1. Dr. Priti Srinivas Sajja
Lecture for the State level seminar organized by Shri H. J. Doshi Information Technology Institute, Jamnagar
Software Engineering
Dr. Priti Srinivas Sajja
Associate Professor
G H Patel P G Department of Computer Science and Technology
Sardar Patel University, Vallabh Vidyanagar , Gujarat
Created By Dr. Priti Srinivas Sajja

2. Introduction and Contact Information
Name: Dr Priti Srinivas Sajja
Communication:
Mobile :
URL:
Academic qualifications : Ph. D in Computer Science
Thesis title: Knowledge-Based Systems for Socio-
Economic Development
Subject area of specialization : Artificial Intelligence
Publications : 84 in International/ National Conferences,
Journals & Books
Academic position : Associate Professor
Department of Computer Science
Sardar Patel University
Vallabh Vidyanagar

3. Agent Oriented Software Engineering
Lecture Plan
Software Engineering
Architectures
Waterfall
Spiral
Iterative and Prototype
RAD
Model for KBS development
Agents
Introduction
Typologies
Multi Agent Systems
Framework
Communication between Agents
Examples of System Designs using Agents
E-Learning Agent Based Systems
Multi layer KBS
KGrid
LOR –Layered Agents Approach

4. Software and Software Engineering
Software engineering is a modeling activity.
Software engineering activity is a problem solving activity.
Software engineering is a knowledge acquisition activity.
Software engineering is a rationale driven activity.
Software is a bundle of data, data structure, comments and instructions.
Data
Data Structures
Instruction
Comments
Software Development can be carried out in ad hoc manner or systematic way (bigger project).

5. Example Instruction Data Structure Data Comments Push A
Push: Method on Stack S
Data Structure
Data
A: Primitive Data Structure (Integer)
Stack : Say S -Data Structure
Push A
//pushes an integer A to stack S
Value A
//pushes…Comments
Comments

6. that represents the highest level of abstraction.
SE Architectures
A process consisting of all the necessary activities for developing a software system
that represents the highest level of abstraction.
Popular Architectures are:
Waterfall
Spiral
Iterative and Prototype
Rapid Application Development
…..

7. Typical SE Activities Project proposal Portfolio management
Requirement gathering
Anticipation (mixed blessings)
Investigation (fact finding methods) and
Specification (decision tree, table and structured English)
Feasibility Studies
Economical
Technical
Operational
Logical Design (DFD/UML )
Physical Design
Design of output
Design of input
Design of databases, processes, data flows, control, run time procedure, security, etc.
Coding
Testing and Certification
Training, Implementation, Evaluation
Typical SE Activities

8. Requirement Acquisition
All requirements must be known.
Deliverables created for each phase are considered frozen – less flexibility.
Can give a false impression of progress.
Not iterative.
Integration at the end.
Little opportunity for customer to preview the system.
Waterfall Model
Requirement Acquisition
V & V
Design
Implementation
Verification
Maintenance
Requirements
When to use?
Requirements are very well known.
Product definition is stable.
Technology is understood.
New version of an existing product.
Porting an existing product to a new platform.

9. A variant of the waterfall that emphasizes the verification and validation of the product.
Testing of the product is planned in parallel with a corresponding phase of development.
V shaped Model
Emphasize planning for verification and validation of the product in early stages of product development.
Each deliverable must be testable.
Project management can track progress.
Easy to use.
Does not easily handle dynamic changes in requirements.
Does not contain risk analysis activities.
Excellent choice for systems requiring high reliability – hospital patient control applications.
All requirements are known.
Solution and technology are known.

10. Construct a partial implementation of a total system.
Then slowly add increased functionality.
The incremental model prioritizes requirements of the system and then implements them in groups.
Each subsequent release of the system adds function to the previous release, until all designed functionality has been implemented.
Incremental Model

11. Non Development Activities
Spiral Model
Provides early indication of insurmountable risks, without much cost.
Users see the system early because of rapid prototyping tools.
Critical high-risk functions are developed first.
Users can be closely tied to all lifecycle steps.
Early and frequent feedback from users.
Required Time
Stopping Criteria?
Non Development Activities
Complex

12. Iterative Development Model
Rapid Application Development Model
Use and Maintain
the Accepted
System
Identify an End
User's Information
Requirements
Develop
Information System
Prototypes
Revise the Prototypes
to Better Meet End
User Requirements
Prototyping
Cycle
Maintenance

13. Intelligent System Development Model
Development Round 1
(resulting in the first in house prototype)
Development Round 2
Knowledge Acquisition
Feasible Requirements Elicitation
Testing, Implementation and Training
Strategy Selection and Overall Design of KBS
Ontology Selection and Knowledge Representation
System Development and Implementation
Knowledge Engineer
ANALYSIS
DESIGN
DETAIL DESIGN
IMPLEMENTATION
Knowledge Sources and
Users
Requirements
Middleware Services
and Tools
Ontology, Reusable Component Library and Standards
Development Methodology for Knowledge Based System
Reference taken from:
Priti Srinivas Sajja and Rajendra Akerkar: “Knowledge-based systems”, Jones & Bartlett Publishers, Sudbury, MA, USA (2009)

