Tree
Graph
Priority
Dequeue
A. Tree
Lists
Strings
Graph
Stacks
Counting the maximum memory needed by the algorithm
Counting the minimum memory needed by the algorithm
Counting the average memory needed by the algorithm
Counting the maximum disk space needed by the algorithm
array
lists
stacks
all of above
Last in first out
First in last out
Last in last out
First in first out
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
Graphs
Binary tree
Stacks
Queues
Traversal
Search
Sort
None of above
Arrays
Records
Pointers
None
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
Operations
Algorithms
Storage Structures
None of above
internal change
inter-module change
side effect
side-module update
Binary search
Insertion sort
Radix sort
Polynomial manipulation
Linked lists
Stacks
Queues
Deque
Data
Operations
Both of the above
None of the above
Much more complicated to analyze than that of worst case
Much more simpler to analyze than that of worst case
Sometimes more complicated and some other times simpler than that of worst case
None or 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.
Abstract level
Implementation level
Application level
All of the above
Arrays
Records
Pointers
Stacks
O(n)
O(log )
O(n2)
O(n log n)
True, False
False, True
True, True
False, False
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.
Counting microseconds
Counting the number of key operations
Counting the number of statements
Counting the kilobytes of algorithm
3,4,5,2,1
3,4,5,1,2
5,4,3,1,2
1,5,2,3,4
AVL tree
Red-black tree
Lemma tree
None of the above
Processor and memory
Complexity and capacity
Time and space
Data and space
Trees
Graphs
Arrays
None of above
O(n)
O(log n)
O(n2)
O(n log n)
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