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Part-B3
Linked Lists
Linked Lists
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Singly Linked List (§ 4.4.1)
A singly linked list is a
concrete data structure
consisting of a sequence
of nodes
Each node stores


next
element
link to the next node
node
elem

A
B
C
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D
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The Node Class for List Nodes
(the file is source/Node.java)
public class Node
{
// Instance variables:
private Object element;
private Node next;
/** Creates a node with null references to its element and next node. */
public Node()
{
this(null, null);
}
/** Creates a node with the given element and next node. */
public Node(Object e, Node n) {
element = e;
next = n;
}
// Accessor methods:
public Object getElement() {
return element;
}
public Node getNext() {
return next;
}
// Modifier methods:
public void setElement(Object newElem) {
element = newElem;
}
public void setNext(Node newNext) {
next = newNext;
}
}
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Inserting at the Head
1. Allocate a new
node
2. update new
element
3. Have new node
point to old head
4. Update head to
point to new node
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Removing at the Head
1. Update head to
point to next node
in the list
2. Allow garbage
collector to reclaim
the former first
node
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Inserting at the Tail
1. Allocate a new
2.
3.
4.
5.
node
Insert new element
Have new node
point to null
Have old last node
point to new node
Update tail to point
to new node
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Removing at the Tail
Removing at the tail
of a singly linked list
is not efficient!
There is no
constant-time way
to update the tail to
point to the previous
node
The interface of data
structure list is in
List.java.
The implementation is
in NodeList.java. But it
uses DNode.java.
Actually, it is doubly
linked list.
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Stack with a Singly Linked List
We can implement a stack with a singly linked list
The top element is stored at the first node of the list
The space used is O(n) and each operation of the
Stack ADT takes O(1) time
nodes

t
elements
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Queue with a Singly Linked List
We can implement a queue with a singly linked list


The front element is stored at the first node
The rear element is stored at the last node
The space used is O(n) and each operation of the
Queue ADT takes O(1) time
r
nodes
f

elements
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List ADT (§ 5.2.3)
The List ADT models
a sequence of
positions storing
arbitrary objects
It establishes a
before/after relation
between positions
Generic methods:

Accessor methods:


Update methods:



size(), isEmpty()

Linked Lists
first(), last()
prev(p), next(p)
replace(p, e)
insertBefore(p, e),
insertAfter(p, e),
insertFirst(e),
insertLast(e)
remove(p)
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Doubly Linked List
A doubly linked list provides a natural
implementation of the List ADT
Nodes implement Position and store:



element
link to the previous node
link to the next node
prev
next
elem
node
Special trailer and header nodes
nodes/positions
header
trailer
elements
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Insertion
We visualize operation insertAfter(p, X), which returns position q
p
A
B
C
p
A
q
B
C
X
p
A
q
B
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X
C
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Insertion Algorithm
Algorithm insertAfter(p,e):
Create a new node v
v.setElement(e)
v.setPrev(p)
{link v to its predecessor}
v.setNext(p.getNext()) {link v to its successor}
(p.getNext()).setPrev(v) {link p’s old successor to v}
p.setNext(v)
{link p to its new successor, v}
return v {the position for the element e}
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Deletion
We visualize remove(p), where p = last()
p
A
B
C
A
B
C
D
p
D
A
B
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Deletion Algorithm
Algorithm remove(p):
t = p.element
{a temporary variable to hold the
return value}
(p.getPrev()).setNext(p.getNext())
{linking out p}
(p.getNext()).setPrev(p.getPrev())
p.setPrev(null) {invalidating the position p}
p.setNext(null)
return t
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Performance
In the implementation of the List ADT
by means of a doubly linked list




The space used by a list with n elements is
O(n)
The space used by each position of the list
is O(1)
All the operations of the List ADT run in O(1)
time
Operation element() of the
Position ADT runs in O(1) time
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Terminologies
A Graph G=(V,E): V---set of vertices and
E--set of edges.
Path in G: sequence v1, v2, ..., vk of
vertices in V such that (vi, vi+1) is in E.

vi and vj could be the same
Simple path in G: a sequence v1, v2, ..., vk
of distinct vertices in V such that (vi, vi+1) is
in E.

vi and vj can not be the same
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Example:
Simple path
A path, but not simple
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Terminologies (continued)
Circuit: A path v1, v2, ..., vk such
that v1 = vk
.
Simple circuit: a circuit v1, v2, ...,
vk,where v1=vk and vivj for any 1<i,
j<k.
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Euler circuit
Input: a graph G=(V, E)

Problem: is there a circuit in G that
uses each edge exactly once.
Note: G can have multiple edges, .i.e., two
or more edges connect vertices u and v.

