Graphs
Binary tree
Stacks
Queues
B. Binary tree
Processor and memory
Complexity and capacity
Time and space
Data and space
elementary items
atoms
scalars
all of above
Best case
Null case
Worst case
Average case
Operations
Algorithms
Storage Structures
None of above
underflow
overflow
housefull
saturated
Data
Operations
Both of the above
None 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.
Sorting
Merging
Inserting
Traversal
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
sorted linked list
sorted binary trees
sorted linear array
pointer array
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
O(n)
O(log )
O(n2)
O(n log n)
11
12
13
14
Counting microseconds
Counting the number of key operations
Counting the number of statements
Counting the kilobytes of algorithm
mn
max(m,n)
min(m,n)
m+n-1
Arrays
Records
Pointers
None
Arrays
Records
Pointers
Stacks
Last in first out
First in last out
Last in last out
First in first out
16
12
6
10
List
Stacks
Trees
Strings
Queue
Stack
List
None of the above
Graph
Binary tree
Trees
Stack
AVL tree
Red-black tree
Lemma tree
None of the above
push, pop
insert, delete
pop, push
delete, insert
internal change
inter-module change
side effect
side-module update
FIFO lists
LIFO list
Piles
Push-down lists
3 additions and 2 deletions
2 deletions and 3 additions
3 deletions and 4 additions
3 deletions and 3 additions
Binary search
Insertion sort
Radix sort
Polynomial manipulation
linear arrays
linked lists
both of above
none of above
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