Course Name Software Engineering -I Course Number 371 CSM-3 Credit Hours 3 Contact Hours 4 Course Coordinator Dr.M.K.Jayanthi

Transcription

1 Course Name Software Engineering -I Course Number 371 CSM-3 Credit Hours 3 Contact Hours 4 Course Coordinator Dr.M.K.Jayanthi Text Books Software Engineering 9th Ed, Sommerville, PEARSON ISBN-10 : Other Supplemental Materials Specific Course Information This course is an introduction to software engineering and examines the a. Course Description theory, techniques, and technologies associated with the design, construction and testing of software systems. Topics cover the software engineering paradigms, Software process, Agile software development, Requirement Engineering and Software modeling. b. Pre-requisite 114CSM-4 Object-Oriented Programming (OOP) c. Required/ Elective/ Selected Elective a. Course Learning Outcomes Required Specific Goals for the Course 1. State the main purpose and elements of Software Engineering. 2. Describe the Software Engineering Ethics and Principles. 3. Understand the basics of Professional Software Development process and its Stages. 4. Compare different Software Process Models like Plan driven development and Agile Development. 5. Analyse Software Process Activities and Develop and design Rational Unified Process (RUP) Models. 6. Analyse Coping with change in Agile Process and Design UML Diagrams. 7. Use Functional and non Functional Requirements Engineering process. 8. Choose Requirement Specification to improve the Data Design. 9. Interpret the different System Modelling techniques and Design Model Driven engineering Process. 10. Justify the limitations of Static Models comparing with Behavioral models. 11. Show working of Structural models.

2 Mapping of STUDENT OUTCOMES(SLOS) with COURSE OUTCOMES(CLOS) 1 a1 a2 b1 b2 b3 b4 c1 c2 c3 c4 d1 d Topics Covered Introduction to Software Engineering: Professional Software Development- Basics of software engineering-software Engineering Ethics-Case Study Software Process :Software Process Models-Process Activities -Coping with change -Rational Unified Process (RUP ) Agile Software Development :Agile Method-Plan driven and Agile development -Extreme Programming Requirements engineering: Functional and non Functional Requirements-Software Requirement Document-Requirement Specification-Requirements Engineering Processes System Modeling: Context models-interaction models-structural models-behavioral models-model Driven engineering

3 Course Name Introduction to Artificial Intelligence Course Number 375 CSM -3 Credit Hours 3 Contact Hours 4 Course Coordinator Dr.Nermeen Talat Text Books Introduction to Artificial Intelligence by Elaine Rich & Kevin Knight, 2nd Ed. Other Supplemental Materials Specific Course Information a. Course Description This course is designed to provide the students with an introduction to the fundamental concepts and techniques underlying the construction of intelligent computer systems and stimulate practical experiences of using such techniques in applications by apply some of them in programming assignments. Topics covered in the course include: Intelligent agent, problem solving and search, game playing, expert systems, fuzzy logic, and machine learning. b. Pre-requisite None c. Required/ Elective/ Selected Elective a. Course Learning Outcomes Required Specific Goals for the Course 1. Define Artificial Intelligent. 2. Describe various areas of Artificial Intelligent. 3. Recognize different search algorithms in AI. 4. Analyze the Heuristic search. 5. Justify the knowledge for different AI. 6. Analyze the scope for performance improvement. 7. Use case study to implement AI. 8. Demonstrate different applications of AI.

4 Mapping of STUDENT OUTCOMES(SLOS) with COURSE OUTCOMES(CLOS) Topics Covered a1 a2 b1 b2 b3 b4 c1 c2 c3 c4 d1 d Introduction to A.I: Definitions, AI problems, Application of AI AI techniques; Level of the model; Success criteria, introduction to Agents, Agent faculties, Agent Architecture. Problem Solving Search and Control Strategies General problem solving, search and control strategies, problem space, State space search, Problem characteristics, Production system and characteristics, Heuristic search techniques, Generate and test; Hill climbing. Best first search; Problem reduction; Constraint satisfaction; Means ends analysis Knowledge representation: Approaches to representations; Mappings Representing knowledge using rules: Procedural versus declarative knowledge Logic Programming; Forward versus Backward Reasoning; Matching Natural Language Processing, Syntactic Processing and Semantic Analysis Fuzzy logic, expert system, Game theories.

