Introduction to Data structures and Trees.ppt

Introduction to Data structures and Trees

1. UNIT -1
Introduction to Data Structures

2. Data Structures
A data structure is a scheme
for organizing data in the
memory of a computer.
Some of the more commonly
used data structures include
lists, arrays, stacks, queues,
heaps, trees, and graphs.
Binary Tree

3. Data Structures
The way in which the data is
organized affects the
performance of a program
for different tasks.
Computer programmers
decide which data structures
to use based on the nature
of the data and the
processes that need to be
performed on that data.
Binary Tree

4. Example: A Queue
A queue is an example of commonly used simple data
structure. A queue has beginning and end, called the front
and back of the queue.
Data enters the queue at one end and leaves at the other.
Because of this, data exits the queue in the same order in
which it enters the queue, like people in a checkout line at
a supermarket.

5. Example: A Binary Tree
A binary tree is another
commonly used data
structure. It is organized like
an upside down tree.
Each spot on the tree, called
a node, holds an item of data
along with a left pointer and
a right pointer.
Binary Tree

6. Example: A Binary Tree
The pointers are lined up
so that the structure forms
the upside down tree, with
a single node at the top,
called the root node, and
branches increasing on the
left and right as you go
down the tree.
Binary Tree

7. Choosing Data Structures
By comparing the queue with
the binary tree, you can see
how the structure of the data
affects what can be done
efficiently with the data.

8. Choosing Data Structures
A queue is a good data structure
to use for storing things that need
to be kept in order, such as a set
of documents waiting to be
printed on a network printer.
.

9. Choosing Data Structures
The jobs will be printed in the
order in which they are received.
Most network print servers
maintain such a print queue.
.

10. Choosing Data Structures
A binary tree is a good data
structure to use for searching
sorted data.
The middle item from the list is
stored in the root node, with
lesser items to the left and greater
items to the right.

11. Choosing Data Structures
A search begins at the root. The
computer either find the data, or
moves left or right, depending on
the value for which you are
searching.
Each move down the tree cuts the
remaining data in half.

12. Choosing Data Structures
Items can be located very quickly
in a tree.
Telephone directory assistance
information is stored in a tree, so
that a name and phone number
can be found quickly.

13. Choosing Data Structures
For some applications, a queue is
the best data structure to use.
For others, a binary tree is better.
Programmers choose from
among many data structures
based on how the data will be
used by the program.

14. Data Structures in Alice
Alice has two built-in data structures
that can be used to organize data, or
to create other data structures:
• Lists
• Arrays

15. Lists
A list is an ordered set of data. It is often used to store
objects that are to be processed sequentially.
A list can be used
to create a queue.

16. Arrays
An array is an indexed set of variables, such as
dancer
[1]
, dancer
[2]
, dancer
[3]
,… It is like a set of
boxes that hold things.
A list is a set of items.
An array is a set of
variables that each
store an item.

17. Arrays and Lists
You can see the difference between arrays and
lists when you delete items.

18. Arrays and Lists
In a list, the missing spot is filled in when
something is deleted.

19. Arrays and Lists
In an array, an empty variable is left behind
when something is deleted.

20. Lists
A list is created in Alice by checking the make a
list box when creating a new variable.
Make a list box

21. Lists
The For all in order and For all together tiles can
be used to work with lists. They are at the
bottom of the editor area.

22. Arrays
Arrays can be created in a similar manner, but
more often they are created using the array
visualization object from the Alice local gallery.
The Array Visualization object
has special properties and
methods for manipulating
the elements in an array.

23. Arrays
Alice has a set of built-in functions that can be
performed on arrays.

24. CHAPTER 4 24
LISTS
All the programs in this file are selected from
Ellis Horowitz, Sartaj Sahni, and Susan Anderson-Freed
“Fundamentals of Data Structures in C”,
Computer Science Press, 1992.

