Tuesday, 11 June 2019
Wednesday, 3 April 2019
Unit 2 Question Bank DS
DSA
Unit 1 MCQ Test Date:
6/7/17 Class SE-III
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1. Time required to merge
two sorted lists of size m and n, is
A - Ο(m | n) B -
Ο(m + n) C - Ο(m log n) D - Ο(n log m)
2. The Θ notation in asymptotic evaluation represents
−
3. Which of the following usees FIFO method
4. Two main
measures for the efficiency of an algorithm are
a. Processor and memory b. Complexity and capacity
c. Time and space d. Data and space
c. Time and space d. Data and space
5. The time
factor when determining the efficiency of algorithm is measured by
a. Counting microseconds b. Counting the number of key operations
c. Counting the number of statements d. Counting the kilobytes of algorithm
c. Counting the number of statements d. Counting the kilobytes of algorithm
6. The space factor when determining the efficiency of
algorithm is measured by
a. Counting the maximum memory needed by the algorithm
b. Counting the minimum memory needed by the algorithm
c. Counting the average memory needed by the algorithm
d. Counting the maximum disk space needed by the algorithm
7. Which of the following case does not exist in complexity theory
b. Counting the minimum memory needed by the algorithm
c. Counting the average memory needed by the algorithm
d. Counting the maximum disk space needed by the algorithm
7. Which of the following case does not exist in complexity theory
a. Best case b.
Worst case c. Average case d. Null case
8. The Worst case occur in linear search algorithm
when
a. Item is somewhere in the middle of the
array b. Item is not in
the array at all c. Item is the last element in the array d. Item is the last element in
the array or is not there at all
9. The Average case occur in linear search algorithm
a. When Item is somewhere in the middle of
the array b.
When Item is not in the array at all c.
When Item is the last element in the array
d. When Item is the last element in the array or is not there at all
d. When Item is the last element in the array or is not there at all
10. The complexity of the average case of an algorithm
is
a. Much more complicated to analyze than
that of worst case
b. Much more simpler to analyze than that of worst case
c. Sometimes more complicated and some other times simpler than that of worst case
d. None or above
b. Much more simpler to analyze than that of worst case
c. Sometimes more complicated and some other times simpler than that of worst case
d. None or above
11. The complexity of linear search algorithm is
a. O(n) b.
O(log n) c. O(n2) d. O(n log n)
12. The complexity of Bubble sort algorithm is
a. O(n) b.
O(log n) c. O(n2) d.
O(n log n)
13. Which of the following data structure is
not linear data structure?
a. Arrays b.
Linked lists c. Both of above d. None of above
14. Which of the following data structure is
linear data structure?
a. Trees b. Graphs c. Arrays d. None of above
15. The operation of processing each element in the
list is known as
a. Sorting b.
Merging c. Inserting d. Traversal
16. Finding the location of the element with a given
value is:
a. Traversal b.
Search c. Sort d. None of above
17. Arrays are best data structures
a. for relatively permanent collections of data
b. for the size of the structure and the data in the structure are constantly changing
c. for both of above situation d. for none of above situation
b. for the size of the structure and the data in the structure are constantly changing
c. for both of above situation d. for none of above situation
18. Linked lists are best suited
a. for relatively permanent collections of data
b. for the size of the structure and the data in the structure are constantly changing
c. for both of above situation d. for none of above situation
b. for the size of the structure and the data in the structure are constantly changing
c. for both of above situation d. for none of above situation
19. The elements of an array are stored successively
in memory cells because
a. by this way computer can keep track only
the address of the first element and the addresses of other elements can be
calculated
b. the architecture of computer memory does not allow arrays to store other than serially
c. both of above d. none of above
b. the architecture of computer memory does not allow arrays to store other than serially
c. both of above d. none of above
20. Which
of the following data structures are indexed structures?
a. linear
arrays b. linked lists c. both of above d. none of above
21. Which of
the following is not the required condition for binary search algorithm?
