Last in first out
First in last out
Last in last out
First in first out
A. Last in first out
Lists
Strings
Graph
Stacks
Last in first out
First in last out
Last in last out
First in first out
Tree
Graph
Priority
Dequeue
Stacks linked list
Queue linked list
Both of them
Neither of them
Graphs
Binary tree
Stacks
Queues
floor address
foundation address
first address
base address
Divide and conquer strategy
Backtracking approach
Heuristic search
Greedy approach
Stack
Queue
List
Link list
Binary search
Insertion sort
Radix sort
Polynomial manipulation
Linked lists
Stacks
Queues
Deque
O(n)
O(log n)
O(n2)
O(n log n)
push, pop
insert, delete
pop, push
delete, insert
3 additions and 2 deletions
2 deletions and 3 additions
3 deletions and 4 additions
3 deletions and 3 additions
Counting microseconds
Counting the number of key operations
Counting the number of statements
Counting the kilobytes of algorithm
11
12
13
14
Breath first search cannot be used to find converted components of a graph.
Optimal binary search tree construction can be performed efficiently using dynamic programming.
Given the prefix and post fix walks over a binary tree.The binary tree cannot be uniquely constructe
Depth first search can be used to find connected components of a graph.
FIFO lists
LIFO list
Piles
Push-down lists
array
lists
stacks
all of above
the name of array
the data type of array
the index set of the array
the first data from the set to be stored
Stack
Input restricted dequeue
Priority queues
Output restricted qequeue
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
Application level
Abstract level
Implementation level
All of the above
The list must be sorted
there should be the direct access to the middle element in any sublist
There must be mechanism to delete and/or insert elements in list
none of above
internal change
inter-module change
side effect
side-module update
grounded header list
circular header list
linked list with header and trailer nodes
none of above
Sorting
Merging
Inserting
Traversal
tables arrays
matrix arrays
both of above
none of above
Best case
Null case
Worst case
Average case
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
LOC(Array[5]=Base(Array)+w(5-lower bound), where w is the number of words per memory cell for the array
LOC(Array[5])=Base(Array[5])+(5-lower bound), where w is the number of words per memory cell for the array
LOC(Array[5])=Base(Array[4])+(5-Upper bound), where w is the number of words per memory cell for the array
None of above