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SCHOOL OF COMPUTING
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
BHARATH INSTITUTE OF SCIENCE AND TECHNOLOGY
WELCOMES NBA EXPERT COMMITTEE

DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING
➢ PART I : INTRODUCTION
Department/ Faculty/ Student Achievements
CRITERIA 1 - Vision, Mission and Program Educational Objectives
CRITERIA 2 - Program Curriculum and Teaching –Learning Processes
CRITERIA 3 -Program Outcomes and Course Outcomes
CRITERIA 4 - Student Performance
CRITERIA 5 -Faculty Information and Contributions
CRITERIA 6 - Facilities and Technical Support
CRITERIA 7 - Continuous Improvement
➢ PART II : OBE PHILOSOPHY OF CSE DEPARTMENT
PRESENTATION OVERVIEW
9/2/2021 2

1984
B. E (CSE)
1998
B. E (CSE)
2016
B. Tech , M. Tech , Ph. D
UNIVERSITY OF MADRAS ANNA UNIVERSITY BHARATH INSTITUTE OF HIGHER EDUCATION AND
RESEARCH- BIST
DEPARTMENT PROFILE
B. Tech – CSE
YEAR 2020-21 2019-20 2018-19
SANCTIONED INTAKE 1140 1140 1140
ENROLLED 1128 1133 845
FACULTY 203 143 83
ENROLLMENT RATIO 90.82 %
2003
COURSES OFFERED
 B. Tech - Computer Science and Engineering
 M. Tech - Computer Science and Engineering
 Ph. D - Computer Science and Engineering
9/2/2021 3

Student
Activity
Supported
Campus
Placement
Entrepreneurship
NAAC
Vibrant Student
Domain
Expertise
Faculty-
Journals
Books
Patents
Projects
Industry –
Institute
Partnership
Scopus, WoS, SCI, UGC Publications
HCL, Wipro, Infosys, L & T
Infotech, Cognizant, ZOHO,
Capgemini, Amazon,
Hexaware, Tech Mahindra
One 18, Zunzo , Go Cart, CARS36,
Locate Health, Trucks Trade,
Business Book, Furni made, Cars
Cloud, Team Work, Starmobin
Seminars, Workshops,
Conferences,Symposium,
Co-Curricular Activities,
Extra Curricular Activities
Doctorates-78
Student Strength - 3036
DEPARTMENT RECOGNITIONS
IBM Collaborative Programs, MOUs
NAAC Accreditation with ‘A’ grade in 2015( 5 Years ).
9/2/2021 4

 B.Tech CSE Artificial Intelligence – IBM, India Associated .
 B.Tech CSE Cyber Security – IOA, U.K Associated.
 Established two Centre Of Excellence(CoE) Research
Laboratories at 2019 .
 Machine Cognition
Digital Forensic
 International and National events are organized along with
Industries to enrich knowledge of faculty and students.
 Placement ratio in Premier IT companies has been
improved.
 Data Science
CAPGEMINI
)
 Artificial Intelligence
Red Hat India Private
Limited
 Red Hat Enterprise
 Linux
ORACLE
 Internet of Things
 Virtual Computing
VMware
Siemens
 NIT
 Cyber Security
Risk Sense
AREA OF
COLLABORATION
MOUs with Industries
9/2/2021 5
CSE DEPARTMENT RECOGNITIONS

FACULTY AWARDS & ACHIEVEMENT
Dr .G. UMARANI SRIKANTH
 Distinguished women in engineering-Venus International Foundation
 Leading educationist of India award-Venus International Foundation
 Bharat excellence award-Venus International Foundation
Dr. K.P.KALIYAMURTHIE
 Best Senior Faculty Award - Novel Research Academy, Puducherry
 Global Eminent Researcher Award-VIJ Trust
Dr. S. NEDUNCHELIYAN
 Best Research Supervisor Award 2015- Grabs Educational Charitable Trust,
Chennai
 Best NSS Unit Award 2017- Anna University, Chennai
 Achiever Award 2020- Kalam Dream Trust, Chennai
 Life Time Achievement Award 2020- Bestow Edutrex International Award,
Bombay
Dr .C.RAJABHUSHANAM
 Best Employee 2007-2008 - Research Data Systems Corp, USA
 Commendation Member of Organizing Committee, TECHSHASTRA 2019 -
BIST
 Has 5 Patents awarded 2019-20- BIST
NAME OF THE
FACULTY
NAME OF THE AWARD
RECEIVED
Dr. B.Persis Urbana Ivy
Best Researcher Award
Best Teacher Award
Dr. Anitha Karthi
Best Lecturer Award
Best Performer Award
Dr. J. Paramesh Best Teaching Staff Award
Dr. K. Rameshkumar
Best Teacher Award
Patent Appreciation Award
Book Publication Appreciation
Award
Research Promotion
Appreciation Award
Dr. S. Thaiyalnayaki 100% Result Awards
Dr. M.K.Vidhyalakshmi Best Proctor Award
Mrs. C.Geetha
Best Result Producer Cash
Award
9/2/2021 6

Our Student Mr. Keerthan Chand(U19CS043 )
have contributed to develop the SDSAT (Satish
Dhawan Sat). The purpose of this satellite is to
study space radiation Magnetosphere and
Demonstrate the indigenously designed and
developed nano satellite components as part of
the Aatmanirbhar Bharat.
https://youtu.be/Hbx7J2XPHq8
STUDENT ACHIEVEMENT
9/2/2021 7

STUDENT ACHIEVEMENT
Darshan and team
were III runners up
in Smart India
Hackathon
Chandramouly
and team won 1st
Prize in Banyan
Hack
Larika team won
Make in India
Paper Publication
Guhan completed
cultural internship
project in Egypt.
Meghna complete an
Internship through
AIESEC
Hema got 2nd place in
Coding Contest-
International
Symposium
Himabindu is persuing
PhD in Stanford University.
Akshatha and Team
attended final round
of #UNITED BY HCL
Hackathon in
Manchester City.
Arinjita Paul pursuing
Ph.D at IIT Madras
Abishek received CSE
Department Topper
Award .
Prasad Published
Journal at International
Conference at
Presidency College.
Bade Anil received
Python for Data Science
Badge by IBM
9/2/2021 8

DEPARTMENT VISION & MISSION
9/2/2021 9
CRITERIA 1
VISION
Department of Computer Science and
Engineering envisions and constantly strives to
provide an excellent academics and faculty to
inherit a professional competence along with
high technical knowledge, communication
skills, human dignity and values cater to the
needs of Industries and research organization
in global arena.
MISSION
M1 : To mould the computer science and engineering
graduates to global standards with expertise and knowledge
to shoulder accountable position in the field.
M2 : To provide hands-on experience in the advancements of
the Computer Science and Engineering field which is
required for the growing dynamic IT and ITES(IT Enabled
Services) Industries.
M3:To shape strong personal, technical, research,
entrepreneurial, and leadership skills.
M4 : To train knowledge in life long learning, professional
ethics and contribution to the society

PEO1 - PREPARATION
❖ To provide students with sound fundamental in Mathematical, Scientific and Engineering fundamentals necessary to
formulate, analyse, and comprehend the fundamental concepts essential to articulate, solve and assess engineering problems
and to prepare them for research & development and higher learning.
PEO2 - CORE COMPETENCE
❖ To apply critical reasoning, quantitative, qualitative, designing and programming skills, to identify, solve problems and to
analyze the experimental evaluations, and finally making appropriate decisions along with knowledge of computing principles
and applications and be able to integrate this knowledge in a variety of Industry and inter-disciplinary setting.
PEO3 - PROFESSIONALISM
❖ To broaden knowledge to establish themselves as creative practicing professionals locally and globally, in fields such as design,
development, problem solving to production support in software industries and R&D sectors.
PEO4 - SKILL
❖ To provide better opportunity to become a future researchers / scientist with good communication skills so that they may be
both good team-members and leaders with innovative ideas for a sustainable development.
PEO5 - ETHICS
❖ To be ethically and socially responsible solution providers and entrepreneurs in Computer Science and other engineering
discipline.
PROGRAM EDUCATIONAL OBJECTIVES (PEOs)
9/2/2021 10
CRITERIA 1

