))
h(n) =
This function is interesting because of
its remarkably rapid growth.
A(3,1) = 24 - 3
A(4,1) = 265536 - 3

Excessive recursion - 1
• Consider the Fibonacci sequence of numbers
n if n<2
fibo(n-1) +fibo(n-2) otherwise
static long fibo(long n)
{if (n<2)
return n;
else
return(fibo(n-1)+fibo(n-2));
}
This
implementation
looks very natural
but extremely
inefficient!
fibo(n) =

The tree of calls for fibo(4)
18
Fib(4)
Fib(2) Fib(3)
Fib(0) Fib(1)
1
0
Fib(2)
Fib(0) Fib(1)
1
0
Fib(1)
1
Excessive recursion - 2

More Examples – The Tower of Hanoi
19
• Rules:
Only one disk may be moved at a time.
Each move consists of taking the upper disk from one
of the rods and sliding it onto another rod, on top of
the other disks that may already be present on that
rod.
No disk may be placed on top of a smaller disk.
Source: http://en.wikipedia.org/wiki/Hanoi_tower

More Examples – The Tower of Hanoi
Algorithm
20
void moveDisks(int n, char fromTower, char toTower, char auxTower)
{if (n == 1) // Stopping condition
Move disk 1 from the fromTower to the toTower;
else
{moveDisks(n - 1, fromTower, auxTower, toTower);
move disk n from the fromTower to the toTower;
moveDisks(n - 1, auxTower, toTower, fromTower);
}
}

More Examples – Drawing fractals
21

1. Divide an interval side into three even parts
2. Move one-third of side in the direction
specified by angle
Examples of von Koch snowflakes
More Examples – Von Knoch snowflakes

Recursion vs. Iteration
23
• Some recursive algorithms can also be easily
implemented with loops
– When possible, it is usually better to use iteration,
since we don’t have the overhead of the run-time stack
(that we just saw on the previous slide)
• Other recursive algorithms are very difficult to
do any other way

Summary
• Recursive definitions are programming concepts that
define themselves
• Recursive definitions serve two purposes:
– Generating new elements
– Testing whether an element belongs to a set
• Recursive definitions are frequently used to define
functions and sequences of numbers
• Tail recursion is characterized by the use of only one
recursive call at the very end of a method
implementation.

Reading at home
Text book: Data Structures and Algorithms in Java
5 Recursion 189
5.1 Illustrative Examples - 191
5.1.1 The Factorial Function -191
5.1.3 Binary Search - 196
5.1.4 File Systems - 198
5.2 Analyzing Recursive Algorithms - 202
5.3 Further Examples of Recursion - 206
5.3.1 Linear Recursion - 206
5.3.2 Binary Recursion - . 211
5.3.3 Multiple Recursion - 212
5.4 Designing Recursive Algorithms - 214
5.6 Eliminating Tail Recursion -. 219

3 recursion

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