5 Course Name Computer Networks 2 Course Number 463 CSM 4 Credit Hours 4 Contact Hours 5 Course Coordinator Dr.Manoj Signhal Text Books Data Communications and Networking By Behrouz A. Forouzan with Sophia Chung Fegan, 4th International Edition, 2007, McGraw Hill. Other Supplemental Materials Specific Course Information This course introduces advance topics in network protocol, architecture a. Course Description and applications. Important topics including Data Link Layer: Error Detection and Correction, Network Layer: Logical Addressing, Delivery, Forwarding, and Routing, Quality of Service (QoS), Network Management: Simple Network Management Protocol, Cryptography and Internet Security: IPSec, SSL/TLS, PGP VPN, and Firewalls are covered in this course b. Pre-requisite 364CSM-4 Computer Networks 1 c. Required/ Elective/ Selected Elective Required Specific Goals for the Course 1. Describe the error detection and correction techniques 2. Define classfull and classless addressing 3. Describe the nature and roles of protocols working at the application, network, data link and physical layers 4. Design subnet of a big network as per the given requirement a. Course Learning 5. Calculate the first address, last address and total number of address Outcomes (COURSE of an address block whose one address is given 6. Create the routing table for different routing protocols OUTCOMES(CLOS)) 7. Analyze the security issues in the internet 8. Demonstrate the working of a protocol by using latest simulation software

6 Mapping of STUDENT OUTCOMES(SLOS) with COURSE OUTCOMES(CLOS) Topics Covered a1 a2 b1 b2 b3 b4 c1 c2 c3 c4 d1 d Error Detection and Correction: Types of Errors-Error Detection- Error Correction-CYCLIC CODES-Cyclic Redundancy Check Network Layer: Logical Addressing-IPv4 ADDRESSES-Address Space-Notations-Class full Addressing-Classless Addressing-Network Address Translation (NAT)-IPv6 ADDRESSE-IPV6 Structure Network Layer: Internet Protocol: Internetworking-IPv4-IPv6- transition from IPv4 TO IPv6-Dual Stack-Tunneling-Header Translation Network Layer: Delivery, Forwarding, and Routing-unicast routing protocols-optimization-intra- and Inter domain Routing-Distance Vector Routing-Link State Routing-Path Vector Routing-multicast routing protocols Quality of Service (QoS): Flow characteristics-flow Classes- Techniques to Improve QoS-Integrated Services-Differentiated Services Network Management: SNMP Simple Network Management Protocol (SNMP)-Concept, Management Components Structure of Management Information-Management Information Base (MIB)-SNMP-Messages- UDP Ports-Security Cryptography: Symmetric-Key Cryptography-Traditional Ciphers- Simple Modem Ciphers-Modem Round Ciphers-Mode of Operation- Asymmetric-Key Cryptography-RSA Security in the Internet: IPSec, SSL/TLS, PGP VPN, and Firewalls-IP Security (IPSec)-Two Modes-Two Security Protocols

7 Course Name Software Project Management Course Number 472 CSM 3 Credit Hours 3 Contact Hours 4 Course Coordinator Dr.Yessine Haj Kacem Text Books 1. Software Engineering 9th Ed, Sommerville, PEARSONISBN-10 : Software Engineering, 7th Ed. Roger S. Pressman, McGraw Hill, ISBN-13 : Other Supplemental Materials a. Course Description Specific Course Information The course introduces the students to the various concepts and methodologies of Project Management. The actual procedures are described. Exercises and Case Studies (Workshops) are introduced within the learning scope whereby assessing general implications. Brief introduction to Microsoft Project is given as well. Students will build hands-on training from especially prepared workshops b. Pre-requisite 233 CSM Computer Modeling and Simulation c. Required/ Elective/ Selected Elective a. Course Learning Outcomes Required Specific Goals for the Course 1. Recognize the advanced concepts of software project management. Be able to understand well the techniques of managing people, resources and risks of software projects. 2. Be able to understand well the software project risks and develop optimal solutions. Be able to understand well the advanced topics such as software project cost and price, Quality Management, Software Testing Strategies and Process Improvement 3. Create charts for project scheduling using PERT and GANTT diagrams. Judge the quality of a software. Estimate the software project cost and price. Evaluate and test a software project 4. Develop the capability of thinking and designing application projects. 5. Analyze the concepts to employ to real life project applications. 6. Communicate and share the work with other 7. Expressing understanding concepts both orally and in written.