a. The list
must be sorted
b. there should be the direct access to the middle element in any sublist
c. There must be mechanism to delete and/or insert elements in list
d. none of above
b. there should be the direct access to the middle element in any sublist
c. There must be mechanism to delete and/or insert elements in list
d. none of above
22. Which of
the following is not a limitation of binary search algorithm?
a. must use
a sorted array
b. requirement of sorted array is expensive when a lot of insertion and deletions are needed
c. there must be a mechanism to access middle element directly
d. binary search algorithm is not efficient when the data elements are more than 1000.
b. requirement of sorted array is expensive when a lot of insertion and deletions are needed
c. there must be a mechanism to access middle element directly
d. binary search algorithm is not efficient when the data elements are more than 1000.
23.
Two dimensional arrays are also called
a. tables
arrays b. matrix arrays c. both of above d. none of above
24. A
variable P is called pointer if
a. P
contains the address of an element in DATA. b.
P points to the address of first element in DATA
c. P can store only memory addresses d. P contain the DATA and the address of DATA
c. P can store only memory addresses d. P contain the DATA and the address of DATA
25. Which of
the following data structure can't store the non-homogeneous data
elements?
a. Arrays b. Records c. Pointers d. None
26. Which of
the following data structure store the non homogeneous data elements?
a. Arrays b. Records c. Pointers d. None
27. Each
data item in a record may be a group item composed of sub-items; those items
which are indecomposable are called
a.
elementary items b. atoms c. scalars d. all of above
28. The
difference between linear array and a record is
a. An array
is suitable for homogeneous data but the data items in a record may have
different data type
b. In a record, there may not be a natural ordering in opposed to linear array.
c. A record form a hierarchical structure but a lienear array does not
d. All of above
b. In a record, there may not be a natural ordering in opposed to linear array.
c. A record form a hierarchical structure but a lienear array does not
d. All of above
29. Which of
the following statement is false?
a. Arrays
are dense lists and static data structure
b. data elements in linked list need not be stored in adjecent space in memory
c. pointers store the next data element of a list
d. linked lists are collection of the nodes that contain information part and next pointer
b. data elements in linked list need not be stored in adjecent space in memory
c. pointers store the next data element of a list
d. linked lists are collection of the nodes that contain information part and next pointer
30. Binary
search algorithm cannot be applied to
a. sorted
linked list b. sorted binary trees c. sorted linear array d. pointer array
31. When new
data are to be inserted into a data structure, but there is no available
space; this situation is usually called
a. underflow b. overflow c.
housefull d. saturated
32. Which of
the following name does not relate to stacks?
a. FIFO
lists b. LIFO list c. Piles d. Push-down lists
Data Structures Presentation Slides
Unit 1
1. Data Structure and Problem Solving
2. Recursion
3. Algorithmic Strategies
Unit 2
Unit 3
Unit 4
Unit 5
Unit 6
1. Data Structure and Problem Solving
2. Recursion
3. Algorithmic Strategies
Unit 2
Unit 3
Unit 4
Unit 5
Unit 6
Data Structures CO
Course Objectives:
1. To understand the standard and abstract data
representation methods.
2. To acquaint with the structural constraints and
advantages in usage of the data.
3. To understand the memory requirement for various data
structures.
4. To operate on the various structured data.
5. To understand various data searching and sorting
methods with pros and cons.
6. To understand various algorithmic strategies to
approach the problem solution.
Course
Outcomes:
On completion of the course, student will be able to–
1. To discriminate the usage of various structures in
approaching the problem solution.
2. To design the algorithms to solve the programming
problems.
3. To use effective and efficient data structures in
solving various Computer Engineering domain problems.
4. To analyze the problems to apply suitable algorithm
and data structure.
5. To use appropriate algorithmic strategy for better
efficiency
Data Structures University Syllabus
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Unit 1
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Introduction to Algorithm and
Data Structures
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Algorithms- Problem
Solving, Introduction to Algorithms, Characteristics of algorithms, Algorithm
design tools: flowchart,
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Algorithm design tools: Pseudo
code , Writing pseudocode for sequential searching, max, min, factorial
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Iterative and Recursive
algorithms
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Analysis of Algorithms, Complexity of algorithms- Space
complexity
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Analysis of Algorithms, Time complexity,
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Asymptotic notation- Big-O, Theta and Omega, standard
measures of efficiency.