PO1: Engineering Knowledge
PO2: Problem Analysis
PO3: Design/Development of Solutions
PO4: Conduct investigations of complex
problems
PO5: Modern Tool usage
PO6: Engineer & Society
PO7: Environment & Sustainability
PO8: Ethics
PO9: Individual & Team work
PO10: Communication
PO11: Project Management & Finance
PO12: Life long learning
PSO1
The computer science and engineering
graduates to apply standard Software
Engineering practices and strategies like
analysis, develop, test, apply in projects and
other technologies to deliver quality product.
PSO2
Design and develop computer
programs/computer-based system in the
areas related to algorithms, networking
protocol application, web design and cloud
with intelligence computing of varying
complexity.
PSO3
Acquaint with the contemporary skills in
Artificial Intelligence, Machine Learning and
data Analytics projects industrial/research
setting and thereby innovate novel solutions
to the existing problems.
PROGRAM OUTCOMES
(POs)
PROGRAM SPECIFIC OUTCOMES
(PSOs)
Vision and Mission of the
Institution and
Department
Programme Outcomes
and Programme Specific
Outcomes
Discussion with Faculty
members by HoD
Inputs from Premier
National and International
Universities
Inputs from Stakeholders,
Managemet,
Alumini,
Employer,
Students,
Faculty,
Industry Experts,
Professional Bodies,
Parents,
Academician and
Government Agency
(UGC and AICTE)
Structure of the
Curriculum
Course Outcomes and
Syllabus
Board of Studies
Academic Council
Approved and Finalized
Curriculum and Syllabi
CO, PO and PSO
attainment
measured
(if any changes
needed)
PROGRAM CURRICULUM PROCESS
9/2/2021 11
CRITERIA 2

COURSE CATEGORIES CREDITS
R 2015 R 2018
Humanities and Social Sciences HS 16 9
Maths & Basic Sciences BS 36 38
Engineering Sciences ES 18 21
Professional Core & Core Electives PC 95 69
Non Major and Open Electives (NE & OE) OE 15 8
Project Work & Research (PR) PR 16 13
Professional Elective PE - 15
Engineering Electives EE - 2
TOTAL CREDITS 196 175
HS
8%
18%
ES
9%
PC
49%
OE
8%
PR
8%
PE
0% EE
0%
R 2015
STRUCTURE & COMPONENTS OF THE CURRICULUM
HS
5% BS
22%
ES
12%
PC
39%
OE
5%
PR
7% PE
9%
EE
1%
R 2018
9/2/2021 12
CRITERIA 2

M5:
Human Values and Ethics
PLANNING
• Academic Plan
• Lesson Plan
• Course Allocation
• Course Registration
TEACHING
• Class Conduction
• Lab Conduction
• Project Conduction
ACADEMIC SUPPORT
• Periodical Counseling
• MOOCs-NPTEL-Certification Courses.
• Value Added Courses
FACULTY EVALUATION
Faculty feedback &
Corrective Actions
Student Exit Survey
STUDENT EVALUATON
Internal Assessments
End semester examination
PROJETCS/ INDUSTRY SUPPORT
• Industrial visit
• Internship
• MOU’s
• Mini Project and Project
03
01
04
02 05
06
TEACHING LEARNING PROCESS
Faculty
Higher Semester
Course
Allocation
Teaching
Area Of
Specialization
Course
Registration
Attainment
Calculation
Assessment
Attendance
9/2/2021 13
CRITERIA 2

Program
Outcomes and
Specific Outcomes
 Chalk and Talk
 Technical Quiz
 Video presentation
 Flipped Class room
 Role play
 Real life Examples &
Practical Demonstration
INFORMATION &
COMMUNICATIONS
TECHNOLOGIES (ICT)
INSTRUCTION
DELIVERY
VARIOUS INSTRUCTIONAL METHODS
MY CAMU
LEARNING OUTSIDE THE
CLASSROOM
PROFESSIONAL CLUB ACTIVITIES
 Lesson Plan
 PPT
 NPTEL Videos
 Topic Related Videos
 Online Classes
 Zoom Platform
 Course notes
 E- Tutorial( Learning Management
System)
 2 marks Q & A
 Previous year question papers
 Assignment
 Seminars & Workshops
 Value Added Courses
 Content beyond syllabus
 Internship/Case Study
 In-Plant Training
 Industrial Visit
 IOT Club
 Innovators club
 Entrepreneurship
Development Cell
STUDENT
CENTRIC
LEARNING
ACADEMIC CALENDAR
9/2/2021 14
CRITERIA 2

BEST PRACTICES GOAL
Think-pair-share
Enhance the overall comprehension of students and
allows teachers to present their content in a dynamic
way .
Minute Paper
Get a immediate feedback about the understanding of
the topic which are discussed in the same
class/periods.
Question-and
Answer
Technique
Motivate students for self-study and group study.
Short
Cases/Scenarios
Develop skills in interpersonal communication and in
expressing views in a clear and concise manner
Brainstorming
improve verbal skills for effective public speaking.
TEACHING AND LEARNING METHODS
Technical Quiz
Smart Class Room
My Camu Video presentation
Online Class
Kahoot Quiz
9/2/2021 15
CRITERIA 2

METHOD OF
CATEGORIZATION
ACTION TAKEN
=>8 GPA in Previous
semester
 Encouraged to do online courses and Journal Publications.
 Encouraged to participate in the National & International
workshops, seminars, and conferences.
 Motivated to participate in the Hackathons events.
 Conducted Technical Talk in the department.
<=6 GPA is Previous
semester
 Encouraged the students to secure good marks in the
Semester Papers.
 Motivated them through counselling.
 Mentor-Mentee System to understand the difficulties of
student’s personal and professional problems and to provide
necessary guidance.
 Special Coaching classes are scheduled and conducted.
METHODOLOGIES TO SUPPORT SLOW & FAST LEARNERS
Identification Process
Inputs from Mentors,
Internal test Performances,
Previous End Semester
Results
Identification of Slow
Learner
(Scored Less Than 60%)
Online Materials
Seminars
Conferences
Journal Publications
Placement in Reputed
firms
Best Student Awards
To aspire for Higher
Studies
Mentoring
Counseling &
Motivation
Special Coaching Class
Remedial Class
Identification of fast
Learner
(Scored Greater Than 80%)
Winner of Hack Quest Contest
Best Student Awards
9/2/2021 16
CRITERIA 2

End Semester
Examination
CO ASSESSMENT
THEORY COURSES
Continuous Internal
Assessment
CIA1 CIA2
PRACTICAL PROJECT
Review I Review II
Internal External
Review III Viva-Voce
Assignments
ESPE
MPE
Course Exit
Survey
Course Exit
Survey
COURSE OUTCOME ASSESSMENT FRAMEWORK
9/2/2021 17
CRITERIA 3

9/2/2021 18
DIRECT ASSESSMENT TOOL FOR THEORY COURSE
COURSE OUTCOME ASSESSMENT FRAMEWORK
THEORY PRACTICAL
COURSE
OUTCOME
ESE
70 %
CIA
30 %
Internal Review
Marks
External Review
Marks
CIA 1
CIA 2
ASSIGNMENTS
ESE
ASSESSMENT
TOOLS
CO 1 CO 2 CO 3 CO 4 CO 5 CO 6
CIA 1 50% 50%
CIA 2 50 % 50 %
Assignment 1 100 %
Assignment 2 100 %
ESE 100% 100% 100% 100% 100% 100%
TOTAL 30% (CIA) + 70% (ESE)
DIRECT ASSESSMENT TOOL FOR PROJECT PHASE
ASSESSMENT TOOLS CO 1 CO 2 CO 3
Internal Review Marks 50% 50% 50%
External Review Marks 50% 50% 50%
TOTAL 100% 100% 100%
DIRECT ASSESSMENT TOOL FOR PRACTICAL COURSE
ASSESSMENT
TOOLS
CO 1 CO 2 CO 3 CO 4 CO 5 CO 6
Model Practical
Exam
50% 50% 50% 50% 50% 50%
End Sem Practical
Exam
50% 50% 50% 50% 50% 50%
TOTAL 100% 100% 100% 100% 100% 100%

