Detailed Syllabus Outline
- Introduction to Information Technology and Computers, History of Computing, Computer HW and SW Details, Computer System Components and Communication System, Input & Output devices and their types, Storage Media and their types, Types of Computer Hardware, Software, and Programming languages, Information Representation & Number Systems, User interfaces, Major Software Issues, Creation, formatting, and maintenance of Computer documents, Usage of Word processors, Spread sheets, Power-Point, Email, Search Engines, Browsers, Messengers, and Internet , Computers & Society, Information Security/Privacy, Computer Crimes and Ethical Challenges, Viruses, Plagiarism, Intellectual Property Rights, Difference between computer science, software engineering, information technology, information systems, computer engineering and bioinformatics; IEEE / ACM computing disciplines guidelines.
- Basic programming elements and concepts, Problem Solving & Program Design, Components of a programming language, Program development and execution, Program structure, Data types and variable declarations, Standard I/O streams, and statements, Control structures, Standard library functions, User defined functions and parameter passing, Arrays, pointers, and strings, Structures, unions, and bit manipulation operators.
- Object Oriented Programming Concepts ( Object-oriented paradigm, data abstraction, encapsulation, inheritance, Polymorphism), Introduction to Classes and Objects ( classes, objects, data members, member functions), Classes Advanced ( friends, static, composition, this, const), Operator overloading (stream insertion, stream extraction, binary operator, unary operator), Inheritance (single inheritance, multiple inheritances, protected members, method over-riding), Polymorphism (virtual function, pure-virtual functions, abstract cl**** abstract super class), Standard Template Library (STL), Files & streams (sequential access files, random access files), File processing, Exception Handling
- Section-B (50 Marks)
- Fundamental concepts, Properties of algorithms, Criteria for an Algorithm, Parameters for selecting an algorithm, Algorithm Representations, Pseudo Code and Flow Charts, Designing Algorithms, Algorithm Analysis and Asymptotic Notations, Classification of Lists, Abstract Data Types, Implementation of Stacks and Queues using ADTs, Searching and Sorting Algorithms (Linear Search, Binary Search, Bubble Sort, Merge Sort, Quick Sort, Heap Sort), Stacks and Queues, Hash Tables (Linear Probing, Bucketing, Chaining), Recursion, Trees (Binary Trees, Binary Search trees, AVL Trees, Two-Three Trees), Graphs, Heuristic (Guided) Search, Genetic Algorithms, Encryption Algorithms (DES, RSA)
- Software Processes, Software Process Models, Agile Software Development, Analysis Modeling, Requirements Engineering, Design Concepts, Architectural Design, Design & Implementation, Software Testing, System Delivery and Maintenance, Software Evolution Formal Specification, Software Quality Assurance, Introduction to Proofs of Correctness (LNO), Distributed Software Engineering, Aspect-Oriented Software Engineering, Project Management, Process Improvement
- Difference among various type of Translators, Phases of Compilers, Classification of Compilers, Lexical Analysis (Input buffering, Specification & Recognition of tokens, Regular expressions, Finite automata, Syntax Analysis (Context-free grammars and their classification, LL(k) vs. LR(k) grammars, Top-down vs. Bottom-Up parsers, Parsing Techniques, FIRST and FOLLOW sets, Predictive Parsing using LL(1) grammars, Syntax error handling and recovery strategies), Syntax Directed Translation (Synthesized attributes, Inherited attributes, Construction of syntax trees, Top-down translation), Semantic analysis (Symbol tables, Type Expressions, Type Checking of statements), Intermediate Code Generation, Code Generation (Issues in the design of code generation, The target machine, Run-time storage management, Register allocation), Code optimization (Elimination of Redundant code, Folding of Constant, Loop optimization, Peephole optimization, Problems of optimization)