25. CHAPTER 4 25
Introduction
Array
successive items locate a fixed distance
disadvantage
data movements during insertion and deletion
waste space in storing n ordered lists of varying
size
possible solution
linked list

26. CHAPTER 4 26
Dense list (array)Linked list
特性 資料存在連續的空
間,且有固定的相關
位置
資料存在任意的空間
優點 可隨機存取陣列中
的資料
插入,刪除,分割,
合併資料較有效率 ,
不同的串列可共用空
間且資料個數沒有限
制
缺點 插入,刪除資料困
難,
且資料個數受限於
陣列的大小
只能透過 link循序存
取資料,較浪費空間
( 因為多存 link )

27. CHAPTER 4 27
SINGLY LINKED LISTS
bat  cat  sat  vat NULL
*Figure 4.2: Usual way to draw a linked list (p.147)
Linked list
An ordered sequence of nodes with links
The nodes do not reside in sequential locations
The locations of the nodes may change on different runs
ptr

28. CHAPTER 4 28
typedef struct list_node *list_pointer;
typedef struct list_node {
char data [4];
list_pointer link;
}list_node;
Creation
list_pointer ptr =NULL;
Testing
#define IS_EMPTY(ptr) (!(ptr))
Allocation
ptr=(list_pointer) malloc (sizeof(list_node));
Example 4.1: create a linked list of words
Declaration

29. CHAPTER 4 29
B A T \0 NULL 
address of
first node
first datafirst link
first
*Figure 4.5:Referencing the fields of a node(p.152)
e -> name  (*e).name
strcpy(ptr -> data,
“bat”);
ptr -> link = NULL;

30. CHAPTER 4 30
typedef struct list_node *list_pointer;
typedef struct list_node {
int data;
list_pointer link;
};
list_pointer ptr =NULL
Example 4.2: (p.150)
Example: create a two-node list
10  20 NULL
ptr

31. CHAPTER 4 31
list_pointer create2( )
{
/* create a linked list with two nodes */
list_pointer first, second;
first = (list_pointer) malloc(sizeof(list_node));
second = ( list_pointer) malloc(sizeof(list_node));
second -> link = NULL;
second -> data = 20;
first -> data = 10;
first ->link = second;
return first;
} *Program 4.2:Create a tow-node list (p.152)
10  20 NULL
first

32. CHAPTER 4 32
Insert GAT after FAT
(a) Insert GAT into data [5]

1 HAT
2
3 CAT
4 EAT
5 GAT
6
7 WAT
8 BAT
9 FAT
10
11 VAT
15
4
9
1
0
3
5
7

33. CHAPTER 4 33
BAT  CAT  EAT 
(b) Insert node GAT into list (p.148)
FAT 
Insert GAT after FAT
first
1.Get a node a that is currently unused.
2.Set the data field of a to GAT.
3.Set the link field of a to point to the node after FAT, which contains
hat.
4.Set the link field of the node containing FAT to a.
HAT 
GAT 
a
×

34. CHAPTER 4 34
void insert(list_pointer *ptr, list_pointer node)
{
/* insert a new node with data = 50 into the list ptr after node */

list_pointer temp;
temp = (list_pointer) malloc(sizeof(list_node));
if (IS_FULL(temp))//判斷是否用盡記憶體 , temp==NULL
{
fprintf(stderr, “The memory is full\n”);
exit (1);
}

List Insertion:
Insert a node after a specific node
#define IS_FULL(p) (!(p))

35. CHAPTER 4 35
temp->data = 50;
if (*ptr) { // nonempty list
temp->link =node ->link;
node->link = temp;
}
else { // empty list
temp->link = NULL;
*ptr =temp;
}
}
*Program 4.3:Simple insert into front of list (p.144)
temp
50 
10  20 NULL
ptr
node

36. CHAPTER 4 36
10  20 NULL 50  20 NULL 50 
(a) before deletion (b)after deletion
Delete node other than the first node.
ptr
List Deletion
Delete the first node.
10  20 NULL 50  20 NULL 10 
ptr trail node ptr
( P.145 )
ptrtrail=NULLnode

37. CHAPTER 4 37
void delete(list_pointer *ptr, list_pointer trail,

list_pointer node)
{
/* delete node from the list, trail is the preceding node
ptr is the head of the list */
if (trail)
trail->link = node->link;
else
*ptr = (*ptr) ->link;
free(node);
}

38. CHAPTER 4 38
void print_list(list_pointer ptr)
{
printf(“The list ocntains: “);
for ( ; ptr; ptr = ptr->link)
printf(“%4d”, ptr->data);
printf(“\n”);
}
*Program 4.5: Printing a list (p.146)
Print out a list (traverse a list)