14. Agents Agents act on behalf of users Agents are used where
Co-operation
Autonomous
Learning
Agents are used where
Expertise and resources are distributed
High complexity
Agents provide
Modular approach
Increased reusability

15. Collaborative Agent An Example of Collaborative Agent
Pilgrim Hosting System
‘Darshan’
Donation &
‘Prasad’
Ticket Reservation
Site Seeing
Accommodation Reservation
Pilgrim Information
Temple Mgt. System
Legacy system managed by temple authority
Bus Reser-vation
System
Accommodation booking, billing and administration system managed by temple authority
Accommodation Booking and Administration System
Ticket booking, cancelling and site seeing administration system managed by third party
An Example of Collaborative Agent

16. Working of a Mobile Agent
User
Optional link
Application
User’s Agent
Other Agent
An Example of Interface Agent
Interface
and Mobile Agents
Mobile
Agent
Application Process
Location
Operating Environment
Network
Working of a Mobile Agent

17. Working of an Information Agent Structure of an Intelligent Agent
Network
Working of an Information Agent
Databases
User
Receives necessary information in desired format
Information
and Intelligent Agents
Controller
Executable Tasks List
Goal and Objectives
Interface
Knowledge-Base
Inference
I/O Queue
Structure of an Intelligent Agent

18. Multi Agent System Architecture
Repository of data and knowledge
Knowledge-Base
Optional Distributed Databases
Midle Agent Services and Agent Meeting Place
Control and Presentation Services
Master Agent
Interface Agent
Information Agent
Domain Services
Domain Agent 1
Domain Agent 2
Domain Agent N …
Layered Architecture of Generic Multi Agent System
Optional link

19. Single Agent Example - ‘Parichay’
The system gives training to adult users in multi media to speak and write Gujarati alphabets, words, sentences and numbers.
The package of ‘parichay’ is accommodated in CD with auto-run facility.
The touch screen facility helps even an illiterate person to identify icons and choose appropriate actions.

20. Reference taken from
Sajja Priti Srinivas, “Parichay: An agent for adult literacy”,
Prajna, vol.14, pp (2006)
The frequent continuous development of a letter helps users to see the exact motion to write the letter.
At the end of the full letter generation, the picture representing use of the letter and pronunciation is represented to the user.

21. With a notepad facility given, user may practice any letter.
That letter written by the user is matched with the correct letter by measuring shapes and angles in terms of percentages.
If the degree of matching is low then user may ask to redraw/rewrite the letter.

22. Multi Agent System for Learning
Users
Experts
User Interface Agent
Agents
Learning Mgt.
Drills and Quizzes
Explanation
Semantic Search
& Chat
Resource Management
Question/Answer
Tutorial Path
Documentation
Distributed Databases
Local Data-Bases
Resources
Knowledge Mgt.
Meta knowledge
Conceptual system
Content knowledge
Learner’s ontology
Mail
Documents
Knowledge Discovery
Knowledge Utilization
Knowledge Management

23. Communication between Agents
Agents developed here are communicating with a tool named KQML.
Knowledge based Query Management Language.
(register
    : sender  agent_Learning_Mgt
    : receiver agent_Tutorial-Path
    : reply-with   message
    : language     common_language
    : ontology     common_ontology
    : content      “content.data” )
Action intended for the message
Agents name sharing message
Context-specific information describing the specifics of this message
Ontology of both the agents
Language of both agents

24. Some results form the System

25. Screen Designs of the System

26. Some of the results from System

27. Some of the results from System

28. New architecture on Grid Environment – Future extension
Users
Experts
User Interface Agent
Agents
Learning Mgt.
Drills and Quizzes
Explanation
Semantic Search
& Chat
Resource Management
Question/Answer
Tutorial Path
Documentation
Internet
Grid Middleware Services
Resource Management (Grid Resource Allocation Protocol-GRAM)
and
Grid FTP Replica-Location
Services
Information Discovery Services
Security Services
Distributed databases
Middleware Services and Protocols
Local Data-Bases
Resources
Knowledge Mgt.
Meta knowledge
Conceptual system
Content knowledge
Learner’s ontology
Mail
Documents
Knowledge Discovery
Knowledge Utilization
Knowledge Management

29. Towards reusable component library logic
Learning Object Repository (LOR)

30. Multi-tier KBS Accessing LOR through Fuzzy XML
Reference taken from:
Sajja Priti Srinivas, “Multi-tier knowledge-based system accessing learning object repository using fuzzy XML”, in Harrison Yang & Steve Yuen (Eds.), Handbook of Research on Practices and Outcomes in E-Learning: Issues and Trends, Chapter 28, IGI Global Book Publishing, Hershey, PA, USA (2009)

31. Thanks