CO1 Outline the features of different lifecycle models.
CO2
Understand the principle involved in gathering and
validating software requirements
CO3
Use the suitable model of analysis for requirements and
arrive at an appropriate software design.
CO4
Study the quality assurance procedures during software
development
CO5
Comprehend the software project management and
software maintenance practices.
CO6 Demonstrate the Concept of Software Testing.
COURSE OUTCOME
BCS501- SOFTWARE ENGINEERING
9/2/2021 19
CRITERIA 3

Items
Marks
(Maximum)
Conduction of
Experiments
10
Record 10
Viva 10
Model Practical 10
Internal Total 40
End Semester
Exam
60
TOTAL 100
PRACTICAL
THEORY
Components For
Internal Assessment
Duration Of The
Test In Minutes.
Marks
(Max)
CIA – I 90 10
CIA – II 90 10
Seminar/
Assignment/
OnlineTest/
Quiz
- 10
Internal Total 30
End Semester Exam 70
TOTAL 100
RUBRICS FOR CO ATTAINMENT – R 2015
ASSESSMENT METHODS
Course Code -
Name
BCS501 -Software Engineering
Year & Semester III & V
Direct Assessment Evaluation – Theory Courses
Assessment Tool Assessment Weightage
Internal
Assessment
Assignment 1
30%
CIA 1
Assignment 2
CIA 2
END – SEMESTER EXAMINATION 70%
9/2/2021 20
CRITERIA 3

ITEM 2020 – 21 2019-20 2018-19
Sanctioned Intake 1140 1140 1140
Total Number Of
Students Admitted In
First Year
1128 1133 824
Lateral Entry - 16
TOTAL 1128 1133 840
ENROLMENT RATIO : 90.82%
ENROLLMENT RATIO
2020 – 21 2019-20 2018-19
1140 1140
1140
1128
1133
824
16 5
CRITERIA 4
9/2/2021 21

B.TECH - COMPUTER SCIENCE AND ENGINEERING – SEM V – ASSIGNMENT1
S.NO REG NO. NAME OF THE STUDENT Q1
CO
ATTAINMENT
BTL
ATTAINMENT
COURSE OUTCOMES CO-3 CO-3 BTL3
BTL TOTAL BTL2
MAX MARKS
GENERAL
PRESENTATION
VARIETY
OF
SOURCES
DEPTH
AND
BREADTH
IDEA
GENERATION
PEER
EVALUATION
17 10 10 % 10 %
1 U15CS001 Abhijeet Kumar 4 4 4 4 1 17 10 10 100 10 100
2 U15CS002 Abhijit Kumar Gupta 2 4 4 4 1 15 9 9 88.3 9 88.3
3 U15CS003 Abhishek Kumar Singh 3 4 3 3 1 14 8 8 82.4 8 82.4
4 U15CS004 Allu Sai Siva Priyanka Naidu 4 3 4 4 1 16 9 9 94.2 9 94.2
57 U15CS060 Hari Haran M 4 4 4 3 1 16 9 9 94.2 9 94.2
58 U15CS061 Hasthi Ruchitha 4 4 4 3 1 16 9 9 94.2 9 94.2
59 U15CS062 Hema Narayanan R 4 4 4 3 1 16 9 9 94.2 9 94.2
60 U15CS063 Inaparthi Raghava 4 4 4 4 1 17 10 10 100 10 100
AVERAGE CO ATTAINMENT ( %) 87.2 87.2
ASSIGNMENT 1 (Attainment) - BCS501 SOFTWARE ENGINEERING C
9/2/2021 22

CO
ATTAINMENT
(%)
CQI REMARKS REMEDIAL MEASURE
CO3 87.2
Assessment was done through
submission of assignment and
hence target was fixed as 85%.
Enough of content / relevant
materials was not submitted
by students.
Motivation was given to students to
study basics and encouraged them to
prepare well for next exam.
Target 85
Total Number Of Students 60
No. Of Students Attained CO Based On Target 60
Attainment % Based On Target 85
AVERAGE ATTAINMENT 87.2
BTL Attainment 87
Assignment – I CO ATTAINMENT - BCS501 SOFTWARE ENGINEERING CRITERIA 3
9/2/2021 23
85
87.2
Attainment % based on
target
Average Attainment
87
BTL Attainment

B.TECH - COMPUTER SCIENCE AND ENGINEERING – SEM V - TEST - 1
S.NO REG NO
NAME OF THE
STUDENT
Q1 Q2 Q3 Q4 Q5 Q6 Q7
CO
ATTAINMENT
CO
ATTAINMENT
BTL
ATTAINMENT
BTL
ATTAINMENT
BTL
ATTAINMENT
BTL
ATTAINMENT
COURSE OUTCOMES CO-1 CO-1 CO-2 CO-2 CO-2 CO-1 CO-1 CO-1 CO-2 BTL1 BTL2 BTL4 BTL5
BTL BTL1 BTL2 BTL2 BTL2 BTL4 BTL5 BTL5 TOTAL
20 % 10 % 2 % 6 % 6 % 16 %
MAX MARKS 2 2 2 2 6 6 10 30
1 U15CS001 Abhijeet Kumar 1 2 2 2 5 5 8 25 16 80 9 90 1 50 6 100 5 83.4 13 81.3
2 U15CS002 Abhijit Kumar Gupta - 2 1 2 5 5 7 22 14 70 8 80 - - 5 83.4 5 83.4 12 75
3 U15CS003
Abhishek Kumar
Singh
2 1 2 2 4 3 7 21 13 65 8 80 2 100 5 83.4 4 66.7 10 62.5
4 U15CS004
Allu Sai Siva Priyanka
Naidu
2 2 1 2 2.5 6 9 24.5 19 95 5.5 55 2 100 5 83.4 2.5 41.7 15 93.8
57 U15CS060 Hari Haran M 2 2 2 2 6 5 9 28 18 90 10 100 2 100 6 100 6 100 14 87.5
58 U15CS061 Hasthi Ruchitha 2 2 2 2 6 5 9 28 18 90 10 100 2 100 6 100 6 100 14 87.5
59 U15CS062 Hema Narayanan R 2 2 2 2 6 5 9 28 18 90 10 100 2 100 6 100 6 100 14 87.5
60 U15CS063 Inaparthi Raghava 2 2 2 2 6 5 9 28 18 90 10 100 2 100 6 100 6 100 14 87.5
AVERAGE CO ATTAINMENT
( %)
85.17 88.59 95.00 95.02 82.67 83.36
INTERNAL ASSESSMENT 1 - BCS501 SOFTWARE ENGINEERING CRITERIA 3
9/2/2021 24

CO
ATTAINMENT
( %)
CQI REMARKS REMEDIAL MEASURE
CO-1 85.17
1. Various case studies was discussed in
the class.
2. Students were able to understand the
scenario but many of them could not
explain or identify properly
1. Students were given enough of
lab sessions to practice.
2. NPTEL video sessions was run
through to enhance their
knowledge.
CO-2 88.59
Concept based study was
explained in the class.
1. Students were given enough of
lab sessions to practice.
2. NPTEL video sessions was run
through to enhance their
knowledge.
CO1 - Target 85
CO2 - Target 85
Total Number Of Students 60
No. Of Students Attained CO1 Based On Target 60
No. Of Students Attained CO2 Based On Target 60
CO1 - Attainment % Based On Target 85.00
AVERAGE CO-1 ATTAINMENT 85.17
CO2 - Attainment % Based On Target 85.00
AVERAGE CO-2 ATTAINMENT 88.59
BTL-1 Attainment 95.00
CO ATTAINMENT - BCS501 SOFTWARE ENGINEERING
95.00 95.02
82.67 83.36
BTL-1
Attainment
BTL-2
Attainment
BTL-4
Attainment
BTL-5
Attainment
BTL
Attainment
(%)
BTL ATTAINMENT
CRITERIA 3
9/2/2021 25
85.00
85.17 85.00
88.59
CO1 -
Attainment %
based on
target
Average CO-1
Attainment
CO2 -
Attainment %
based on
target
Average CO-2
Attainment