39. CHAPTER 4 39
4.3 DYNAMICALLY LINKED STACKS AND QUEUES
  NULL  
top
element link
(a) Linked Stack
  NULL  
front
element link
(b) Linked queue
rear
*Figure 4.11: Linked Stack and queue (p.157)

40. CHAPTER 4 40
#define MAX_STACKS 10 /* maximum number of stacks */
typedef struct {
int key;
/* other fields */
} element;
typedef struct stack *stack_pointer;
typedef struct stack {
element item;
stack_pointer link;
};
stack_pointer top[MAX_STACKS];
Represent n stacks

41. CHAPTER 4 41
#define MAX_QUEUES 10 /* maximum number of queues */
typedef struct queue *queue_pointer;
typedef struct queue {
element item;
queue_pointer link;
};
queue_pointer front[MAX_QUEUE], rear[MAX_QUEUES];
Represent n queues

42. CHAPTER 4 42
void push( int I, element item)
{
/* add item to the ith stack */
stackPointer temp;
MALLOC (temp, sizeof(*temp));
temp  data = item;
temp  link = top[i];
top[i] = temp;
}
*Program 4.5:Add to a linked stack (p.158)
Push in the linked stack

43. CHAPTER 4 43
element pop(int i)
{/* remove top element from the ith stack */
stack_pointer temp = top[i];
element item;
if (!temp))
return
stackEmpty();
item = temp data;
top[i] = temp link;
free(temp);
return item;
}
*Program 4.6: Delete from a linked stack (p.158)
pop from the linked stack

44. CHAPTER 4 44
enqueue in the linked queue
void addq(queue_pointer *front, queue_pointer *rear, element item)
{ /* add an element to the rear of the queue */
queue_pointer temp =
(queue_pointer) malloc(sizeof (queue));
if (IS_FULL(temp)) {
fprintf(stderr, “ The memory is full\n”);
exit(1);
}
temp->item = item;
temp->link = NULL;
if (*front) (*rear) -> link = temp;
else *front = temp;
*rear = temp; }

45. CHAPTER 4 45
dequeue from the linked queue
(similar to push)
element deleteq(queue_pointer *front) {
/* delete an element from the queue */
queue_pointer temp = *front;
element item;
if (IS_EMPTY(*front)) {
fprintf(stderr, “The queue is empty\n”);
exit(1);
}
item = temp->item;
*front = temp->link;
free(temp);
return item;
}

46. CHAPTER 4 46
Polynomials

typedef struct poly_node *poly_pointer;
typedef struct poly_node {
int coef;
int expon;
poly_pointer link;
};
poly_pointer a, b, c;
Axaxax ax
m
e
m
e e
m m
() ...  
 
 
1 2 0
1 2 0
coef expon link
Representation

47. CHAPTER 4 47
Example
a= 3x
14
+ 2x
8
+ 1
b= 8x
14
- 3x
10
+ 10x
6
3 14 .2 8 .1 0 null
a
8 14 .-3 10 .106 null
b

48. CHAPTER 4 48
Adding Polynomials
3 14 2 8 1 0
a
8 14 -3 10
b
d
a->expon == b->expon
3 14 2 8
a
8 14 -3 10
b
11 14
d
a->expon < b->expon
NULL
10 6NULL
11 14NULL
1 0NULL
10 6NULL
-3 10NULL

49. CHAPTER 4 49
Adding Polynomials (Continued)
3 14 2 8
a
8 14 -3 10
b
11 14
a->expon > b->expon
-3 10
d
1 0NULL
10 6NULL
2 8NULL

50. CHAPTER 4 50
Alogrithm for Adding Polynomials
poly_pointer padd(poly_pointer a, poly_pointer b)
{
poly_pointer front, rear, temp;
int sum;
rear =(poly_pointer)malloc(sizeof(poly_node));
if (IS_FULL(rear)) {
fprintf(stderr, “The memory is full\n”);
exit(1);
}
front = rear;
while (a && b) {
switch (COMPARE(a->expon, b->expon)) {

51. CHAPTER 4 51
case -1: /* a->expon < b->expon */
attach(b->coef, b->expon, &rear);
b= b->link;
break;
case 0: /* a->expon == b->expon */
sum = a->coef + b->coef;
if (sum) attach(sum,a->expon,&rear);
a = a->link; b = b->link;
break;
case 1: /* a->expon > b->expon */
attach(a->coef, a->expon, &rear);
a = a->link;
}
}
for (; a; a = a->link)
attach(a->coef, a->expon, &rear);
for (; b; b=b->link)
attach(b->coef, b->expon, &rear);
rear->link = NULL;
temp = front; front = front->link; free(temp);
return front;
}
Delete extra initial node.

