(chapter 7) A Concise and Practical Introduction to Programming Algorithms in Java

1A Concise and Practical Introduction to Programming Algorithms in Java © 2009 Frank Nielsen
Frank NIELSEN
nielsen@lix.polytechnique.fr
A Concise and
Practical
Introduction to
Programming
Algorithms in Java
Chapter 7: Linked lists

Agenda
● Cells and linked lists
● Basic static functions on lists
● Recursive static functions on lists
● Hashing: Resolving collisions
● Summary of search method
(with respect to time complexity)

Summary of Lecture 7
Searching:
● Sequential search (linear time) / arbitrary arrays
● Dichotomic search (logarithmic time) / ordered arrays
Sorting:
● Selection sort (quadratic time)
● Quicksort (recursive, in-place, O(n log n) exp. time)
Hashing
Methods work on arrays...
...weak to fully dynamic datasets

Memory management in Java:
AUTOMATIC
● Working memory space for functions (stack):
PASS-BY-VALUE
● Global memory for storing arrays and objects:
Allocate with new
● Do not free allocated objects, Java does it for you!
GARBAGE COLLECTOR
(GC for short)
http://en.wikipedia.org/wiki/Java_(programming_language)

Memory management
Dynamic memory: Linear arrays...
Problem/Efficiency vs Fragmentation...
Dynamic RAM
RAM cells
DRAM: volatile memory
1 bit: 1 transistor/1 capacitor,
constantly read/rewritten
HDD: hard disk, static memory

Visualizing memory
A representation
class Toto
{
double x;
String name;
Toto(double xx, String info)
{this.x=xx;
// For mutable object do this.name=new Object(info);
this.name=info;}
};
class VisualizingMemory
{
public static void Display(Toto obj)
{
System.out.println(obj.x+":"+obj.name);
}
public static void main(String[] args)
{
int i;
Toto var=new Toto(5,"Favorite prime!");
double [] arrayx=new double[10];
Display(var);
}
}
HeapFunctions
local variables
stack execution
pass-by-value
(non-persistent)
arrays
objects
persistent
int i (4 bytes)
main
Double [ ] array
Toto var
Object Toto
x
name
array[9]
...
array[1]
array[0]
Display
(pass by reference)

Garbage collector (GC)
You do not have to explicitly free the memory
Java does it automatically on your behalf
No destructor:
● for objects
● for arrays
Objects no longer referred to are automatically collected
Objects no longer needed can be explicitly “forgotten”
obj=null;
array=null;

Flashback: Searching
● Objects are accessed via a corresponding key
● Each object stores its key and additional fields
● One seeks for information stored in an object from its key
(key= a handle)
● All objects are in the main memory (no external I/O)
More challenging problem:
Adding/removing or changing object attributes dynamically
Today!

Linked list: cells and links
● Sequence is made of cells
● Each cell stores an object (cell=container)
● Each cell link to the following one
(=refer to, =point to)
● The last cell links to nothing (undefined)
● To add an element, create a new cell that...
...points to the first one (=head)
● Garbage collector takes care of cells not pointed by others

Linked list: cells and links
Cell = wagon
Link = magnet
12 99 37
head tail termination
Container:
Any object is fine

Lisp: A language based on lists
http://en.wikipedia.org/wiki/LISP
(list '1 '2 'foo)
(list 1 2 (list 3 4))
(12 (99 (37 nil)))
(head tail)
Lisp (1958) derives from "List Processing Language"
Still in widespread use nowdays

Advantages of linked lists
● Store and represent a set of objects
● But we do not know beforehand how many...
● Add/remove dynamically to the set elements
Arrays: Memory compact data-structure for static sets
Linked lists: Efficient data-structure for dynamic sets
but use references to point to successors
(reference= 4 bytes)

Linked lists
head reference

Dynamic insertion
Insert 33
Constant time operation
(think of how much difficult it is to do with arrays)

Dynamic deletion
Delete 9
Constant time operation
(think of how much difficult it is to do with arrays)

Abstract lists
Lists are abstract data-structures supporting
the following operations (interface):
Constant: Empty list listEmpty (null)
Operations:
Constructor: List x Object → List
Head: List → Object (not defined for listEmpty)
Tail: List → List (not defined for listEmpty)
isEmpty: List → Boolean
Length: List → Integer
belongTo: List x Object → Boolean
...

