To prepare well for the UGC NET Computer Science Exam, candidates must be aware of the UGC NET Computer Science Syllabus 2023, which covers all the topics that will be included in the exam. A thorough understanding of the syllabus can help candidates plan and create a study schedule in advance.
Candidates preparing for the UGC NET Exam in Computer Science & Application should specifically focus on Paper 2 syllabus, which is important for the exam. It is crucial to have knowledge of the updated UGC NET Computer Science Syllabus while preparing for the exam as it can significantly aid in the preparation process.
UGC NET Computer Science Syllabus 2023
NTA UGC NET Computer Science Syllabus for Paper 2
1st Unit : Discrete Structures and Optimization
- Mathematical Logic: Propositional and Predicate Logic, Normal Forms, Propositional Equivalences,
- Optimization: Linear Programming - Mathematical Model, Simplex and Dual Simplex Method, Graphical Solution, Sensitive Analysis.
- Group Theory: Groups, Product and Quotients of Algebraic Structures, Subgroups, Semi Groups, Isomorphism.
- Sets and Relations: Representation, Set Operations and Properties of Relations.
- Counting, Mathematical Induction and Discrete Probability: Pigeonhole Principle, Basics of Counting, Permutations and Combinations.
- Graph Theory: Simple Graph, Shortest Paths in Weighted Graphs, Multigraph, Paths and Circuits, Weighted Graph, Eulerian Paths and Circuits.
- Boolean Algebra: Boolean Functions and its Representation.
2nd Unit : Computer System Architecture
- Digital Logic Circuits and Components: Digital Computers, Logic Gates, Map Simplifications, Boolean Algebra, Combinational Circuits.
- Data Representation: Number Systems and Conversion, Data Types, Complements, Fixed Point Representation.
- Register Transfer and Micro operations: Bus, Register Transfer Language and Memory Transfers.
- Basic Computer Organization and Design: Stored Program Organization and Computer Registers, Instruction Codes, Computer Instructions.
- Programming the Basic Computer: Assembly Language, Machine Language, Assembler.
- Microprogrammed Control: Address Sequencing, Control Memory, Design of Control Unit.
- Central Processing Unit: Stack Organization, General Register Organization, Instruction Formats.
- Vector Processing and Pipeline: Arithmetic Pipeline, Pipelining, Parallel Processing.
- Input-Output Organization: Peripheral Devices and Input-Output Interface.
- Memory Hierarchy: Associative Memory, Main Memory, Auxiliary Memory.
- Multiprocessors: Interconnection Structures, Characteristics of Multiprocessors, Interprocessor Communication, Interprocessor Arbitration and Synchronization.
3rd Unit : Computer Graphics and Programming Languages
- Language Design and Translation Issues: Paradigms and Models, Programming Language Concepts, Programming Environments.
- Elementary Data Types: Composite Data Types and Scalar Properties of Types and Objects.
- Programming in C: Data Types, Tokens, Identifiers.
- Object-Oriented Programming: Inheritance, Class, Encapsulation, Object, Instantiation.
- Programming in C++: Datatypes, Tokens, Identifiers, Operators, Variables and Constants; Control statements.
- Web Programming: HTML, XML, Java, Servlets, DHTML, Scripting, Applets.
- Computer Graphics: Random-Scan Systems and Raster-Scan; Graphics Monitors, Video-Display Devices.
- 2-D Geometrical Transforms and Viewing: Rotation, Scaling, Translation, Reflection and Shear Transformations; Matrix Representations and Homogeneous Coordinates.
- 3-D Object Representation, Geometric Transformations and Viewing: Quadric Surfaces, Polygon Surfaces, Spline Representation.
4th Unit : Database Management Systems
- Database System Concepts and Architecture: Schemas, Data Models and Instances; Three-Schema Architecture and Data Independence.
- Data Modeling: Relational Model - Constraints, Entity-Relationship Diagram, Design, Languages, and Programming.
- SQL: Data Definition and Data Types; Queries, Constraints, Delete, Insert and Update Statements.
- Normalization for Relational Databases: Normalization; Algorithms for Query Processing & Optimization and Functional Dependencies.
- Enhanced Data Models: Temporal Database Concepts, Deductive Databases, Multimedia Databases.
- Data Warehousing and Data Mining: Concept Hierarchy, Data Modeling for Data Warehouses, OLAP and OLTP.
- Big Data Systems: , Introduction to Map-Reduce, Big Data Characteristics, Types of Big Data, Big Data Architecture and Hadoop.
5th Unit: System Software and Operating System
- System Software: Assembly, Machine, and High-Level Languages.
- Basics of Operating Systems: Operations, Operating System Structure, and Services.
- Process Management: Interprocess Communication; Process Scheduling and Operations, Communication in Client-Server Systems.
- Threads: Multithreading Models, Multicore Programming.
- CPU Scheduling: Thread Scheduling; Scheduling Criteria and Algorithms, MultipleProcessor Scheduling.
- Deadlocks: Methods for Handling Deadlocks, Deadlock Characterization, Deadlock Prevention.
- Memory Management: Paging, Contiguous Memory Allocation, Swapping, Segmentation.
- Storage Management: Scheduling and Management, Mass-Storage Structure, Disk Structure, RAID Structure.
- File and Input/Output Systems: File Sharing, Directory and Disk Structure; Access Methods, FileSystem Mounting, File-System Structure and Implementation; Directory Implementation.
- Security: Access Matrix, Protection, Revocation of Access Rights, Access Control, Program Threats, System and Network Threats; Cryptography as a Security Tool, User Authentication.