8 Mapping of STUDENT OUTCOMES(SLOS) with COURSE OUTCOMES(CLOS) Topics Covered 1 x x a1 a2 b1 b2 b3 b4 c1 c2 c3 c4 d1 d2 2 x x 3 x x x x x 4 x x x x 5 x x x x 6 x x x x 7 x x Overview of Software Project Management : Project Management Concepts - The Management Spectrum: People, The Product, The Process, The Project W5HH principle, Critical Practices Project Planning and Scheduling: Software Pricing, Plan Driven development Project Scheduling, Estimation Techniques Risk Management: Risk Strategies, Risk Identification,Risk Projection, Risk Refinement Risk Mitigation, Monitoring and Management. Quality Management: Software Quality, Software Standards - ISO 9001 standards framework Software measurements and metrics - Software Testing Strategies : Verification and Validation -Types of Testing, System testing Process Improvement: Process measurement, Process analysis - Process change, CMMI ( Capability Maturity Model ).

9 Course Name Software Engineering II Course Number 473 CSM -3 Credit Hours 3 Contact Hours 4 Course Coordinator Dr.M.K.Jayanthi Text Books Other Supplemental Materials 1. Software Engineering: Somerville 9th Edition 2. Software Engineering: Somerville 8th Edition (ch11 only) Specific Course Information a. Course Description This course is designed to provide the advanced concepts of software engineering according to the needs. Topics covered the advanced concepts of software engineering which include architectural design, distributed systems architecture, application architecture, object oriented design, real time software design and component based software engineering. b. Pre-requisite CS 371 Software engineering - 1 c. Required/ Elective/ Selected Elective a. Course Learning Outcomes Required Specific Goals for the Course 1. Define the advanced concepts of software engineering. 2. State the models of architectural design for software and the phases of Software development. 3. Describe the Software Engineering concepts with case studies. 4. Analysis the requirement of software using concepts of objectoriented design. 5. Develop software using component models and software reuse. 6. Architectural patterns for distributed systems and the role of software developer. 7. Modify the software based on software reuse strategy and use of Open sources to software. 8. Examine components and integrate them to produce software. 9. Use CASE tools for analysis and design the software and Illustrate Application frameworks.

10 Mapping of STUDENT OUTCOMES(SLOS) with COURSE OUTCOMES(CLOS) 1 a1 a2 b1 b2 b3 b4 c1 c2 c3 c4 d1 d Topics Covered Architectural Design: Architectural design decisions--system organization- Modular decomposition styles- Control styles-reference architectures Design and implementation: Object-oriented design using the UML- Design patterns- Implementation issues-open source development Distributed software engineering: Distributed systems issues- Client server computing- Architectural patterns for distributed systems- Software as a service Software reuse: The reuse landscape- Application frameworks- Software product lines- COTS product reuse.

11 Course Name Design & Analysis of Algorithms Course Number 474 CSM-3 Credit Hours 3 Contact Hours 4 Course Coordinator Dr.Mohammed Ramadan Text Books Other Supplemental Materials Introduction to Algorithms, 2nd Edition, T.H. Cormen, C.E. Leiserson, R.L. Rivest, and C. Stein, McGraw-Hill, Specific Course Information a. Course Description This course is a survey of concepts, principles and techniques related to the designing and analyzing algorithms. Students will become acquainted with both the strengths and limitations of various techniques like greedy approach, divide and conquer, dynamic programming, branch and bound. Lower bounds on the efficiency of solving are also address, especially the notion of NP-completeness b. Pre-requisite CSM 216 -Algorithms & Data Structures 2 c. Required/ Elective/ Selected Elective a. Course Learning Outcomes Required Specific Goals for the Course 1. Describe the methodologies of how to analyse an algorithm 2. Determine asymptotic expressions for the best and worst-case running time of algorithms. 3. Explain the basic concepts of time and space complexity, divide and conquer strategy, dynamic programming, greedy and approximate algorithms and amortized analysis. 4. Analyze the complexities of various problems in different domains 5. Develop algorithmic paradigms and methods by using design techniques to solve problems; investigate the complexities of various problems in different domains; 6. Calculate complexity for different types of algorithms for different types of problems.. 7. demonstrate the complexities of various problems in different domains

