PMS Syllabus for the Subject of Computer Science Papers

1. Introduction to Computing

Number Systems, Binary numbers, Boolean logic, History Computer system, basic machine organization, Von Neumann Architecture, Algorithm definition, design, and implementation, Programming paradigms and Languages, Graphical programming, Overview of Software Engineering and Information Technology, Operating system, Compiler, Computer networks and Internet, Computer graphics, Al, Social and legal issues.

2. Programming Solving Techniques

Algorithms and problem solving, development of basic Algorithms, analyzing problem, designing solution, testing designed solution, fundamental programming constructs, translation of algorithms to programmes, data types, control structures, functions, arrays, records, files, testing programmes.

1. Computer Communications & Networks

Analogue and digital Transmission, Noise, Media, Encoding, Asynchronous and Synchronous transmission, Protocol design issues, Network System architecture (OSI, TCP/IP), Error control, Flow Control, Data Link Protocols (HDLC,PPP). Local Area Networks and MAC Layer protocols (Ethernet, Token ring), Multiplexing, Switching and IP Networks, Internetworking, Routing, Bridging, Transport layer protocols TCP/IP, UDP. Network security issues, Programming exercises or projects involving implementation of protocols at different layers.

2. Digital Logic & Computer Architecture

Logic design of Digital Systems, Fundamental and advanced concepts of Logic Designs, Boolean Algebra & functions, Designing and implementation of combinational and Sequential logic, minimization techniques, number representation and basic binary arithmetic Logic families and digital integrated circuits, use of CAD tools for logic designs. Topics of Computer Architecture.

1. Data Structures & Algorithms

Basic database concepts; Entity Relationship modeling, Relational data model and algebra, Structured Query Language, RDBMS, Database design, functional dependencies and normal forms, Transaction processing and optimization concepts, concurrency control and recovery techniques, Database recovery techniques, Database security and authorization, Small Group Project implementing a database, Physical database design. Storage and file structure, indexed files, hashed files, signature files, b-trees, files with dense index, file with variable length records, database efficiency and tuning.

2. Operating Systems

History and Goals, Evolution of multi-user systems, Process and CPU management, Multithreding, Kernel and User Modes, Protection, Problems of cooperative processes, Synchronization, Deadlocks, Memory management and virtual memory, Relocation, External Fragmentation, Paging and Demand Paging, Secondary storage, Security and Protection, File systems, I/O systems, Introduction to distributed operating systems. Scheduling, dispatch and Introduction to concurrency.

PMS Syllabus for the Subject of Computer Science Papers (PAPER II)

Total Marks:100

1. Theory of Automata and Formal Languages.

Finite State Models: Language definitions preliminaries, Regular expressions/Regular languages, Finite automatas (FAs), Transition graphs (TGs),NF As, kleene’s theorem, Transducers (automata with output), Pumping lemma and non regular language Grammars and PDA: Context free grammars, Derivations, derivation trees and ambiguity, Simplifying CFLs , Normal form grammars and parsing, Push-down Automata, Pumping lemma and non-context free languages, Decidability, Chomsky’s hierarchy of grammars, Turing Machines Theory: Turing machines, Post machine, Variations on 1M, 1M encoding, Universal Turing Machine, Context sensitive Grammars, Defining Computers by TMs.

2 Compiler Theory & Design

Compiler techniques and methodology. Organization of compilers. Lexical and syntax analysis. Parsing techniques. Object code generation and optimization, detection and recovery from errors. Comparison between compilers and interpreters.

3. Numerical Methods

Mathematical Preliminaries, Solution of Equations in one variable, Interpolation and Polynomial Approximation, Numerical Differentiation and Integration, Initial Value Problems for Ordinary Differential Equations, Direct Methods for Solving Linear Systems, Iterative Techniques in Matrix Algebra, Solution of non-linear equations, Approximation Theory, Eigenvalues and Eigenvector computation

I. Data Base Systems

Basic database concepts, Entity Relationship modelling, Relational data model and algebra, Structured Query language, RDBMS; Database design, functional dependencies and normal forms, Transaction processing and optimization concepts, concurrency control and recovery techniques, Database recovery techniques, Database security and authorization. Small Group Project implementing a database. Physical database design: Storage and file structure, indexed files, hashed files, signature files, b-trees, files with dense index, files with variable length records, database efficiency and tuning Data Warehousing and Data Mining, Emerging Database Technologies and Applications.

2. Software Engineering

Software Engineering, Process Models, Software verification and validation. Techniques are introduced to evaluate software correctness, efficiency, performance and reliability, integration of these techniques into a verification and validation plan. Technical reviews, software testing, programme verification, prototyping, and requirement tracing. Attitude of industry toward reliability and performance.

1. Artificial Intelligence

Introduction to Common Lisp. AI classical systems: General Problem Solver, rules, simple search, means-ends analysis. ElIZA, pattern matching, rule based translators, OPS-5. Knowledge Representation: Natural language, rules, productions, predicate logic, semantic networks, frames, objects, scripts. Searching, Depth first search, breadth first search, best first search, hill climbing, min-max search. Symbolic Mathematics: student solving algebra problems, translating English equations, solving algebraic equations, simplification rules, rewrite rules, meta-rules, Macsyma, PRESS, ATLAS. Logic Programming: Resolution, unification, horn-clause logic, Prolog, Prolog programming. Sample case studies of shells and Knowledge Based Systems. A brief appreciation of state of the art computational techniques like neural networks, genetic algorithm, fuzzy sets.

REFERENCE MATERIAL:

Artificial Intelligence by Luger, 4th edition, Pearson Education.

2. Computer Graphics

Graphics hardware, Fundamental algorithms, Applications of graphics. Interactive graphics programming -graph plotting, windows and clipping, and segmentation. Programming raster display systems, panning and zooming. Raster algorithms and software Scan-Converting lines, characters and circles. Region filling and clipping. Two and three dimensional imaging geometry and transformations. Curve and surface design, rendering, shading, colour and animation.