Linked list in Java
● null is the empty list (=not defined object)
● A cell is coded by an object (class with fields)
● Storing information in the cell = creating field
(say, double, int, String, Object)
● Pointing to the next cell amounts to contain
a reference to the next object

public class List
{
int container;
List next;
// Constructor List(head, tail)
List(int element, List tail)
{
this.container=element;
this.next=tail;
}
static boolean isEmpty(List list)
{// in compact form return (list==null);
if (list==null) return true;
else return false;
}
static int head(List list)
{return list.container;}
static List tail(List list)
{return list.next;}
}

Common mistake
● Cannot access fields of the null object
● Exception nullPointerException is raised
● Perform a test if (currentCell!=null)
to detect wether the object is void or not,
before accessing its fields
static int head(List list)
{if (list!=null)
return list.container;
else
return -1; }

public class List
{...}
class ListJava{
public static void main (String[] args)
{
List myList=new List(23,null);
}
} MemoryFunction stack
MyList (4 bytes)
Reference
main
23 null
List object
Container (int)
Reference to list

class ListJava{
{
List u=new List(6,null);
List v=new List(12,u);
}
}

u=v;

u=new List(16,u);

Browsing lists
Start from the head, and
inspect element by element (chaining with references)
until we find the empty list (termination)
Linear complexity O(n)
static boolean belongTo(int element, List list)
{
while (list!=null)
{
if (element==list.container) return true;
list=list.next;
}
return false;
}

class ListJava{
{
List u=new List(6,null);
u=new List(16,u);
u=new List(32,u);
u=new List(25,u);
System.out.println(List.belongTo(6,u));
System.out.println(List.belongTo(17,u));
}
}
List: Linear search complexity O(n)
static boolean belongTo(int element, List list)
{
while (list!=null)
{
if (element==list.container) return true;
list=list.next;
}
return false;
}
==
equals

class ListString
{
String name;
ListString next;
// Constructor
ListString(String name, ListString tail)
{this.name=new String(name); this.next=tail;}
static boolean isEmpty(ListString list)
{return (list==null);}
static String head(ListString list)
{return list.name; }
static ListString tail(ListString list)
{return list.next;}
static boolean belongTo(String s, ListString list)
{
while (list!=null)
{
if (s.equals(list.name))
return true;
list=list.next;
}
return false;
}
}
Generic lists

class ListString
{
String name;
ListString next;
...
static boolean belongTo(String s, ListString list)
{
while (list!=null)
{
return true;
list=list.next;
}
return false;
}
}
class Demo{...
ListString l=new ListString("Frank",null);
l=new ListString("Marc",l);
l=new ListString("Frederic",l);
l=new ListString("Audrey",l);
l=new ListString("Steve",l);
l=new ListString("Sophie",l);
System.out.println(ListString.belongTo("Marc",l));
System.out.println(ListString.belongTo("Sarah",l));
}
Generic lists

Length of a list
static int length(ListString list)
{
int l=0;
while (list!=null)
{l++;
list=list.next;
}
return l;
}
Note that because Java is pass-by-value
(reference for structured objects),
we keep the original value, the head of the list,
after the function execution.
System.out.println(ListString.length(l));
System.out.println(ListString.length(l));

Dynamic insertion:
Add an element to a list
static ListString Insert(String s, ListString list)
{
return new ListString(s,list);
}
l=ListString.Insert("Philippe", l);
l=new ListString("Sylvie",l);
Call static function Insert of the class ListString

Pretty-printer of lists
Convenient for debugging operations on lists
Philippe-->Sophie-->Steve-->Audrey-->Frederic-->Marc-->Frank-->null
static void Display(ListString list)
{
while(list!=null)
{
System.out.print(list.name+"-->");
list=list.next;
}
System.out.println("null");
}
ListString.Display(l);

