Graph
Binary tree
Trees
Stack
D. Stack
Traversal
Search
Sort
None of above
O(n)
O(log n)
O(n2)
O(n log n)
Divide and conquer strategy
Backtracking approach
Heuristic search
Greedy approach
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.
Abstract level
Implementation level
Application level
All of the above
Array
Stack
Tree
queue
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 n)
O(n2)
O(n log n)
FAEKCDBHG
FAEKCDHGB
EAFKHDCBG
FEAKDCHBG
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
AVL tree
Red-black tree
Lemma tree
None of the above
Best case
Null case
Worst case
Average case
by this way computer can keep track only the address of the first element and the addresses of other elements can be calculated
the architecture of computer memory does not allow arrays to store other than serially
both of above
none of above
internal change
inter-module change
side effect
side-module update
Application level
Abstract level
Implementation level
All of the above
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.
Processor and memory
Complexity and capacity
Time and space
Data and space
Stack
Input restricted dequeue
Priority queues
Output restricted qequeue
Graphs
Binary tree
Stacks
Queues
tables arrays
matrix arrays
both of above
none of above
Queue
Stack
List
None of the above
Stacks linked list
Queue linked list
Both of them
Neither of them
3,4,5,2,1
3,4,5,1,2
5,4,3,1,2
1,5,2,3,4
Stack
Queue
List
Link list
mn
max(m,n)
min(m,n)
m+n-1
floor address
foundation address
first address
base address
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
Records
Pointers
None
Stacks
Dequeues
Queues
Binary search tree
elementary items
atoms
scalars
all of above