COURSE CODE : BCS501 COURSE NAME : SOFTWARE ENGINEERING SEM : V
ATTAINMENT - CO1 ATTAINMENT - CO2
S.NO REG NO. NAME OF THE STUDENT CIA-I CIA (30%) ESE(70%)
CO1
ATTAINMENT
CIA-I CIA (30%) ESE(70%)
CO2
ATTAINMENT
1 U15CS001 Abhijeet Kumar 80 24 59 65.4 90 27 64 71.6
2 U15CS002 Abhijit Kumar Gupta 70 21 91 84.7 80 24 77 78.1
3 U15CS003 Abhishek Kumar Singh 65 20 86 80.0 80 24 73 75.0
4 U15CS004 Allu Sai Siva Priyanka Naidu 95 29 77 82.6 55 17 59 57.9
57 U15CS060 Hari Haran M 90 27 86 87.5 100 30 73 81.0
58 U15CS061 Hasthi Ruchitha 90 27 46 58.9 100 30 59 71.4
59 U15CS062 Hema Narayanan R 90 27 68 74.7 100 30 50 65.0
60 U15CS063 Inaparthi Raghava 90 27 68 74.7 100 30 59 71.4
AVERAGE ATTAINMENT 85 75.3
NO. OF STUDENTS ATTAINED TARGET 60 60
ATTAINMENT % BASED ON TARGET 85.17 88.59
CO1 & CO2 ATTAINMENT CRITERIA 3
9/2/2021 26

COURSE CODE : BCS501 COURSE NAME : SOFTWARE ENGINEERING
SEM : V
COs
TARGET
DIRECT
ATTAINMENT
INDIRECT
ATTAINMENT
OVER ALL ATTAINMENT
(70%DIRECT +
30%INDIRECT)
CO1 85 86 84 85.40
CO2 85 83 89 84.80
CO3 85 88 87 87.70
CO4 85 89 82 86.90
CO5 85 80 90 83.00
CO6 85 81 89 83.40
85.00 84.50 86.83 85.20
CO ATTAINMENT SUMMARY CRITERIA 3
9/2/2021 27
85.40
84.80
87.70
86.90
83.00
83.40
85.20

CO ATTAINMENT
S.NO. REG NO. NAME OF THE STUDENT CO1 CO2 CO3 CO4 CO5 CO6
1 U15CS001 Abhijeet Kumar 65.37 71.59 78.79 77.05 77.29 77.29
2 U15CS002 Abhijit Kumar Gupta 84.70 78.11 78.99 82.50 82.50 82.50
3 U15CS003 Abhishek Kumar Singh 79.98 74.96 69.73 64.45 70.51 70.51
4 U15CS004 Allu Sai Siva Priyanka Naidu 82.61 57.87 74.53 76.27 73.27 73.27
57 U15CS060 Hari Haran M 87.48 80.96 56.67 70.24 72.25 72.25
58 U15CS061 Hasthi Ruchitha 58.85 71.37 - 74.77 78.55 78.55
59 U15CS062 Hema Narayanan R 74.74 65.00 - 73.27 67.51 67.51
60 U15CS063 Inaparthi Raghava 74.74 71.37 - 70.04 68.54 68.54
OVERALL CO ATTAINMENT CRITERIA 3
9/2/2021 28

MID-SEM SURVEY
COs NO. OF STUDENTS EXCELLENT VERY GOOD GOOD SATISFACTORY POOR TOTAL
Attainment Level of CO1 60 57.41 31.48 5.56 3.70 1.85 87.78
Attainment Level of CO2 60 62.96 33.33 3.70 - - 91.84
COURSE EXIT SURVEY
COs NO. OF STUDENTS EXCELLENT VERY GOOD GOOD SATISFACTORY POOR TOTAL
Attainment Level of CO1 60 64.81 31.48 1.85 1.85 - 91.84
MID-SEM SURVEY & COURSE EXIT SURVEY CRITERIA 3
9/2/2021 29

FINAL COURSE EXIT SURVEY
COs NO OF STUDENTS MES CES
FINAL CES
(30% MES + 70% CES)
Attainment Level of CO1 60 87.78 91.84 90.62
Attainment Level of CO2 60 91.84 91.11 91.33
Attainment Level of CO3 60 91.49 91.49
FINAL COURSE EXIT SURVEY CRITERIA 3
9/2/2021 30

MARK SHEET
S.No REG NO.
Q
1
Q
2
Q
3
Q
4
Q
5
Q
6
Q
7
Q
8
Q
9
Q
10
Q
11
Q
12
Q
13
Q
14
Q
15
Q
16
Q
17
Q
18
Q
19
Q
20
Q
21
Q
22
Q
23
Q
24
Q
25
Q
26
Q
27
Q
28
Q
29
Q
30
Q
31
Q
32
Q
33
Q
34
Q
35
Q
36
Q
37
Q
38
Q
39
Q
40
Q
41
Q
42
Q
43
Q
44
TOTAl
CO-NUMBER 1 1 1 1 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 1 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 1 2 3 3
BTL-NUMBER 1 1 1 1 2 1 2 1 2 2 2 1 1 1 2 2 2 2 1 2 2 2 2 2 2 3 3 2 3 2 2 3 2 3 3 2 2 3 3 2 5 6 6 6
MAX MARKS 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 10 10 100
1 U15CS001 Abhijeet Kumar 1 1 - 1 - 1 1 1 1 - - 1 1 1 1 1 1 1 1 1 2 2 2 - 2 2 2 - 2 - - 2 2 2 - 2 2 2 - 2 4 5 6 7 66
2 U15CS002 Abhijit Kumar Gupta 1 1 - 1 - 1 1 - - - - 1 - 1 1 1 1 1 1 - 2 2 2 2 2 2 2 - 2 - - 2 2 2 - 2 2 2 - 2 9 9 9 10 79
3 U15CS003 Abhishek Kumar Singh 1 1 - 1 - 1 1 - 1 - - 1 1 1 1 1 1 1 1 - 2 2 2 2 2 2 2 - 2 - - 2 2 2 - 2 2 2 - 2 8 8 5 6 71
4 U15CS004
Allu Sai Siva Priyanka
Naidu
1 1 - 1 - 1 1 - 1 - - 1 1 1 1 1 1 1 1 - 2 2 2 2 2 2 2 - 2 - - 2 2 2 - 2 2 2 - 2 6 5 6 6 67
57 U15CS060 Hari Haran M 1 1 - 1 - 1 1 1 1 - - 1 - 1 1 1 1 1 1 - 2 2 2 2 2 2 2 - 2 - - 2 2 2 - 2 2 2 - - 8 7 7 6 70
58 U15CS061 Hasthi Ruchitha 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 2 1 2 2 1 1 1 2 2 2 2 - 2 2 2 2 2 2 2 2 2 2 - - - - 63
59 U15CS062 Hema Narayanan R 1 - 1 - - 1 1 - 1 1 - 1 1 1 1 1 1 1 1 1 2 2 - - - 2 2 - 2 - - 2 - 2 - 2 2 2 - - 9 5 6 7 62
60 U15CS063 Inaparthi Raghava 1 1 - 1 - 1 1 - - - - 1 - 1 1 1 1 1 1 - 2 2 2 2 2 2 2 0 2 - - 2 2 2 - 2 2 2 - - 4 5 6 5 60
ATTAINMENT OF END SEMESTER EXAMINATION CRITERIA 3
9/2/2021 31

COURSE
COURSE
OUTCOME
PROGRAMME OUTCOMES
PROGRAMME SPECIFIC
OUTCOMES
PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2 PSO3
BCS501 SOFTWARE
ENGINEERING
CO-1 0.3 - 0.6 0.3 0.3 0.1 - - - - - - 0.3 - -
CO-2 0.6 0.6 0.3 - - 0.3 - - - - - - - - -
CO-3 0.3 0.3 0.6 - 0.3 - - - - - 0.3 - 0.3 - -
CO-4 - 0.6 0.3 0.6 - - - - - - - - 0.6 - -
CO-5 0.3 0.3 - 0.1 - 0.6 - - - - - - - - -
CO-6 - - 0.3 0.6 0.3 0.3 - - - - - - - - -
Strongly Mapped COs Count 0 2 3 2 3 0 0 1 3 1 2 2 1 1 2
Moderately Mapped COs Count 2 2 1 1 1 2 0 2 1 2 1 1 1 2 0
Slightly Mapped COs Count 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
CO-PO MAPPING (ARTICULATION MATRIX) CRITERIA 3
9/2/2021 32