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Story:
The problem is called Konigsberg bridge problem

it asks if it is possible to take a walk in the town
shown in Figure 1 (a) crossing each bridge
exactly once and returning home.
solved by Leonhard Euler
[pronounced OIL-er]
(1736)
The first problem solved by using graph
theory
A graph is constructed to describe the
town.
(See Figure 1 (b).)
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The original Konigsberg bridge
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(Figure 1)
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Theorem for Euler circuit
(proof is not required)
Theorem 1 (Euler’s Theorem) The
graph has an Euler circuit if and only
if all the vertices of a connected graph
have even degree.
Proof: (if)
Going through the circuit, each
time a vertex is visited, the degree is
increased by 2. Thus, the degree of
each vertex is Linked
even.
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Proof of Theorem 1: (only if)
We give way to find an Euler circuit for a graph in
which every vertex has an even degree.

Since each node v has even degree, when we first
enter v, there is an unused edge that can be used
to get out v.
 The only exception is when v is a starting node.
 Then we get a circuit (may not contain all edges in
G)

If every node in the circuit has no unused edge, all
the edges in G have been used since G is
connected.
 Otherwise, we can construct another circuit, merge
the two circuits and get a larger circuit.
 In this way, every edge
in G can be used.
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An example for Theorem 1:
a
a
13
2
1
b
11
8
3
10
g
c
e
f
12
c
7
d
3
1
a
9
4
7
b
b
4
d
7
6
2
1
c
f
2
b
d
5
f
6
i
e
after merge
3
4
e
e
c
h
5
13
12
g
8
11
6
j
5
h
i
10
9
j
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An efficient algorithm for Euler
circuit
1. Starting with any vertex u in G, take an unused
edge (u,v) (if there is any) incident to u
2. Do Step 1 for v and continue the process until v has no unused
edge. (a circuit C is obtained)
3. If every node in C has no unused edge, stop.
4. Otherwise, select a vertex, say, u in C, with some
unused edge incident to u and do Steps 1 and 2 until
another circuit is obtained.
5. Merge the two circuits obtained to form one circuit
6. Continue the above process until every edge in G is
used.
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Euler Path

A path which contains all edges in a
graph G is called an Euler path of G.
Corollary: A graph G=(V,E) which has an
Euler path has 2 vertices of odd
degree.
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Proof of the Corollary


Suppose that a graph which has an Euler path
starting at u and ending at v, where uv.
Creating a new edge e joining u and v, we have an
Euler circuit for the new graph G’=(V, E{e}).
 From Theorem 1, all the vertices in G’ have even
degree. Remove e.
 Then u and v are the only vertices of odd degree in
G.
(Nice argument, not required for exam.)
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Representations of Graphs

Two standard ways

Adjacency-list representation


Adjacency-matrix representation


Space required O(|E|)
Space required O(n2).
Depending on problems, both representations are
useful.
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Adjacency-list representation




1
Let G=(V, E) be a graph.
V– set of nodes (vertices)
E– set of edges.
For each uV, the adjacency list Adj[u] contains all
nodes in V that are adjacent to u.
2
3
5
4
1
2
5
2
1
5
3
2
4
4
2
5
3
/
5
4
1
2
/
(a)
/
3
4
/
/
(b)
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Adjacency-matrix
representation


Assume that the nodes are numbered 1, 2, …, n.
The adjacency-matrix consists of a |V||V| matrix A=(aij)
such that
1
2
3
4
5
1
0
1
0
0
1
2
1
0
1
1
1
3
0
1
0
1
0
4
0
1
1
0
1
5
1
1
0
1
0
aij= 1 if (i,j) E, otherwise aij= 0.
2
1
3
5
4
(a)
(c)
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Implementation of Euler circuit
algorithm (Not required)

Data structures:


Adjacency matrix
Also, we have two lists to store the circuits



One for the circuit produced in Steps 1-2.
One for the circuit produced in Step 4
We can merge the two lists in O(n) time.
In Step 1: when we take an unused edge (u, v), this
edge is deleted from the adjacency matrix.
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Implementation of Euler
circuit algorithm
In Step 2: if all cells in the column and row of v is 0,
v has no unused edge.
1.
Testing whether v has no unused edge.
2.
A circuit (may not contain all edges) is obtained
if the above condition is true.
In Step 3: if all the element’s in the matrix are 0,
stop.
In step 4: if some elements in the matrix is not 0,
continue.
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Summary of Euler circuit
algorithm
 Design a good algorithm needs two
parts
1. Theorem, high level part
2. Implementation: low level part. Data
structures are important.
 We will emphasize both parts.
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Summary (Subject to change)

Understand singly linked list





How to create a list
insert at head, insert at tail, remove at head and remove
at tail.
Should be able to write program using singly linked list
We will have chance to practice this.
Know the concept of doubly linked list.


No time to write program about this.
Euler Circuit


Understand the ideas
No need for the implementation.
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My Questions: (not part of
the lecture)

Have you learn recursive call?

A function can call itself. .
Example:
f(n)=n!=n×(n-1)×(n-2)×…×2×1
and 0!=1.
It can also be written as f(n)=n×f(n-1) and f(0)=1.
Java code:
Public static int recursiveFactorial(int n) {
if (n==0) return 1;
else return n*recursiveFactorial(n-1);
}
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Remks


Delete Euler Circuit
They do not like programming, especially, complicated programming work.
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