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Chapter 11:  Recursion Presentation slides for Java Software Solutions Foundations of Program Design Third Edition by John Lewis and William Loftus Java Software Solutions is published by Addison-Wesley Presentation slides are copyright 2002 by John Lewis and William Loftus. All rights reserved. Instructors using the textbook may use and modify these slides for pedagogical purposes.

Recursion Recursion is a fundamental programming technique that can provide elegant solutions certain kinds of problems Chapter 11 focuses on: thinking in a recursive manner programming in a recursive manner the correct use of recursion examples using recursion recursion in graphics

Recursive Thinking Recursion is a programming technique in which a method can call itself to solve a problem A recursive definition is one which uses the word or concept being defined in the definition itself; when defining an English word, a recursive definition usually is not helpful But in other situations, a recursive definition can be an appropriate way to express a concept Before applying recursion to programming, it is best to practice thinking recursively

Recursive Definitions Consider the following list of numbers: 24, 88, 40, 37 A list can be defined recursively      A LIST is a:  number             or a:  number  comma  LIST That is, a LIST is defined to be a single number, or a number followed by a comma followed by a LIST The concept of a LIST is used to define itself

Recursive Definitions The recursive part of the LIST definition is used several times, ultimately terminating with the non-recursive part:   number comma LIST     24     ,   88, 40, 37                number comma LIST                  88     ,   40, 37                             number comma LIST                               40     ,   37                                          number                                            37

Infinite Recursion All recursive definitions must have a non-recursive part If they don't, there is no way to terminate the recursive path A definition without a non-recursive part causes infinite recursion This problem is similar to an infinite loop with the definition itself causing the infinite “loop” The non-recursive part often is called the base case

Recursive Definitions Mathematical formulas often are expressed recursively N!, for any positive integer N, is defined to be the product of all integers between 1 and N inclusive This definition can be expressed recursively as:      1!  =  1      N!  =  N * (N-1)! The concept of the factorial is defined in terms of another factorial until the base case of 1! is reached

Recursive Definitions        5!      5 * 4!          4 * 3!              3 * 2!                  2 * 1!                      1

Recursive Programming A method in Java can invoke itself;  if set up that way, it is called a recursive method The code of a recursive method must be structured to handle both the base case and the recursive case Each call to the method sets up a new execution environment, with new parameters and new local variables As always, when the method execution completes, control returns to the method that invoked it (which may be an earlier invocation of itself)

Recursive Programming Consider the problem of computing the sum of all the numbers between 1 and any positive integer N, inclusive This problem can be expressed recursively as:

Recursive Programming public int sum (int num) { int result; if (num == 1) result = 1; else result = num + sum (num - 1); return result; }

Recursive Programming

Recursion vs. Iteration Just because we can use recursion to solve a problem, doesn't mean we should For instance, we usually would not use recursion to solve the sum of 1 to N problem, because the iterative version is easier to understand;  in fact, there is a formula which is superior to both recursion and iteration! You must be able to determine when recursion is the correct technique to use

Recursion vs. Iteration Every recursive solution has a corresponding iterative solution For example, the sum (or the product) of the numbers between 1 and any positive integer N can be calculated with a for loop Recursion has the overhead of multiple method invocations Nevertheless, recursive solutions often are more simple and elegant than iterative solutions

Indirect Recursion A method invoking itself is considered to be direct recursion A method could invoke another method, which invokes another, etc., until eventually the original method is invoked again For example, method m1 could invoke m2, which invokes m3, which in turn invokes m1 again until a base case is reached This is called indirect recursion, and requires all the same care as direct recursion It is often more difficult to trace and debug

Indirect Recursion

Maze Traversal We can use recursion to find a path through a maze; a path can be found from any location if a path can be found from any of the location’s neighboring locations At each location we encounter, we mark the location as “visited” and we attempt to find a path from that location’s “unvisited” neighbors Recursion keeps track of the path through the maze The base cases are an prohibited move or arrival at the final destination

Maze Traversal See MazeSearch.java (page xxx) See Maze.java (page xxx)

MazeSearch.java

Maze.java

Towers of Hanoi The Towers of Hanoi is a puzzle made up of three vertical pegs and several disks that slide on the pegs The disks are of varying size, initially placed on one peg with the largest disk on the bottom with increasingly smaller disks on top The goal is to move all of the disks from one peg to another according to the following rules: We can move only one disk at a time We cannot place a larger disk on top of a smaller disk All disks must be on some peg except for the disk in transit between pegs

Towers of Hanoi (Figure 11.5 here)

Towers of Hanoi A solution to the three-disk Towers of Hanoi puzzle (Figure 11.6 here)

Towers of Hanoi To move a stack of N disks from the original peg to the destination peg move the topmost N - 1 disks from the original peg to the extra peg move the largest disk from the original peg to the destination peg move the N-1 disks from the extra peg to the destination peg The base case occurs when a “stack” consists of only one disk This recursive solution is simple and elegant even though the number of move increases exponentially as the number of disks increases The iterative solution to the Towers of Hanoi is much more complex

Towers of Hanoi See SolveTowers.java (page xxx) See TowersOfHanoi.java (page xxx)

SolveTowers.java

TowersOfHanoi.java

Recursion in Graphics Consider the task of repeatedly displaying a set of tiled images in a mosaic in which one of the tiles contains a copy of the entire collage The base case is reached when the area for the “remaining” tile shrinks to a certain size See TiledPictures.java (page xxx)

TiledPictures.java

Fractals A fractal is a geometric shape than can consist of the same pattern repeated in different scales and orientations The Koch Snowflake is a particular fractal that begins with an equilateral triangle To get a higher order of the fractal, the middle of each edge is replaced with two angled line segments

Fractals (Figure 11.7 here) See KochSnowflake.java (page xxx) See KochPanel.java (page xxx)

KochSnowflake.java

KochPanel.java

Summary Chapter 11 has focused on: thinking in a recursive manner programming in a recursive manner the correct use of recursion examples using recursion recursion in graphics