COURSE
OUTCOME
CO
ATTAINMENT
PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2 PSO3 PSO1 PSO2 PSO3
CO-1 77.36 23.21 46.41 46.41 46.41 46.41 23.21 - 23.21 46.41 23.21 46.41 46.41 23.21 23.21 46.41 27.76 - -
CO-2 43.73 - 26.24 - - 26.24 - - - - - - - - 13.12 4.37 - - -
CO-3 58.95 - - 35.37 35.37 - - - 35.37 17.68 35.37 17.68 17.68 35.37 35.37 35.37 20.13 - -
CO-4 54.17 - - - - 16.25 - - - - - - - - - - 40.27 - -
CO-5 55.29 16.59 16.59 16.59 16.59 - 16.59 - 16.59 33.17 - 33.17 - - - - - - -
CO-6 55.23 - 16.57 33.14 - 33.14 - - 0.00- 33.14 16.57 - 33.14 - - - - - -
PO ATTAINMENT CRITERIA 3
9/2/2021 33

YEAR OF
ENTRY
N1 + N2 + N3
SUCCESSFULLY GRADUATED WITHOUT
BACKLOGS
I YEAR II YEAR III YEAR IV YEAR
2020-21 1128(1128+0) 1003 - - -
2019-20 1133 (1133+0+0) 994 979 - -
2018-19 845 (824+16+5) 763 762 751 -
2017-18 718 (698+8+12) 676 673 662 653
ITEM 2020-21 2019 –20 2018 – 19 2017 – 18
No. of students 1128 1133 845 718
Graduated
without backlogs
1003 979 751 653
Success Index (SI) 0.88 0.86 0.89 0.91
Average Success
Index
0.89
ITEM 2020-21 2019 – 20 2018 – 19 2017-18
No. of students 1128 1133 845 718
Graduated with
backlogs
125 154 94 65
Success Index (SI) 0.11 0.14 0.11 0.09
Average Success
Index
0.1 1
YEAR I YEAR II YEAR III YEAR IV YEAR
2020-21 125 - - -
2019-20 139 154 - -
2018-19 61 83 94 -
2017-18 22 45 56 65
SUCCESS RATE WITH BACKLOG
SUCCESS RATE WITHOUT BACKLOG
SUCCESS RATE IN THE STIPULATED PERIOD CRITERIA 4
9/2/2021 34

ITEM 2017-21 2016-20 2015-19
Total No. of Students 720 240 240
No. of Students placed 637 212 203
No. of Students to higher
studies
38 15 23
No. of Students turned
entrepreneur
- 8 14
PLACEMENT , HIGHER STUDIES AND ENTREPRENEURSHIP CRITERIA 4
9/2/2021 35

PROFESSIONAL SOCIETIES ESTABLISHING YEAR
Computer Society of India (CSI) December 2012
Internet of Things Club (IOT) August 2017
Institution of Engineering
Technology (IET)
December 2018
Indian Society for Technical
Education (ISTE)
March 2021
PROFESSIONAL SOCIETIES
PROFESSIONAL
SOCIETIES
NAME OF THE MEMBER
MEMBERSHIP
NUMBER
CSI Dr.K.P.Kalliyamurthe N1186603
CSI Dr.Rajabhushanam Cheruki 10174068
IET
Dr.K.P.Kalliyamurthe 1100745921
Dr. S.Nedunchellian 1100745920
ISTE
Dr.K.P.Kalliyamurthe LM101531
ISTE
Ms.N.Raji LM 58876
ISTE
Ms.K.AnitaDavamani LM77473
ISTE Ms.E.Srividhya LM125503
ISTE Ms.R.Jagadeeswari LM86835
ISTE Ms.G.Umarani Srikanth LM32118
ISTE Ms.M.K.Vidhyalakshmi LM06514
CRITERIA 4
9/2/2021 36
CLUB ACTIVITIES

PROFESSIONAL SOCIETIES - EVENTS
NAME OF
PROFESSIONAL
SOCIETIES
ACADEMIC YEAR TITLE
ORGANIZED
DATE
NUMBER OF
PARTICIPANTS
IET 2019-20
Workshop on Machine Learning
16-01-2020
to
18-01-2020
167
Seminar on Artificial Intelligence and
Expert Systems
08-07-2019 200
CSI 2018-19
Workshop On Microwave Remote Sensing
And Agriculture
28-03-2019 180
Workshop on Internet of Things(IoT) Using
Arduino
14/11/2018
to
15/11/2018
212
Technical Seminar on An Introduction And
New Trends, Research Scope In Control
Systems
24-09-18 200
CSI 2017-18
Technical Seminar on Ethical Hacking 23/02/2018 217
Technical Seminar on Cloud Computing 27/12/2017 170
Technical Seminar On Cyber Physical
System
25-09-2017 120
CRITERIA 4
9/2/2021 37

IoT CLUB EVENTS
NAME OF THE
WORKSHOP/SEMINAR/FDP
RESOURCE PERSON DATE
IOT Club Inauguration
Mr. M.Senthil Kumar,
Project Director, ITEnabled Service
19-07-2017
Workshop on
Pythonprogramming
Mr. Bharath Kumar
Dass, Infosys Pvt Ltd,
Chennai 13-09-2017
Seminar - Artificial Intelligenceand
expert system
Dr. B.Lavanya,
Professor, University of
Madras, Chennai
05-10-2017
Workshop on Smart IrrigationUsing
IOT
Dr .Persis Urbana Ivy,
Professor and R&D
Incharge,Manakula
Vinayaga Inst. Of
Technology, Pondicherry
02-02-2018
Workshop on IOT (Batch 01)
Mr.Vivek Vasan
Chief Technical Officer,
ARIOT, Chennai
14-03-2019
to
15-03-2019
Mr.Vivek Vasan
Chief Technical Officer,
ARIOT, Chennai
29-03-2019
to
30-03-2019
Faculty Development Program on
Machine Learning & Deep Learning
Techniques
Dr.Vijayarajeswaran,
Managing Director,
VI Micro System PVT Ltd,Chennai
12-06-2019
to
14-06-2019
CRITERIA 4
9/2/2021 38

NAME OF THE WORKSHOP RESOURCE PERSON DATE
Seminar on IOT based smart
sensor network
Dr. Persis Urbana Ivy,
Professor and R&D Incharge,
ManakulaVinayaga Inst. of Technology, Pondicherry
23-01-2020
Webinar on Integration of IOTand
Cloud Computing
Dr. Rajeshwari Mukesh,
HOD,School of Computing Sciences,
Hindustan Institute of Technology &Science, Chennai
15-04-2020
Mr. Vivek Vasan
Chief Technical Officer,ARIOT, Chennai
14-03-2019
to
15-03-2019
Mr. Vivek Vasan
Chief Technical Officer,ARIOT, Chennai
29-03-2019
to
30-03-2019
Faculty Development Program on
Machine Learning & Deep Learning
Techniques
Dr. Vijayarajeswaran,Managing Director,
VI Micro System PVT Ltd,Chennai
12-06-2019
to
14-06-2019
Seminar on IOT based smart
sensor network
Dr.PersisUlbana Ivy,
Professor and R&D Incharge,
ManakulaVinayaga Inst. of Technology, Pondicherry
23-01-2020
Webinar on Integration of IOTand
Cloud Computing
Dr. Rajeshwari Mukesh,
HOD,School of Computing Sciences,
Hindustan Institute ofTechnology &Science, Chennai
15-04-2020
IoT CLUB EVENTS CRITERIA 4
9/2/2021 39

CATEGORY NAME FREQUENCY YEAR
Newsletter TECHINFO 19B Half-Yearly 2019-2020
Newsletter TECHINFO 19A Half-Yearly 2019-2020
Magazine TECHASTRA T19 Yearly 2019-2020
Magazine CONTINUUM V18 Yearly 2018-2019
Magazine EKALAVYA 2K17 Yearly 2017-2018
PUBLICATION OF TECHNICAL MAGAZINES AND NEWSLETTERS CRITERIA 4
9/2/2021 40

ACADEMIC YEAR
No Of Students
Participated In The
Inter- Institute Events
No Of Students
Participated In
The Workshop /
Webinar
No Of Students
Participated In
The Symposium
No Of Students
Received
Awards
No Of Students
Outside The
State
2019-20 89 76 13 - 24
2018-19 89 83 6 2 33
2017-18 102 50 52 1 66
STUDENT PARTICIPATION AT OTHER INSTITUTION EVENTS CRITERIA 4
9/2/2021 41

