Abstract level
Implementation level
Application level
All of the above
B. Implementation level
linear arrays
linked lists
both of above
none of above
Arrays
Records
Pointers
None
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
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
array
lists
stacks
all of above
floor address
foundation address
first address
base address
Application level
Abstract level
Implementation level
All of the above
O(n)
O(log n)
O(n2)
O(n log n)
16
12
6
10
AVL tree
Red-black tree
Lemma tree
None of the above
grounded header list
circular header list
linked list with header and trailer nodes
none of above
Arrays
Linked lists
Both of above
None of above
Graphs
Binary tree
Stacks
Queues
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
the name of array
the data type of array
the index set of the array
the first data from the set to be stored
Abstract level
Implementation level
Application level
All of the above
Processor and memory
Complexity and capacity
Time and space
Data and space
sorted linked list
sorted binary trees
sorted linear array
pointer array
internal change
inter-module change
side effect
side-module update
Sorting
Merging
Inserting
Traversal
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.
underflow
overflow
housefull
saturated
Linked lists
Stacks
Queues
Deque
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
3,4,5,2,1
3,4,5,1,2
5,4,3,1,2
1,5,2,3,4
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
Last in first out
First in last out
Last in last out
First in first out
Data
Operations
Both of the above
None of the above
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
Counting microseconds
Counting the number of key operations
Counting the number of statements
Counting the kilobytes of algorithm