Reference Books:
Basics of Software Project Management, NIIT, Prentice-Hall India, 2004 Software Project Management in Practice, Pankaj Jalote, Pearson Education, 2002
Effective Methods for software Testing William Perry Software Testing in Real World Edward Kit
SOFTWARE REQUIREMENTS
Microsoft project 2003
Subject Code
|
J030334
|
Title
|
Web Services and SOA Applications
|
Work Load Per Week
|
L:3 T:1 Lab:4
|
Practical: 4
|
Examination
|
Internal: 30 University Exam: 70
|
Practical: 50
|
Objectives
|
Make student familiar with Web Services(WS) and Service Oriented Architecture (SOA)
|
Learning Outcomes
|
Upon completion of this course, students should be able to:
-
Use Java XML API for parsing, Data Binding and Messaging
-
Understand the concept Web Service and SOAP
-
Identify the role of SOAP
-
Writing Web Services using java and WSDL
-
Relate Web Services with SOA
|
Pre-requisites
|
Web Support Technologies (J030106)
Object Oriented Programming with Java (J030109)
Distributed Programming (J030224)
|
Reference Book
| Java Web Services: up and Running, Martin Kalin, Oriely, 2009 Java SOA a Cook Book, Eben Hewitt, Oriely, 2009 Designing Web Services with the J2EE™ 1.4 Platform JAX-RPC, SOAP, and XML Technologies, Inderjeet Singh and others, Addison Wesley |
Syllabus
Lec.
Num
|
Unit Title
|
Details
|
1.
|
Introduction to Web Services
|
Web Services and SOA Overview
|
2.
|
What SOA provides and what not? Alternatives to SOA
|
3.
|
Java API for XML
|
Overview of XML Technologies
|
4.
|
Creating and Parsing XML with DOM
|
5.
|
Data Binding using JAXB, JAXB Compilation
|
6.
|
Mapping Schema types to Java, Java to XMl binding using annotations
|
7.
|
Marshaling and unmarshaling with JAXB
|
8.
|
Working with JAXB Object Modeling, In memory validation
|
Lec.
Num
|
Unit Title
|
Details
|
9.
|
The Simple Object Access Protocol (SOAP)
|
SOAP Messaging Model , SOAP Namespaces, SOAP Envelope Header and body
|
10.
|
SOAP Faults, Attachments, XML Schema, Validating Message Content, SOAP Encoding
|
11.
|
The Java APIs for SOAP Messaging (SAAJ)
|
The SAAJ Object Model, Parsing a SOAP Message, Reading Message Content
|
12.
|
Working with Namespaces, Creating a Message, Setting Message Content , Integration with the DOM and JAXP
|
13.
|
The Java API for XML Messaging (JAXM)
|
Building Low-Level Web Services , Messaging Scenarios
|
14.
|
Point-to-Point Messaging, JAXM Message Providers
|
15.
|
JAXM Servlets, Creating a SOAP Connection , Sending a Message,
|
16.
|
The Java API for XML Messaging (JAXM)
|
Building Low-Level Web Services , Messaging Scenarios
|
17.
|
Point-to-Point Messaging, JAXM Message Providers
|
18.
|
JAXM Servlets, Creating a SOAP Connection , Sending a Message,
|
19.
|
Web Services Description language (WSDL)
|
Web Services as Component-Based Software, The Need for an IDL
|
20.
|
Web Services Description Language, WSDL Information Model, The Abstract Model - Service Semantics
|
21.
|
Message Description , Messaging Styles,
|
22.
|
The Concrete Model - Ports, Services, Locations
|
23.
|
Extending WSDL - Bindings , Service Description
|
24.
|
Java API for XML Based RPC
|
The Java Web Services Architecture, Two Paths
|
25.
|
How It Works - Build Time and Runtime
|
26.
|
The Web Services for J2EE Specification
|
27.
|
JAX-RPC Deployment
|
28.
|
|
Mapping Between WSDL/XML and Java
|
29.
|
|
Generating from WSDL and Java
|
30.
|
Generating Web Services Using Java Code
|
The Java-to-XML Mapping, Primitive Types and Standard Classes
|
Lec.
Num
|
Unit Title
|
Details
|
31.
|
|
Value Types and JavaBeans, The Java-to-WSDL Mapping
|
32.
|
Simple and Complex Types, Arrays and Enumerations
|
33.
|
Service Endpoint Interface, Scope of Code Generation
|
34.
|
Inheritance Support, Multi-Tier Application Design, Analyzing the Domain
|
35.
|
Generating Java Web Services from WSDL
|
The XML-to-Java Mapping ,Simple and Complex Types
|
36.
|
Enumerations, Arrays, Miscellaneous, Optionally-Supported Constructs
|
37.
|
The WSDL-to-Java Mapping, Mapping Operation Inputs and Outputs
|
38.
|
Building a Service Client, Locating a Service, Client-Side Validation
|
39.
|
Creating a Web Service and Deploying the Service
|
40.
|
Web Services and Security
|
Threats to web services, Public key and digital signature techniques
|
41.
|
J2EE techniques, Securing a web service URIs
|
42.
