The item is somewhere in the middle of the array
The item is not in the array at all
The item is the last element in the array
The item is the last element in the array or is not there at all
D. The item is the last element in the array or is not there at all
Traversal
Search
Sort
None of above
Stack
Queue
List
Link list
mn
max(m,n)
min(m,n)
m+n-1
The item is somewhere in the middle of the array
The item is not in the array at all
The item is the last element in the array
The item is the last element in the array or is not there at all
O(n)
O(log )
O(n2)
O(n log n)
Tree
Graph
Priority
Dequeue
elementary items
atoms
scalars
all of above
P contains the address of an element in DATA.
P points to the address of first element in DATA
P can store only memory addresses
P contain the DATA and the address of DATA
When Item is somewhere in the middle of the array
When Item is not in the array at all
When Item is the last element in the array
When Item is the last element in the array or is not there at all
tables arrays
matrix arrays
both of above
none of above
Stack
Input restricted dequeue
Priority queues
Output restricted qequeue
must use a sorted array
requirement of sorted array is expensive when a lot of insertion and deletions are needed
there must be a mechanism to access middle element directly
binary search algorithm is not efficient when the data elements are more than 1000.
Graph
Binary tree
Trees
Stack
sorted linked list
sorted binary trees
sorted linear array
pointer array
Stacks linked list
Queue linked list
Both of them
Neither of them
Sorting
Merging
Inserting
Traversal
Processor and memory
Complexity and capacity
Time and space
Data and space
FIFO lists
LIFO list
Piles
Push-down lists
floor address
foundation address
first address
base address
Abstract level
Implementation level
Application level
All of the above
O(n)
O(log n)
O(n2)
O(n log n)
Arrays
Records
Pointers
None
Dynamic programming
Greedy method
Divide and conquer
Backtracking
underflow
overflow
housefull
saturated
internal change
inter-module change
side effect
side-module update
for relatively permanent collections of data
for the size of the structure and the data in the structure are constantly changing
for both of above situation
for none of above situation
Arrays are dense lists and static data structure
data elements in linked list need not be stored in adjacent space in memory
pointers store the next data element of a list
linked lists are collection of the nodes that contain information part and next pointer
Stacks
Dequeues
Queues
Binary search tree
16
12
6
10
array
lists
stacks
all of above