52. CHAPTER 4 52
Analysis
(1)coefficient additions
0  additions  min(m, n)
where m (n) denotes the number of terms in A (B).
(2)exponent comparisons
extreme case
e
m-1
> f
m-1
> e
m-2
> f
m-2
> … > e
0
> f
0
m+n-1 comparisons
(3)creation of new nodes
extreme case
m + n new nodes
summary O(m+n)

53. CHAPTER 4 53
Attach a Term
void attach(float coefficient, int exponent,
poly_pointer *ptr)
{
/* create a new node attaching to the node pointed to
by ptr. ptr is updated to point to this new node. */

poly_pointer temp;
temp = (poly_pointer) malloc(sizeof(poly_node));
if (IS_FULL(temp)) {
fprintf(stderr, “The memory is full\n”);
exit(1);
}
temp->coef = coefficient;
temp->expon = exponent;
(*ptr)->link = temp;
*ptr = temp;
}

54. CHAPTER 4 54
A Suite for Polynomials
poly_pointer a, b, d, e;
.
.
.
a = read_poly();
b = read_poly();
d = read_poly();
temp = pmult(a, b);
e = padd(temp, d);
print_poly(e);
read_poly()
print_poly()
padd()
psub()
pmult()
e(x) = a(x) * b(x) + d(x)

55. CHAPTER 4 55
Erase Polynomials
void earse(poly_pointer *ptr)
{
/* erase the polynomial pointed to by ptr */
poly_pointer temp;
while (*ptr) {
temp = *ptr;
*ptr = (*ptr)->link;
free(temp);
}
}
O(n)

56. CHAPTER 4 56
Circularly Linked Lists
3 14 2 8 1 0
ptr
ptr
avail
...
avail
temp
circular list vs. chain
NULL

57. CHAPTER 4 57
Maintain an Available List
poly_pointer get_node(void)
{
poly_pointer node;
if (avail) {
node = avail;
avail = avail->link:
}
else {
node = (poly_pointer)malloc(sizeof(poly_node));
if (IS_FULL(node)) {
printf(stderr, “The memory is full\n”);
exit(1);
}
}
return node;
}

58. CHAPTER 4 58
Maintain an Available List (Continued)
void ret_node(poly_pointer ptr)
{
ptr->link = avail;
avail = ptr;
}
void cerase(poly_pointer *ptr)
{
poly_pointer temp;
if (*ptr) {
temp = (*ptr)->link;
(*ptr)->link = avail;
avail = temp;
*ptr = NULL;
}
}
Independent of # of nodes in a list O(1) constant time

59. CHAPTER 4 59
4.4.4 Representing Polynomials As Circularly Linked Lists
    
avail
temp
ptr
     NULL
avail
*Figure 4.14: Returning a circular list to the avail list (p.159)

60. CHAPTER 4 60
Head Node
3 14 2 8 1 0
a
-1a
Zero polynomial
-1
ax x 321
14 8
Represent polynomial as circular list.
(1) zero
(2) others

61. CHAPTER 4 61
Another Padd
poly_pointer cpadd(poly_pointer a, poly_pointer b)
{
poly_pointer starta, d, lastd;
int sum, done = FALSE;
starta = a;
a = a->link;
b = b->link;
d = get_node();
d->expon = -1; lastd = d;
do {
switch (COMPARE(a->expon, b->expon)) {
case -1: attach(b->coef, b->expon, &lastd);
b = b->link;
break;

62. CHAPTER 4 62
Another Padd (Continued)
case 0: if (starta == a) done = TRUE;
else {
sum = a->coef + b->coef;
if (sum) attach(sum,a->expon,&lastd);
a = a->link; b = b->link;
}
break;
case 1: attach(a->coef,a->expon,&lastd);
a = a->link;
}
} while (!done);
lastd->link = d;
return d;
}

63. CHAPTER 4 63
Additional List Operations
typedef struct list_node *list_pointer;
typedef struct list_node {
char data;
list_pointer link;
};
Invert single linked lists
Concatenate two linked lists

64. CHAPTER 4 64
Invert Single Linked Lists
list_pointer invert(list_pointer lead)
{
list_pointer middle, trail;
middle = NULL;
while (lead) {
trail = middle;
middle = lead;
lead = lead->link;
middle->link = trail;
}
return middle;
}
0: null
1: lead
2: lead
...
Use two extra pointers: middle and trail.