S.NO STUDENT NAME CONFERENCE NAME PAPER TITLE YEAR
1 Mr. Shaik Nagur Basha
National E-Conference on
Unconventional Computational
Intelligence (NCUCI-2020)
Data Curation with
Deep Learning
2020
2 Mr. Pranay Reddy
Smart Parking System
Based On IoT
2020
3 Ms.B.N.Swarna Jyothi
Analyzing and Estimating the
Performance of Weka
Classifierson Significant Diseases
2020
4 Mr.Vennakula Saivarun
Review of the Use of AI
Techniques in Serious Games:
DecisionMaking
andMachineLearning
2020
5 Ms.Pothana Bhavya
Emotion Player with Music 2020
6 Mr.Abdul Sameer
Sports Fantasy 2020
STUDENT PUBLICATIONS CRITERIA 4
9/2/2021 42

STUDENT FACULTY RATIO
16%
12%
11%
9%
4%
11%
2%
4%
4%
3%
4%
2%
9%
5%
4%
Artificial Intelligence Data Science
Cyber Security Networking and Cloud
IoT Programming
Block Chain Technologies Software Engnineering
Operating System Harwares and Computer Architecture
Machine Learning Theory of Computation
Digital Forensics Comuter Vision
Digital Image Processing
FACULTY
COMPETENCY
YEAR 2020-21 2019-20 2018-19
U1.1 1140 1140 720
U1.2 1140 720 240
U1.3 720 240 240
UG 1 3000 2100 1200
P1.1 18 18 18
P1.2 18 18 18
PG 1 36 36 36
Total No. of
Students in the
Department (S)
3036 2136 1236
No. of Faculty in
the Department
(F)
203 143 83
Student Faculty
Ratio (SFR)
14.9 14.9 14.8
Average SFR SFR=(SFR1+SFR2+SFR3)/3
14.8
CRITERIA 5
9/2/2021 43

YEAR PH.D M.Tech/M.E TOTAL
2020-21 66 137 203
2019-20 46 97 143
2018-19 25 58 83
YEAR RETAINED PERCENTAGE %
2019-20 93/143 65%
2019-20 55/83 62%
2017-18 31/50 59%
AVERAGE 62 %
YEAR PROFESSOR
ASSOCIATE
PROFESSOR
ASSISTANT
PROFESSOR
2020-21 22 44 137
2019-20 16 32 95
2018-19 9 18 56
FACULTY DETAILS CRITERIA 5
9/2/2021 44
1 2 3 4 5 6
22
44
137
16
32
95
9
18
56
YEAR 2020-21 2019-20 2018-19

ACADEMIC RESEARCH
YEAR
JOURNAL CONFERENCE
TOTAL
INTERNATIONAL NATIONAL INTERNATIONAL NATIONAL
2020 450 25 120 10 605
2019 420 17 83 12 532
2018 350 8 42 9 409
CRITERIA 5
9/2/2021 45
2019-20 2018-19 2017-18
NO. OF PATENTS 31 17 1
CONSULTANCY 6 5 4
BOOKS
PUBLISHED
9 8 7
63%
35%
2%
NO. OF PATENTS
2019-20 2018-19 2017-18
40%
33%
27%
CONSULTANCY
2019-20 2018-19 2017-18
INDEX 2017-18 2018-19 2019-20
SCOPUS 277 342 354
WOS 38 45 48
SCI 23 28 35
UGC CARE 20 22 38
TOTAL 358 437 475

ACADEMIC RESEARCH CRITERIA 5
9/2/2021 46

YEAR
CONFERENCES
SEMINARS WORKSHOP WEBINARS TOTAL
INTERNATIONAL NATIONAL
2020-21 - 2 - - 24 26
2019-20 1 2 14 - 17
2018-19 2 3 14 11 - 30
2017-18 1 2 14 6 - 23
EVENTS CONDUCTED BY THE DEPARTMENT
DEPARTMENT EVENTS CRITERIA 5
9/2/2021 47

DEPARTMENT EVENTS
NATIONAL CONFERENCE ON 2017
NATIONAL CONFERENCES ON 2018
CRITERIA 5
9/2/2021 48
NATIONAL SYMPOSIUM TECHASTHRA-19
NATIONAL SYMPOSIUM TECHASTHRA-19

FACULTY PARTICIPATIONS IN FDPs / STTPs/ TRAINING ACTIVITIES
YEAR STTP FDP WORKSHOP WEBINAR
2020 51 26 75 18
2019 22 17 54 -
2018 10 10 22 -
CRITERIA 5
9/2/2021 49

Dr. D. VENKATA
SUBRAMANIAN
Database Consultant -USA
Based MNC, Chennai
bostonvenkat@gmail.com
VISITING AND ADJUNCT PROFESSORS
NAME OF THE
FACULTY
HOURS
TAKEN
MODULE
DR. D. VENKATA
SUBRAMANIAN
52 Distributed computing - VI SEM
DR.ROBERT
MASILAMANI
52
Data warehousing and Data Mining -
VI SEM
DR. VENKADESHAN 51
Grid and Cloud Computing - VII SEM
MR.RAMAN
RAGURAMAN
50
Web Technology – VII SEM
DR. MUTHUKUMARAN
MARUTHAPPA
54
Data warehousing and Data Mining -
VI SEM
DR. HOSHANG
KOLIVAND
45
Artificial Intelligence and Expert
System - VII SEM
Dr. ROBERT MASILAMAN
Former Professor & Dean,
Hindustan Institute of
Technology and Science,
Chennai.
robertmani@gmail.com
CRITERIA 5
9/2/2021 50
Dr. HOSHANG KOLIVAND
Professor, School of Computer
Science and Mathematics
Liverpool John Moores
University, Liverpool, UK
H.Kolivand@ljmu.ac.uk
Dr. VENKADESHAN
Associate Professor , IT
University of Technology and
Applied Sciences, Oman
venkadeshan.ramalingam@sh
ct.edu.om
Mr. RAMAN RAGURAMAN
Lecturer & Course Manager
School of Computing
AIMST University Malaysia
raman_raguraman@aimst.edu.
my / imklim@gmail.com
Dr. MUTHUKUMARAN
MARUTHAPPA
Professor, Faculty of Science
and Technology,
Sunway University, Malaysia
muthuma@sunway.edu.my

SYSTEM CONFIGURATION
HP RCTO 280 Pro Microtower PC,
Intel Core i3- 3.6 GHz Processor 65W ,
10 Gen, 1 TB HDD, 8GB RAM ,21 ” Inch FHD Display
SOFTWARE AVAILABILITY
 Ubuntu 4.10, Windows 10
 Turbo C++ 4.5 V.3.2.3.0
 JDK 11, PEARL
 Oracle 10g - SQL Server Management Studio
LAB UTILIZATION
ODD SEMESTER
 U18PCCS3L1-Data Structures & Algorithm Lab
 U18PCCS3L2- Object Oriented Programming Lab
EVEN SEMESTER
 U18PCCS4L1 – Operating System Lab
 U18PCCS4L2 – Design and Analysis of Algorithm Lab
 U18PCCS4L3 – Database Management System Lab
TEACHING STAFF
Mr. N. Nithiyanandam(Co-Ordinator), Mrs.Jenita Christy
Mr. Prabhusankar , Mr. A V Allin Geo , Mr. Aravind,
Mrs. J. Ranganayaki, Mrs. D. Jeyapriya ,
Ms. T. Selva Banupriya , Ms. Jeyapriyanka
NON -TEACHING STAFF Ms .Y. Mayavathi(Programmer)
COMPUTER LABORATORY - I
ROOM NO 101
CRITERIA 6
9/2/2021 51