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Data Structures- Data structure, Abstract Data
Types (ADT), Concept of linear and Non-linear, static and dynamic, persistent
and ephemeral data structures,
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Algorithmic Strategies- Introduction to algorithm
design strategies- Divide and Conquer, and Greedy strategy. #Application
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Recurrence relation - Recurrence
Relation, Linear Recurrence Relations, With constant Coefficients,
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Homogeneous Solutions. Solving
recurrence relations
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Home
assignment: Pseudo code writing and
Algorithm Analysis Class assignments: Objective questions
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2
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Linear Data Structures Using
Sequential Organization
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Sequential Organization, Linear Data Structure Using
Sequential Organization, Array as an Abstract Data Type,
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Memory Representation and
Address Calculation
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Inserting an element into an
array, Deleting an element, Multidimensional Arrays, Two-dimensional arrays,
n- dimensional arrays,
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Concept of Ordered List, Single
Variable Polynomial, Representation using arrays
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Polynomial as array of
structure, Polynomial addition,
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Polynomial multiplication,
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Sparse Matrix, Sparse matrix
representation, Sparse matrix addition,
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Transpose
of sparse matrix
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String
Manipulation Using Array.
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Case
Study- Use of sparse matrix in Social Networks and Maps. Home assignment:
Pseudo code writing for operations on arrays, strings
Class
assignments: Objective questions
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3
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Linked Lists
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Concept of Linked list, Comparison of sequential and linked
organizations, ADT, Primitive operations,
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Realization of Linked Lists, Realization of linked list
using arrays, Dynamic Memory Management,
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Linked list using dynamic memory management
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Linked list
operations, Head pointer and header node,
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Types of linked list- Linear and circular linked
lists, Singly circular linked list, operations
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Doubly
Linked List and operations, Doubly circular linked list
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Polynomial Manipulations - Polynomial addition,
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Multiplication of two polynomials using linked list
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Generalized Linked List (GLL) concept, representation
of polynomial and sets using GLL.
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Case
Study- Garbage Collection
Class Tutorial on objective questions,
Home
assignment: operations on linked lists
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4
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Stacks
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Stacks- concept, Primitive operations, Stack Abstract
Data Type
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Representation of Stacks Using Sequential
Organization, stack operations, Analysis
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Applications of Stack- Expression Evaluation and
Conversion
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Polish
notation and expression conversion
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Need
for prefix and postfix expressions, Postfix expression evaluation,
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Linked Stack and Operations, Multiple Stacks
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Recursion- concept, variants of recursion- direct,
indirect, tail and tree
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Backtracking algorithmic strategy, use of stack in
backtracking,4 queens problem
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Case Study-, Android- multiple tasks/multiple
activities and back stack
Class assignment: Presentation on Linear data structure
Applications
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5
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Queues
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Concept, Queue as Abstract Data Type, Realization of Queues
Using Arrays,
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Queue operations, Analysis
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Circular Queue, Advantages of using circular queues,
operations
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Dequeue operations
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Priority Queue, Array implementation of priority queue
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Linked
Queue and operations
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Linked
Dqueue, Multi-queues,
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Case study- Priority queue in bandwidth
management
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Home
assignment: Operations on type of
queues
Class
assignments: Application of queue
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6
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Sorting and Searching
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Searching- Search Techniques, Sequential search,
variant of sequential search- sentinel search
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Binary search, Analysis
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Fibonacci search, Analysis, Case Study
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Sorting-
Types of sorting-Internal and external sorting, General sort concepts-sort
order, stability, efficiency, number of passes
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Sorting
methods- Bubble sort, Insertion sort, Selection sort
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Quick
sort, analysis
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Heap
sort, analysis ,Shell sort
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Bucket
sort, Radix sort, analysis, Case
Study
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Home
assignment: Sorting techniques
Class
assignments: Sorting techniques
Comparison
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