Dynamic deletion: Removing an element
Removing an element from a list:
Search for the location of the element,
if found then adjust the list (kind of list surgery)
Garbage collector takes care of the freed cell
Take care of the special cases:
● List is empty
● Element is at the head
v w=v.next
E==query
v.next=w.next

Dynamic deletion: Removing an element
Complexity of removing is at least the complexity of
finding if the element is inside the list or not.
static ListString Delete(String s, ListString list)
{
// if list is empty
if (list==null)
return null;
// If element is at the head
if (list.name.equals(s))
return list.next;
// Otherwise
ListString v=list;
ListString w=list.next; //tail
while( w!=null && !((w.name).equals(s)) )
{v=w; w=v.next;}
// A bit of list surgery here
if (w!=null)
v.next=w.next;
return list;
}

Recursion & Lists
Recursive definition of lists yields effective recursive algorithms too!
static int lengthRec(ListString list)
{
if (list==null)
return 0;
else
return 1+lengthRec(list.next);
}
System.out.println(ListString.lengthRec(l));

Recursion & Lists
static boolean belongToRec(String s, ListString list)
{
if (list==null) return false;
else
{
return true;
else
return belongToRec(s,list.next);
}
}
...
System.out.println(ListString.belongToRec("Marc",l));
Note that this is a terminal recursion
(thus efficient rewriting is possible)

Recursion & Lists
static void DisplayRec(ListString list)
{
if (list==null)
System.out.println("null");
else
{
System.out.print(list.name+"-->");
DisplayRec(list.next);
}
}
...
ListString.DisplayRec(l);
Displaying recursively a linked list

Copying lists
Copy the list by traversing the list from its head,
and cloning one-by-one all elements of cells
(fully copy objects like String etc. stored in cells)
static ListString copy(ListString l)
{
ListString result=null;
while (l!=null)
{
result=new ListString(l.name,result);
l=l.next;
}
return result;
}
ListString lcopy=ListString.copy(l);
ListString.Display(lcopy);
Beware: Reverse the list order

Copying lists: Recursion
static ListString copyRec(ListString l)
{
if (l==null)
return null;
else
return new ListString(l.name,copyRec(l.next));
}
ListString.DisplayRec(l);
ListString lcopy=ListString.copy(l);
ListString.Display(lcopy);
ListString lcopyrec=ListString.copyRec(l);
ListString.Display(lcopyrec);
Preserve the order
Sophie-->Audrey-->Frederic-->Marc-->null
Marc-->Frederic-->Audrey-->Sophie-->null
Sophie-->Audrey-->Frederic-->Marc-->null

Building linked lists from arrays
static ListString Build(String [] array)
{
ListString result=null;
// To ensure that head is the first array element
// decrement: from largest to smallest index
for(int i=array.length-1;i>=0;i--)
result=new ListString(array[i],result);
return result;
}
String [] colors={"green", "red", "blue", "purple", "orange", "yellow"};
ListString lColors=ListString.Build(colors);
ListString.Display(lColors);
green-->red-->blue-->purple-->orange-->yellow-->null

Summary on linked lists
● Allows one to consider fully dynamic data structures
● Singly or doubly linked lists (List prev,succ;)
● Static functions: Iterative (while) or recursion
● List object is a reference
(pass-by-reference of functions; preserve head)
● Easy to get bugs and never ending programs
(null empty list never encountered)
● Do not care releasing unused cells
(garbage collector releases them automatically)

Hashing: A fundamental technique
● Store object x in array position h(x) (int)
● Major problem occurs if two objects x and y
are stored on the same cell: Collision.
Key issues in hashing:
● Finding good hashing functions that minimize collisions,
● Adopting a good search policy in case of collisions
int i;
array[i]
Object Obj=new Object();
int i;
i=h(Obj);// hashing function
array[i]

Hashing functions
● Given a universe X of keys and for any x in X,
find an integer h(x) between 0 and m
● Usually easy to transform the object into an integer:
For example, for strings just add the ASCII codes of characters
● The problem is then to transform
a set of n (sparse) integers
into a compact array of size m<<N.
(<< means much less than)