COMPUTER LABORATORY - II
HP RCTO 280 Pro Microtower PC,
Intel Core i3-3.6 GHz Processor 65W , 10 Gen,
1 TB HDD, 8GB RAM ,21.0” Inch FHD Display
LAB UTILIZATION
ODD SEMESTER
 BCS5L1 – Networking Lab
 BCS5L2 – Software Engineering Lab
EVEN SEMESTER
 BCS6L1 – Data Warehousing and Data Mining Lab
 BCS6L2 – C# & .Net Lab
 BCS6L3 – Programming in JAVA Lab
 BCS6P1 – Mini Project
TEACHING STAFF
Mrs. Geetha(Co-Ordinator), Mrs. Anuranjini, Mrs. R. Velvizhi,
Mrs. Narmadha, Mrs. Usha , Mrs. C. Anuradha ,
Mrs. L. Sathyapriya , Dr. Rajabhushanam , Mrs. Sushmitha
Mr. Shaik Abdul Waheed
NON -TEACHING STAFF Mr. S. Pravin( Programmer)
ROOM NO 201
 Turbo C++ 4.5 V.3.2.3.0
 NS3, OPNET
 JDK 11, Selenium
 Visual Basic 6.0
 Informatica(Free),
Weka 3.9, Rapid Miner
 Visual Studio 11.0.50
 Oracle 10g – SQL
Server
CRITERIA 6
9/2/2021 52

COMPUTER LABORATORY - III
ROOM NO 301
HP RCTO 280 Pro Microtower PC ,
Intel Core i3-3.6 GHz Processor 65W , 10 Gen,
1 TB HDD, 8GB RAM ,21.0” Inch FHD Display
LAB UTILIZATION
ODD SEMESTER
 BCS7L1 – Grid and Cloud Computing Lab
 BCS7L2 – Web Technology Lab
EVEN SEMESTER
 BCS6P1 – Mini Project
 BCS8P1 – Project Work
 Open Source Lab
 E-Magazine
TEACHING STAFF
Mr. M. Ramamoorthy,(Co-Ordinator), Mrs. Jagadeeshwari,
Mrs. K. Sathyapriya, Mrs. Asha Judi, Ms. Nivedha
NON -TEACHING STAFF Mr. P. Prahatheeswaran( Programmer)
 Turbo C++ 4.5 V.3.2.3.0
 JDK 11,
 Sales Force, Drop box
(Open Source), Virtual box
(Open Source),AWS,
Windows Azure, Cloud Sim
 Informatica (Free Trail),
Weka 3.9, Rapid Miner
 Apache, XAMPP
 Visual Studio 11.0.50
 Oracle 10g - SQL Server
Management Studio
CRITERIA 6
9/2/2021 53

MACHINE COGNITION
CENTRE OF EXCELLENCE
HARDWARE:
PC – HP Intel Core i5 Processor with 8 GB RAM ,1 TB HDD- 20 Nos.
BROAD BAND CONNECTION:
 BSNL Fiber Optic Internet connection with speed of 100 Mbps
SOFTWARE TOOLS :
CRITERIA 6
9/2/2021 54
DIGITAL FORENSIC
HARDWARE:
PC – HP Intel Core i5 Processor with 8 GB RAM ,1 TB HDD- 20 Nos.
BROAD BAND CONNECTION:
 BSNL Fibre Optic Internet connection with speed of 100 Mbps
SOFTWARE TOOLS FOR CYBER SECURITY:
Academic Year Papers Published
2017-2018 06
2018-2019 18
2019-2020 27
Academic Year Papers Published
2017-2018 13
2018-2019 4
2019-2020 33
 Python version 3.8 Pandas
 Scikit Learn package
 Jupyter notebook
 Keras
 Tensorflow 2.0
 OpenCV
 Kali Linux
 Crack-ng
 Maltego
 Nmap
 OpenVAS (Nessus)
 Wireshark
 Metasploit

CONTINUOUS IMPROVEMENT
PO/PSO ATTAINMENT
CALCULATED
(80% DIRECT & 20% INDIRECT)
COMPARED WITH
TARGET
ACTION PLANS
PROPOSED FOR
IMPROVEMENT
APPROVED BY
DEPARTMENT ADVISORY
COMMITTEE
IMPLEMENTED IN
SUBSEQUENT ACADEMIC
YEAR
ACTION PLAN FOR CONTINUOUS IMPROVEMENT
CONSTITUTE ACADEMIC AUDIT
TEAM BY IQAC
PLANNING OF ACADEMIC AUDIT
CONDUCT OF ACADEMIC AUDIT
COURSE FILE
CO,PO,PSO ATTAINMENT,
LABORATORY FILES,
RESULT ANALYSIS ,BOS
FILES,PLACEMENT,FDP
EXTERNAL AUDIT
INTERNAL AUDIT
REPORT
SUBMISSION TO
IQAC
CORRECTIVE ACTION TAKEN
AUDIT
FINDINGS –IF
ANY
CRITERIA 7
9/2/2021 55

Actions Taken Based On The Results Of Evaluation Of Each Of The POs And PSOs-2020-21
CONTINUOUS IMPROVEMENT
POS TARGET LEVEL ATTAINMENT LEVEL OBSERVATIONS
PO1 90 90
Target achieved
PO2 90 92
Target achieved
PO3 90 93 Target achieved
PO7 90 91 Target achieved.
ACTION TAKEN
1.Encouraged students to take up socio-economic based activities.
2.Conducted project exhibit as a part of association activity and awarded projects with a environmental concern.
3.NSS and YRC volunteers are appreciated and motivated to give seminar relevant to environmental studies, health, safety, legal and
cultural issues and the consequent responsibilities relates to the professional engineering practice.
PO8
85
90 Target achieved
PO12 85
92 Target achieved
CRITERIA 7
9/2/2021 56

OUTCOME BASED EDUCATION
Outcome Based Education is a student-centric teaching and learning methodology in which the
course delivery, assessment are planned to achieve stated objectives and outcomes.
VISION AND MISSION
COURSE 1
CO1,CO2,CO3,
CO4,CO5,CO6
PROGRAM EDUCATIONAL
OBJECTIVES(PEO)
PROGRAM OUTCOMES(PO)
GRADUATE
ATTRIBUTES
PROGRAM SPECIFIC
OUTCOMES(PSO)
OBE
(EDUCATION)
OBC
(CURRICULUM)
OBTL
(TEACHING &
LEARNING)
OBA
(ASSESSMENT)
COURSE 3
CO1,CO2,CO3,
CO4,CO5,CO6
COURSE 4
CO1,CO2,CO3,
CO4,CO5,CO6
COURSE 5
CO1,CO2,CO3,
CO4,CO5,CO6
COURSE n
CO1,CO2,CO3,
CO4,CO5,CO6
COURSE 2
CO1,CO2,CO3,
CO4,CO5,CO6
……
C
9/2/2021 57

 POs give useful guidance at the program level for the curriculum design, delivery and assessment of
student learning .
 They represent fairly high –level generic goals that are not directly measurable.
 Real observability and measurability of the POs at course level is very difficult.
 To connect high-level learning outcomes (POs) with course content, Course outcomes and
assessment, there is a necessity to bring further clarity and specificity to the Program Outcomes.
 This can be achieved through the following two-step process of Identifying Competencies and
Performance Indicators(PI).
TWO STEP PROCESS FOR BRINGING CLARITY TO POs
9/2/2021 58

PROGRAM
OUTCOMES
PO
COMPETENCIES
TO BE ATTAINED
CA
PERFORMANCE
INDICATORS
PI
ASSESSMENT
PROGRAM
OUTCOME-1
COMPETENCY
1.1
COMPETENCY
1.2
COMPETENCY
1.3
PI 1.1.1
PI 1.1.3
PI 1.3.2
PI 1.1.2
PI 1.2.1
PI 1.3.1
PI 1.2.1
PI 1.3.3
CI
A
&ESE
QUESTIONS,
PROJECT/LAB
,
ASSESSMENT
RUBRICS
The assessment of Cos for all the courses is designed by connecting assessment questions (used in
various assessment tools) to the PIs
CONNECTING POs TO ASSESSMENT
9/2/2021 59

9/2/2021 60
COMPETENCY INDICATORS
PO 1.1
Demonstrate competence in mathematical
modelling
PO 1.1.1
Apply the knowledge of discrete structures, linear algebra,
statistics and numerical techniques to solve problems
PO 1.1.2
Apply the concepts of probability, statistics and queuing theory in
modeling of computer-based system, data and network protocols.
PO 1.2 Demonstrate competence in basic sciences PO 1.2.1 Apply laws of natural science to an engineering problem
PO 1.3
Demonstrate competence in
engineering fundamentals
PO 1.3.1 Apply engineering fundamentals
PO 1.4
Demonstrate competence in
specialized engineering knowledge
to the program
PO 1.4.1
Apply theory and principles of computer science and
engineering to solve an engineering problem
PO 1: Engineering knowledge:
Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering
specialization for the solution of complex engineering problems.
CONNECTING POs TO ASSESSMENT