65. CHAPTER 4 65
Concatenate Two Lists
list_pointer concatenate(list_pointer
ptr1, list_pointer ptr2)
{
list_pointer temp;
if (IS_EMPTY(ptr1)) return ptr2;
else {
if (!IS_EMPTY(ptr2)) {
for (temp=ptr1;temp->link;temp=temp->link);
temp->link = ptr2;
}
return ptr1;
}
}
O(m) where m is # of elements in the first list

66. CHAPTER 4 66
4.5.2 Operations For Circularly Linked List
X
1  X
2  X
3

a
*Figure 4.16: Example circular list (p.165)
What happens when we insert a node to the front of a circular
linked list?
Problem: move down the whole list.

67. CHAPTER 4 67
X
1  X
2  X
3

a
*Figure 4.17: Pointing to the last node of a circular list (p.165)
A possible solution:
Note a pointer points to the last node.

68. CHAPTER 4 68
Operations for Circular Linked Lists
void insert_front (list_pointer *ptr, list_pointer
node)
{
if (IS_EMPTY(*ptr)) {
*ptr= node;
node->link = node;
}
else {
node->link = (*ptr)->link;
(*ptr)->link = node;
}
}
X
1  X
2
 X
3 
ptr

69. CHAPTER 4 69
Length of Linked List
int length(list_pointer ptr)
{
list_pointer temp;
int count = 0;
if (ptr) {
temp = ptr;
do {
count++;
temp = temp->link;
} while (temp!=ptr);
}
return count;
}

70. CHAPTER 4 70














15000
0040
00012
01100
4.7 Sparse Matrices
inadequates of sequential schemes
(1) # of nonzero terms will vary after some matrix computation
(2) matrix just represents intermediate results
new scheme
Each column (row): a circular linked list with a head node

71. CHAPTER 4 71
Revisit Sparse Matrices
down head right
next
head node
downentry right
value
rowcol
entry
aij
ij
entry node
aij
# of head nodes = max{# of rows, # of columns}
連同一列元素
連
同
一
行
元
素

72. CHAPTER 4 72
Linked Representation for Matrix
44
10
12
21
-4
02
11
33
-15
11
5
Circular linked list
a
H0 H1 H2 H3

73. CHAPTER 4 73
#define MAX_SIZE 50 /* size of largest matrix */
typedef enum {head, entry} tagfield;
typedef struct matrix_node *matrix_pointer;
typedef struct entry_node {
int row;
int col;
int value;
};
typedef struct matrix_node {
matrix_pointer down;
matrix_pointer right;
tagfield tag;

74. CHAPTER 4 74
union {
matrix_pointer next;
entry_node entry;
} u;
};
matrix_pointer hdnode[MAX_SIZE];

75. CHAPTER 4 75
[0] [1] [2]
[0]
[1]
[2]
[3]
[4]
4 4 4
0 2 11
1 0 12
2 1 -4
3 3 -15
*Figure 4.22: Sample input for sparse matrix (p.174)

76. CHAPTER 4 76
Read in a Matrix
matrix_pointer mread(void)
{
/* read in a matrix and set up its linked
list. An global array hdnode is used */
int num_rows, num_cols, num_terms;
int num_heads, i;
int row, col, value, current_row;
matrix_pointer temp, last, node;
printf(“Enter the number of rows, columns
and number of nonzero terms: “);

77. CHAPTER 4 77
scanf(“%d%d%d”, &num_rows, &num_cols,
&num_terms);
num_heads =
(num_cols>num_rows)? num_cols : num_rows;
/* set up head node for the list of head
nodes */
node = new_node(); node->tag = entry;
node->u.entry.row = num_rows;
node->u.entry.col = num_cols;

if (!num_heads) node->right = node;
else { /* initialize the head nodes */
for (i=0; i<num_heads; i++) {
term= new_node();
hdnode[i] = temp;
hdnode[i]->tag = head;
hdnode[i]->right = temp;
hdnode[i]->u.next = temp;
}