Hashing functions
Key idea is to take the modulo operation
h(k) = k mod m where m is a prime number.
static int m=23;
// TRANSCODE strings into integers
static int String2Integer(String s)
{
int result=0;
for(int j=0;j<s.length();j++)
result=result*31+s.charAt(j);
// this is the method s.hashCode()
return result;
}
// Note that m is a static variable
static int HashFunction(int l)
{return l%m;}

{
String [] animals={"cat","dog","parrot","horse","fish",
"shark","pelican","tortoise", "whale", "lion",
"flamingo", "cow", "snake", "spider", "bee", "peacock",
"elephant", "butterfly"};
int i;
String [] HashTable=new String[m];
for(i=0;i<m;i++)
HashTable[i]=new String("-->");
for(i=0;i<animals.length;i++)
{int pos=HashFunction(String2Integer(animals[i]));
HashTable[pos]+=(" "+animals[i]);
}
for(i=0;i<m;i++)
System.out.println("Position "+i+"t"+HashTable[i]);
}

Position 0 --> whale
Position 1 --> snake
Position 2 -->
Position 3 -->
Position 4 -->
Position 5 -->
Position 6 -->
Position 7 --> cow
Position 8 --> shark
Position 9 -->
Position 10 -->
Position 11 -->
Position 12 --> fish
Position 13 --> cat
Position 14 -->
Position 15 --> dog tortoise
Position 16 --> horse
Position 17 --> flamingo
Position 18 -->
Position 19 --> pelican
Position 20 --> parrot lion
Position 21 -->
Position 22 -->
Collisions in
the hash table

Hashing: Solving collision
Open address methodology
● Store object X at the first free hash table cell
starting from position h(x)
● To seek whether X is in the hash table, compute h(x)
and inspect all hash table cells until h(x) is found or a
free cell is reached.
Complexity of search time ranges from
constant O(1) to linear O(m) time
...record in another location that is still open...

Position 0 whale
Position 1 snake
Position 2 bee
Position 3 spider
Position 4 butterfly
Position 5 null
Position 6 null
Position 7 cow
Position 8 shark
Position 9 null
Position 10 null
Position 11 null
Position 12 fish
Position 13 cat
Position 14 peacock
Position 15 dog
Position 16 horse
Position 17 tortoise
Position 18 flamingo
Position 19 pelican
Position 20 parrot
Position 21 lion
Position 22 elephant
String [] HashTable=new String[m];
// By default HashTable[i]=null
{
int s2int=String2Integer(animals[i]);
int pos=HashFunction(s2int);
while (HashTable[pos]!=null)
pos=(pos+1)%m;
HashTable[pos]=new String(animals[i]);
}

Hashing: Solving collision
Chained Hashing
For array cells not open, create linked lists
Can add as many elements as one wishes

ListString [] HashTable=new ListString[m];
for(i=0;i<m;i++)
HashTable[i]=null;
{
int s2int=String2Integer(animals[i]);
int pos=HashFunction(s2int);
HashTable[pos]=ListString.Insert(animals[i],HashTable[pos]);
}
for(i=0;i<m;i++)
ListString.Display(HashTable[i]);

Executive summary of data-structures
Data-structure
O(1) O(n) O(1)
O(n)
O(1)
O(1) O(n) O(1)
Initializing Search Insert
Array
Sorted array O(n log n) O (log n)
Hashing Almost O(1) Almost O(1)
List
ArraysArrays = Pertinent data-structure for almost static data sets
ListsLists = Data-structure for fully dynamic data sets

Java has many more modern features
Objects/inheritance, Generics, APIs
INF 311

http://en.wikipedia.org/wiki/Linked_list
We presented the concept of linked lists:
A generic abstract data-structure with a set
of plain (while) or recursive static functions.
In lecture 9, we will further revisit linked lists
and other dynamic data-structures using the
framework of objects and methods.
http://www.cosc.canterbury.ac.nz/mukundan/dsal/LinkListAppl.html

(chapter 7) A Concise and Practical Introduction to Programming Algorithms in Java

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(chapter 7) A Concise and Practical Introduction to Programming Algorithms in Java