ASSESSMENT PLANNING
While using Bloom’s Taxonomy framework in planning and designing of assessment of student learning,
the following needs to be considered
CREATE
LEARNING LEVELS
EVALUATE
ANALYZE
APPLY
REMEMBER
UNDERSTAND
ASSESSED THROUGH
 Assignment
 Mini Project
 Professional Training
 Capstone Project
Fixed Hour Examinations
(CIA & ESE )
C
9/2/2021 61

9/2/2021 62
EMBEDDING OUTCOME BASED EDUCATION IN TO B.Tech- CSE
 OBE is implemented through three stages
 Design of Curriculum
 Teaching Learning Process
 Assessments
 BTech (CSE) curriculum is derived through,
 A defined process for curriculum development
 Well Balanced
 Structure of the Curriculum
 In accordance with the Regulations of Statutory Councils and the university
 Program Specific Outcomes
 Uniqueness of BTech (CSE)

9/2/2021 63
PLAN THE WORK
Right before, we start to teach,
 Lesson plan – along with a clear understanding of Weightage
of each CO in a course.
 Blooms Levels of the COs

9/2/2021 64
Assessment process continuous along with teaching learning;
CO ATTAINMENT
Direct Attainment of Cos
 Internal Assessment Tests
 Assignments
 End Semester Examination
Indirect Attainment of Cos
 Survey
PO Attainment
ASSESSMENT PLANNING
Direct Measurement Attainments of COs
Direct Attainment of Cos
 All question papers are mapped/tagged to corresponding COs
 Project works are also assessed with rubrics mapped to Cos
 Weightage 90%
Indirect Attainment of COs
 Survey forms are collected
 Weightage 10%

PO ATTAINMENT PROCESS – R 2018
PO ATTAINMENT
INDIRECT ATTAINMENT
Po/Pso Attainment Value = (90% Of Value Obtained From Direct Po/Pso Assessment +
10% Of Value Obtained From Indirect Assessment)
DIRECT ATTAINMENT
Direct PO/PSo Assessment- CO-PO
Mapping Strength * (Average Of CO-
Related CO Attainment Value)
Indirect Assessment
(Value Obtained From Program Exit Survey)
9/2/2021 65

CO ATTAINMENT PROCESS – R 2018
CO
ATTAINMENT
DIRECT ATTAINMENT
INDIRECT ATTAINMENT
INTERNAL ASSESSMENT
(IA1,IA2, A1 ,A2, Activity Marks)
EXTERNAL ASSESSMENT
(End Semester Exam,
University Activity Marks)
INDIRECT ASSESSMENT
(Course Exit Survey)
DIRECT ATTAINMENT VALUE =
30% Of Value Obtained From Internal +
70% Of Value Obtained From External
INDIRECT ATTAINMENT VALUE
(Obtained from Course Exit Survey)
CO ATTAINMENT VALUE =
(90% Of Value Obtained From Direct
Assessment + 10% Of Value Obtained From
Indirect Assessment )
9/2/2021 66

Direct Attainment of 𝐏𝐎/𝐏𝐒𝐎 for a course
= 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝐴𝑡𝑡𝑎𝑖𝑛𝑚𝑒𝑛𝑡 𝑜𝑓 𝑟𝑒𝑙𝑒𝑣𝑎𝑛𝑡 𝐶𝑂𝑠 ∗ 𝑆𝑐𝑎𝑙𝑖𝑛𝑔 𝐹𝑎𝑐𝑡𝑜𝑟
𝐒𝐜𝐚𝐥𝐢𝐧𝐠 𝐅𝐚𝐜𝐭𝐨𝐫 =
𝑨𝒄𝒕𝒖𝒂𝒍 𝑴𝒂𝒑𝒑𝒊𝒏𝒈 𝑺𝒕𝒓𝒆𝒏𝒈𝒕𝒉
𝑴𝒂𝒙𝒊𝒎𝒖𝒎 𝒑𝒐𝒔𝒔𝒊𝒃𝒍𝒆 𝒎𝒂𝒑𝒑𝒊𝒏𝒈 𝑺𝒕𝒓𝒆𝒏𝒈𝒕𝒉
If number of sessions devoted >=40% Mapping Strength = 3
If number of sessions devoted = 25% to 40% Mapping Strength = 2
If number of sessions devoted= 5% to 25% Mapping Strength = 1
𝐃𝐢𝐫𝐞𝐜𝐭 𝐀𝐭𝐭𝐚𝐢𝐧𝐦𝐞𝐧𝐭 𝐨𝐟 𝐏𝐎 𝐟𝐨𝐫 𝐚 𝐛𝐚𝐭𝐜𝐡
=
𝐬𝐮𝐦 𝐨𝐟 𝐏𝐎/𝐏𝐒𝐎 𝐚𝐭𝐭𝐚𝐢𝐧𝐦𝐞𝐧𝐭 𝐟𝐨𝐫 𝐚𝐥𝐥 𝐜𝐨𝐮𝐫𝐬𝐞𝐬
𝐍𝐮𝐦𝐛𝐞𝐫 𝐨𝐟 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 𝐦𝐚𝐩𝐩𝐞𝐝 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞 𝐏𝐎/𝐏𝐒𝐎
∗ 100
Indirect Attainment – Program End Survey Report
Total Attainment =80% Direct attainment + 20% Indirect attainment
ATTAINMENT CALCULATION
9/2/2021 67
 Direct Attainment =30% internal attainment + 70% university
attainment – R 2015
THEORY
𝐈𝐧𝐭𝐞𝐫𝐧𝐚𝐥 𝐀𝐭𝐭𝐚𝐢𝐧𝐦𝐞𝐧𝐭 =
𝐌𝐚𝐫𝐤𝐬 𝐨𝐛𝐭𝐚𝐢𝐧𝐞𝐝 𝐢𝐧 𝐀𝐓𝟏+𝐀𝐓𝟐+𝐀𝟏+𝐀𝟐
𝐌𝐚𝐫𝐤𝐬 𝐚𝐥𝐥𝐨𝐭𝐭𝐞𝐝 𝐟𝐨𝐫 𝐀𝐓𝟏+𝐀𝐓𝟐+𝐀𝟏+𝐀𝟐
∗ 𝟏𝟎𝟎
𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐀𝐭𝐭𝐚𝐢𝐧𝐦𝐞𝐧𝐭 =
𝐌𝐚𝐫𝐤𝐬 𝐨𝐛𝐭𝐚𝐢𝐧𝐞𝐝
𝑴𝒂𝒓𝒌𝒔 𝑨𝒍𝒍𝒐𝒕𝒕𝒆𝒅
∗ 𝟏𝟎𝟎
PRACTICAL
 Direct Attainment =40% internal attainment + 60% university
attainment- R 2018
THEORY
𝐈𝐧𝐭𝐞𝐫𝐧𝐚𝐥 𝐀𝐭𝐭𝐚𝐢𝐧𝐦𝐞𝐧𝐭 =
𝐌𝐚𝐫𝐤𝐬 𝐨𝐛𝐭𝐚𝐢𝐧𝐞𝐝 𝐢𝐧 𝐀𝐓𝟏+𝐀𝐓𝟐+𝐀𝟏+𝐀𝟐
𝐌𝐚𝐫𝐤𝐬 𝐚𝐥𝐥𝐨𝐭𝐭𝐞𝐝 𝐟𝐨𝐫 𝐀𝐓𝟏+𝐀𝐓𝟐+𝐀𝟏+𝐀𝟐
∗ 𝟏𝟎𝟎
𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐀𝐭𝐭𝐚𝐢𝐧𝐦𝐞𝐧𝐭 =
𝐌𝐚𝐫𝐤𝐬 𝐨𝐛𝐭𝐚𝐢𝐧𝐞𝐝
𝑴𝒂𝒓𝒌𝒔 𝑨𝒍𝒍𝒐𝒕𝒕𝒆𝒅
∗ 𝟏𝟎𝟎
PRACTICAL
 Indirect Attainment – Course Exit Survey Report
Total Attainment =90 % Direct attainment + 10 % Indirect attainment
PO/PSO ATTAINMENT CALCULATION CO ATTAINMENT CALCULATION

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