|
HTTPS, XML and SOAP Solutions, XML encryption and Signature
|
43.
|
WS Security, SAML, XACML
|
Subject Code
|
J030335
|
Title
|
Soft Computing
|
Work Load Per Week
|
L:3 T:1
|
Examinations
|
Int: 30 Univ: 70
|
Objectives
|
Soft Computing is a discipline that deals with the design of hybrid intelligent systems, which is in contrast to classical hard computing technique. A consortium of computing methodologies that provides a foundation for the conception, design, and deployment of intelligent systems and aims to formalize the human ability to make rational decisions in an environment of uncertainty, imprecision, partial truth, and approximation. The main constituents of Soft computing involves neuro computing, fuzzy logic, genetic computing and probabilistic reasoning, and their fusion in real, scientific and industrial applications
|
Learning Outcomes
|
Students who successfully complete this course will be able to general understanding of soft computing methodologies, including artificial neural networks, fuzzy sets, fuzzy logic, fuzzy clustering techniques and genetic algorithms also design and development of certain scientific and commercial application using computational neural network models, fuzzy models, fuzzy clustering applications and genetic algorithms in specified applications
|
Pre-requisites
|
XII Level Mathematics
|
Text Book(s)
|
Artificial intelligence by Elaine Rich, Neural Networks, Fuzzy Logic, Genetic Algorithms by S. Rajasekaran
|
Syllabus
|
|
Lec.
Num
|
Unit Title
|
Details
|
Learning Resources
|
1
|
Introduction to Artificial Intelligence Systems
|
Overview of AI
|
Handout
|
2
|
|
Production Systems
|
Page29(R1)
|
Lec.
Num
|
Unit Title
|
Details
|
Learning Resources
|
3
|
|
Problem characteristics, Production system Characteristics
|
Page 36-44
(R1)
|
4
|
|
Issues in the Design of Search Programs
|
Page 57 (R1)
|
5
|
Heuristic search techniques
|
Hill climbing
|
Page 64(R1)
|
6
|
|
Branch bounding technique
|
Page 6(R1)
|
7
|
|
Best first search & A’ algorithm
|
Page 65(R1)
|
8
|
Soft computing-overview
|
Introduction
|
Handout
|
9
|
|
Guiding Principle of Soft computing
|
Handout
|
10
|
|
Importance of Soft computing
|
Handout
|
11
|
Fuzzy Set Theory
|
Introduction
|
Handout
|
12
|
|
Fuzzy Sets, Fuzzy Logic, Crisp Set
|
Page 157-186(R2)
|
13
|
|
Fuzzy Numbers and Fuzzy Arithmetic
|
Page 157-186(R2)
|
14
|
|
Determination of Membership Functions
|
Page 157-186(R2)
|
15
|
|
Crisp Relations
|
Page 157-186(R2)
|
16
|
|
Fuzzy Relations
|
Page 157-186(R2)
|
17
|
|
Fuzzy Rule based System
|
Page 157-186(R2)
|
18
|
|
Defuzzification Methods
|
Page 157-186(R2)
|
19
|
|
Applications
|
Page 157-186(R2)
|
20
|
|
Fuzzy Mathematical Programming
|
Handout
|
22
|
|
Programming Assignment
|
Page 157-186(R2)
|
23
|
|
Exercise
|
Handout
|
24
|
Evolutionary Computations
|
Introduction
|
Page 225-252(R2)
|
25
|
|
Basic concept
|
Page 225-252(R2)
|
26
|
|
Creation of Offspring
|
Page 225-252(R2)
|
27
|
|
Working Principle
|
Page 225-252(R2)
|
28
|
|
Encoding
|
Page 225-252(R2)
|
29
|
|
Fitness Function
|
Page 225-252(R2)
|
30
|
|
Reproduction
|
Page 225-252(R2)
|
31
|
|
Programming assignment
|
Page 225-252(R2)
|
Lec.
Num
|
Unit Title
|
Details
|
Learning Resources
|
32
|
Neural Networks
|
Introduction
|
Page 11-33(R2)
|
33
|
|
Basic concepts of Neural Networks
|
Page 11-33(R2)
|
34
|
|
Neural Networks Architectures
|
Page 11-33(R2)
|
35
|
|
Characteristics of Neural Network
|
Page 11-33(R2)
|
36
|
|
Solving optimization problems using neural networks
|
Page 11-33(R2)
|
37
|
|
Learning Methods
|
Page 11-33 (R2)
|
38
|
|
Programming assignment
|
Page 11-33 (R2)
|
39
|
|
Learning Methods
|
Page 11-33 (R2)
|
40
|
|
Programming assignment
|
Page 157-186(R2)
|
41
|
|
Back propagation Networks Architecture
|
Page 34-86 (R2)
|
42
|
|
Back propagation Learning’s
|
Page 34-86 (R2)
|
43
|
|
Applications
|
Page 34-86 (R2)
|
44
|
|
Variations of Standard Back propagation Algorithm
|
Page 34-86
(R2)
|
45
|
|
Research Direction
|
Page 34-86
(R2)
|
Reference Books:
(R1): Artificial intelligence by Elaine Rich
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