- Linux Operating Systems: Kernel Modules, Design Principles, Process Management, Scheduling, Memory Management.
- Windows Operating Systems: Design Principles, System Components.
- Distributed Systems: Network Structure, Types of Network based Operating Systems.
6th Unit: Software Engineering
- Software Process Models: Generic Process Model – Framework Activity, Software Process, Project Management, Process Lifecycle, Task Set and Process Patterns; Prescriptive Process Models, Component Based Development.
- Software Requirements: Eliciting Requirements, Developing Use Cases; Functional and Non-Functional Requirements.
- Software Design: Functional Independence, Abstraction, Architecture, Patterns, Modularity, Separation of Concerns, Information Hiding.
- Software Quality: McCall’s Quality Factors, ISO 9126 Quality Factors, Quality Assurance, Quality Control, Risk Management.
- Estimation and Scheduling of Software Projects: Software Sizing, Estimating Cost and Effort; LOC and FP based Estimations; Estimation Models.
- Software Testing: Unit and Integration Testing; Verification and Validation; Error, Fault, Bug, and Failure; White-box and Black-box Testing.
- Software Configuration Management: Software Reuse; Change Control and Version Control.
7th Unit: Data Structures and Algorithms
- Data Structures: Arrays and their Applications; Sparse Matrix, Stacks, Priority Queues, Queues, Trees, Linked Lists, Binary Tree, Forest, Threaded Binary Tree.
- Performance Analysis of Algorithms and Recurrences: Time and Space Complexities.
- Design Techniques: Divide and Conquer; Dynamic Programming, Greedy Algorithms.
- Lower Bound Theory: Lower Bounds through Reductions, Comparison Trees.
- Graph Algorithms: Depth-First Search, Breadth-First Search.
- Complexity Theory: NP-completeness and Reducibility; P and NP Class Problems;
- Selected Topics: Polynomial Arithmetic, Number Theoretic Algorithms.
- Advanced Algorithms: Searching, Parallel Algorithms for Sorting and Merging.
8th Unit : Theory of Computation and Compilers
- Theory of Computation: Non-Computational Problems, Formal Language.
- Regular Language Models: Non-Deterministic Finite Automaton (NDFA), Deterministic Finite Automaton (DFA), Regular Languages, Equivalence of DFA and NDFA, Regular Grammars.
- Context Free Language: Pushdown Automaton (PDA), Context Free Grammar, Non-Deterministic Pushdown Automaton (NPDA), Greibach Normal Form, Chomsky Normal Form, Ambiguity.
- Turing Machines (TM): Standard Turing Machine and its Variations; Recursive and Recursively Enumerable Languages; Universal Turing Machines, Models of Computation and Church-Turing Thesis.
- Unsolvable Problems and Computational Complexity: Unsolvable Problem, Post Correspondence Problem, Halting Problem.
- Syntax Analysis: Associativity, Top Down Parsing, Precedence, Grammar Transformations, Recursive Descent Predictive Parsing.
- Semantic Analysis: Syntax Directed Definitions, Attribute Grammar, Inherited and Synthesized Attributes; Dependency Graph.
- Run Time System: Activation Tree, Storage Organization, Activation Record.
- Intermediate Code Generation: Translation of Declarations, Intermediate Representations, Assignments.
- Code Generation and Code Optimization: Data-flow Analysis, Control-flow, Global Optimization, Local Optimization, Loop Optimization.
9th Unit : Data Communication and Computer Networks
- Data Communication: Simplex, Half Duplex and Duplex Modes of Communication, Components of a Data Communication System; Analog and Digital Signals; Noiseless and Noisy Channels; Bandwidth.
- Computer Networks: Network Topologies, Local Area Networks and all other types of Networks.
- Network Models: OSI Reference Model and its Protocols,Layered Architecture.
- Functions of OSI and TCP/IP Layers: Error Detection and Correction, Framing; Flow and Error Control; HDLC, Sliding Window Protocol.
IPv4 Structure and Address Space; Classful and Classless Addressing; Datagram, Fragmentation and Checksum; Mapping Logical to Physical Address (ARP), IPv6 Packet Format.
- World Wide Web (WWW): Domain Name Service (DNS), Uniform Resource Locator (URL), Resolution - Mapping Names to Addresses.
- Network Security: Cryptography, Malwares and Steganography; Secret-Key Algorithms.
- Mobile Technology: GSM and CDMA; Services and Architecture of GSM and Mobile Computing; Mobile IP and Mobile Communication Protocol; Middleware and Gateway for Mobile Computing.
- Cloud Computing and IoT: IaaS, SaaS, PaaS, Public and Private Cloud; Virtual Server, Virtualization, Cloud Storage.
10th Unit : Artificial Intelligence (AI)
- Approaches to AI: State Space Representation of Problems; Turing Test and Rational Agent Approaches.
- Knowledge Representation: Frames, Logic, Semantic Networks, Scripts, Rules, Conceptual Dependency and Ontologies.
- Planning: Linear and Non Linear Planning, Components of a Planning System; Goal Stack Planning.
- Natural Language Processing: Grammar and Language and Pragmatics.
- Multi-Agent Systems: Agents and Objects; Generic Structure of Multiagent System; Agents and Expert Systems.
- Fuzzy Sets: Membership Functions, Notion of Fuzziness, Fuzzification and Defuzzification; Operations on Fuzzy Sets.
- Genetic Algorithms (GA): Genetic Operators, Encoding Strategies, Fitness Functions, and GA Cycle.
- Artificial Neural Networks (ANN): Unsupervised, Supervised and Reinforcement Learning; Single Perceptron.
