DTSA 5501 - ALGORITHMS FOR SEARCHING,
SORTING, AND INDEXING NEWEST ACTUAL
EXAM || MOST RECENT EXAM 2026-2027 ACTUAL
COMPLETE REAL EXAM QUESTIONS AND CORRECT
ANSWERS (VERIFIED ANSWERS) ALREADY GRADED
A+ | GUARANTEED SUCCESS!! NEWEST EXAM | JUST
RELEASED!!
The second smallest element of a minheap is always the
smaller of the two
children of the root node -
ANSWER-True
The minheap property is that each element is greater than
or equal to its
children (if they exist) -
ANSWER-False
Every sorted list in ascending order is a minheap - ANSWER-
True
The largest element in a minheap is always at the second half
of the array -
, ANSWER-
True
Every path from the root of a minheap with n element to a leaf
is of length at
most log(n) -
ANSWER-True
Suppose we start at the number j=1, and at each step double the
number ( j=2×j
), until we exceed a limit n, the process terminates within
Θ(log(n^2)) steps -
ANSWER-
False
If an array is already sorted in ascending order and the heapify
procedure is ran
on it, then it does not modify the array in any way -
ANSWER-True
The Find operation, which returns a value for a key if it is
present in the Hashtable, has a worst-case complexity of
O(n)O(n) for a table containing nn entries. - ANSWER-True
Expanding the number of slots in a Hashtable does not
require re-applying a
hash function to every element already stored. -
ANSWER-False
SORTING, AND INDEXING NEWEST ACTUAL
EXAM || MOST RECENT EXAM 2026-2027 ACTUAL
COMPLETE REAL EXAM QUESTIONS AND CORRECT
ANSWERS (VERIFIED ANSWERS) ALREADY GRADED
A+ | GUARANTEED SUCCESS!! NEWEST EXAM | JUST
RELEASED!!
The second smallest element of a minheap is always the
smaller of the two
children of the root node -
ANSWER-True
The minheap property is that each element is greater than
or equal to its
children (if they exist) -
ANSWER-False
Every sorted list in ascending order is a minheap - ANSWER-
True
The largest element in a minheap is always at the second half
of the array -
, ANSWER-
True
Every path from the root of a minheap with n element to a leaf
is of length at
most log(n) -
ANSWER-True
Suppose we start at the number j=1, and at each step double the
number ( j=2×j
), until we exceed a limit n, the process terminates within
Θ(log(n^2)) steps -
ANSWER-
False
If an array is already sorted in ascending order and the heapify
procedure is ran
on it, then it does not modify the array in any way -
ANSWER-True
The Find operation, which returns a value for a key if it is
present in the Hashtable, has a worst-case complexity of
O(n)O(n) for a table containing nn entries. - ANSWER-True
Expanding the number of slots in a Hashtable does not
require re-applying a
hash function to every element already stored. -
ANSWER-False