O(max(n,m))

78. CHAPTER 4 78
current_row= 0; last= hdnode[0];
for (i=0; i<num_terms; i++) {
printf(“Enter row, column and value:”);
scanf(“%d%d%d”, &row, &col, &value);
if (row>current_row) {
last->right= hdnode[current_row];
current_row= row; last=hdnode[row];
}
temp = new_node();
temp->tag=entry; temp->u.entry.row=row;
temp->u.entry.col = col;
temp->u.entry.value = value;
last->right = temp;/*link to row list */
last= temp;
/* link to column list */
hdnode[col]->u.next->down = temp;
hdnode[col]=>u.next = temp;
}

利用next field 存放column的last node

79. CHAPTER 4 79
/*close last row */
last->right = hdnode[current_row];
/* close all column lists */
for (i=0; i<num_cols; i++)
hdnode[i]->u.next->down = hdnode[i];
/* link all head nodes together */
for (i=0; i<num_heads-1; i++)
hdnode[i]->u.next = hdnode[i+1];
hdnode[num_heads-1]->u.next= node;
node->right = hdnode[0];
}
return node;
}
O(max{#_rows, #_cols}+#_terms)

80. CHAPTER 4 80
Write out a Matrix
void mwrite(matrix_pointer node)
{ /* print out the matrix in row major form */
int i;
matrix_pointer temp, head = node->right;
printf(“\n num_rows = %d, num_cols= %d\n”,
node->u.entry.row,node->u.entry.col);
printf(“The matrix by row, column, and
value:\n\n”);
for (i=0; i<node->u.entry.row; i++) {
for (temp=head->right;temp!=head;temp=temp->right)
printf(“%5d%5d%5d\n”, temp->u.entry.row,
temp->u.entry.col, temp->u.entry.value);
head= head->u.next; /* next row */
}
}
O(#_rows+#_terms)

81. CHAPTER 4 81
Erase a Matrix
void merase(matrix_pointer *node)
{
int i, num_heads;
matrix_pointer x, y, head = (*node)->right;
for (i=0; i<(*node)->u.entry.row; i++) {
y=head->right;
while (y!=head) {
x = y; y = y->right; free(x);
}
x= head; head= head->u.next; free(x);
}
y = head;
while (y!=*node) {
x = y; y = y->u.next; free(x);
}
free(*node); *node = NULL;
}
Free the entry and head nodes by row.
O(#_rows+#_cols+#_terms)
Alternative: 利用Fig 4.14的技巧，把一列資料 erase (constant time)

82. CHAPTER 4 82
Doubly Linked List
Move in forward and backward direction.
Singly linked list (in one direction only)
How to get the preceding node during deletion or insertion?
Using 2 pointers
Node in doubly linked list
left link field (llink)
data field (item)
right link field (rlink)
缺點 : 較浪費空間 ( 多一個資料鏈結 )

83. CHAPTER 4 83
Doubly Linked Lists
typedef struct node *node_pointer;
typedef struct node {
node_pointer llink;
element item;
node_pointer rlink;
}
head node
ptr
= ptr->rlink->llink
= ptr->llink->rlink
left data right

84. CHAPTER 4 84
first
*Figure 4.22:Empty doubly linked circular list with header node (p.188)

85. CHAPTER 4 85

first
x
first
x
before after
Figure 4.23: Deletion from a doubly linked circular list

86. CHAPTER 4 86
 
node
newnode
node
Insertion into an empty doubly linked circular list

87. CHAPTER 4 87
Insert
void dinsert(node_pointer node, node_pointer newnode)
{
(1) newnode->llink = node;
(2) newnode->rlink = node->rlink;
(3) node->rlink->llink = newnode;
(4) node->rlink = newnode;
}
newnode
L item R
L item R
L item R
node node2
(1) (2
)
將newnode插入在node和node2之
間
dinsert (node的位址,newnode的位
址)
(3)(4)

88. CHAPTER 4 88
Delete
deleted
L item R
L item R
L item R
node node2
(1)
(2
)
void ddelete(node_pointer node, node_pointer deleted)
{
if (node==deleted)
printf(“Deletion of head node not permitted.\n”);
else {
(1) deleted->llink->rlink= deleted->rlink;
(2) deleted->rlink->llink= deleted->llink;
free(deleted);
}
}