12 Mapping of STUDENT OUTCOMES(SLOS) with COURSE OUTCOMES(CLOS) Topics Covered 1 a1 a2 b1 b2 b3 b4 c1 c2 c3 c4 d1 d Introduction: Analyzing algorithms - Asymptotic notation. Order Analysis: Objectives of time analysis of algorithms; Big-oh and Theta notations. Master Theorem and its proof, solution of divide and conquer recurrence relations Searching, Sorting and Divide and Conquer Strategy:Linear Search, Binary Search-Merge-sort; Quick-sort with average case analysis. Heaps and heap-sort. Lower bound on comparison-based sorting and Counting sort. Dynamic Programming: methodology and examples (Fibonaci numbers, Knapsack problem and some other simple examples)-longest integer subsequence, Longest common subsequence,weighted interval scheduling Greedy Method: Methodology, examples and comparison with DP - Knapsack problem and some other simple examples Graph Algorithms: Basics of graphs and their representations. BFS. DFS. Topological sorting Minimum spanning trees. Shortest Paths (Dijkstra, Bellman-Ford, Floyd-Warshall). Hard problems and approximation algorithms: Problem classes P, NP, NP-hard and NP-complete, deterministic and nondeterministic polynomial-time algorithms.

13 Course Name Expert System and Knowledge Engineering Course Number 476CSM -3 Credit Hours 3 Contact Hours 4 Course Coordinator Dr.Narmeen Talat Text Books Other Supplemental Materials 1. Kendal, Simon, Creen, Malcolm An Introduction to Knowledge Engineering 2007, X, 287 p. 33 illus.isbn Introduction to Expert Systems By Peter Jackson Addison Wesley Longman, ISBN Specific Course Information a. Course Description This course introduces students to advanced topics on Expert system and Knowledge Engineering(KE). It covers ESDL, Problem definition, Knowledge representation, knowledge acquisition, part of the Knowledge Engineering. Through the tutorial sessions, the students are given the opportunity to understand knowledge engineering by building and documenting an expert system that addresses a real-world problem. Upon completion of the course, students are able to recognize the relevant domains of knowledge engineering. b. Pre-requisite Introduction to Artificial Intelligence 375 CSM c. Required/ Elective/ Selected Elective a. Course Learning Outcomes Required Specific Goals for the Course 1. Define Knowledge base system. 2. Describe Expert system and its functionalities. 3. Recognize possible solution for real world problems. 4. Analyze the real world problem and choose suitable KMS. 5. Justify the knowledge for different Expert system. 6. Analyze the existing knowledge base and Expert system. 7. Use case study to implement Expert system. 8. Demonstrate different applications of Expert.

14 Mapping of STUDENT OUTCOMES(SLOS) with COURSE OUTCOMES(CLOS) Topics Covered a1 a2 b1 b2 b3 b4 c1 c2 c3 c4 d1 d Introduction To Knowledge Engineering - Data, Information And Knowledge -Comparison Of Engineering, Software Engineering & Knowledge Engineering-The Role Of Knowledge Engineer-Categories Of Knowledge Based System Knowledge Acquisition -Introduction-Scopes Of Knowledge-Sources Of Knowledge-Levels Of Knowledge-Types Of Knowledge-Procedural Knowledge -Declarative Knowledge-Meta-Knowledge-Heuristics Knowledge-Structural Knowledge-Knowledge Acquisition-Prerequisites For Acquisition-Problems In Knowledge Acquisition-Knowledge Acquisition Techniques-Introspection-Observation. -Induction-Protocol Analysis-Prototyping-Interviewing. Structuring Knowledge Graphically-Cognitive Maps-Flowchart- Inference Networks The representation of knowledge-introduction -semantic networksdecision tables-decision trees-frames-production rules-logicpropositional logic.