- Fundamental concepts, Overview of a Computer System, Evolution & Performance Languages, Architectural levels, Virtual machines, Processor types, Metrics, Machine instructions, Instruction execution cycle, CISC vs. RISC, Parallelism, Internal/External data representation, Computer Function and Interconnections, Cache Memory, Internal Memory, External Memory, Input /Output System, Computer Arithmetic Microprocessor and its Bus Structure, I/O Types, Types of Buses, Memory Organization and Structure, information flow and execution in Machine, Instruction Representation, Machine Instruction Characteristics, Instruction Processing, Processor Structure & Function, Control Unit Operation, Micro-programmed Control, Instruction-Level Parallelism And Superscalar Processors, Parallel Processing, Multi-Processor and Multi-core Systems
- Basic Concepts and Classification of Networks, Circuit switching, Packet switching, Multiplexing (TDM, FDM), Layering: OSI and TCP/IP, Application Layer (Network application architectures, HTTP, FTP, Email, DNS, P2P applications), Transport Layer (Multiplexing in UDP and TCP, Connectionless Transport: UDP, Reliable data transfer and TCP, Congestion avoidance and control), Network Layer (The Internet Protocol, IPv4
- Datagram, Internet Address Classes, Special IP Addresses ARP, IPv6, ICMP, Network Address Translation (NAT), Internet Routing Protocols and Algorithms,
- topics (Security, Overlay networks, naming, Content distribution networks, Peer to peer systems, DHTs, Network Attacks)
- Roles of an Operating System, Operating-System Evolution, Structures, and Operations, Classification of Operating Systems, Computing Environments, Design and Components of OS, Process Management, Process Synchronization, Deadlocks, Memory Management, Virtual Memory Management, File Systems (UNIX and Windows Systems), I/O Management
- Section-B (50 Marks)
- Introduction to Database Systems, Relational Data Model & Relational Database Constraints, Relational Data Model, SQL, Relational Algebra & Calculus, ER Model, ER to Relational Mapping, PL/SQL Stored Procedures & Triggers, Functional Dependencies and Normalization, Storage & Indexing, Indexing Structure, XML documents & Web Services, Query Processing & Evaluation, Query Optimization, Transaction processing, Object- Oriented Databases, Distributed Databases, Database Security & Access Control
- The relation between Image Processing, Computer Graphics, Computer Vision and Artificial Intelligence; Image Sensing and Acquisition Techniques; Representing Digital Image; Image Sampling and Quantization; Image Storage and Operations; Image Transformations (Translation, Scaling, Rotation, Shear); Image Histogram; Image Enhancement (Contrast, Smoothing, Sharpening); Gray-scale and Color Images; Color Models (RGB, CMYK and HIS); Image Restoration; Noise Models; Morphological Operators (Erosion, Dilation, Opening, Closing, Skeletonization, Thinning); Image Segmentation; Point Detection, Line Detection, Edge Detection and Boundary Detection; Image Compression
- Modeling techniques for web applications, Introduction to web engineering, requirement engineering, requirement, types of requirements, functional requirements, non functional requirements, Requirement engineering process (Elicitation and negotiation, Documentation, Validation and verification, Management), HTML(hypertext markup language), Software Architecture, Styles, Patterns, and frameworks, Components of W eb Architecture, Classifications of web architecture , Web Application layered architecture ( client server, n- layered, JSP model, struts, OOHDM ), Integration Architecture, Data Aspect architectures, Cascading Style Sheet(CSS), CSS properties, JavaScript (Functionalities, Events, Variables, Operators), DOM(Document Object Model), XML, RSS, API, Client-side programming using (HTML, XHTML, XML, JavaScript, and CSS), Server- side programming using PHP, Web development process, Web Application Development Methodologies, Web site promotion and deployment, Web applications Issues (Accessibility, testing, performance, operation, maintenance, security)
FPSC Recommended Books
| Book Title | Author |
|---|---|
| C++ How to Program | Harvey M. Deitel and Paul J. Deitel. |
| Compilers: Principles, Techniques, and Tools | Alfred V. Aho, Ravi Sethi, and Jeffrey D. Ullman |
| Operating System Concepts | Silberschatz, Galvin, and Gagne. John |
| Operating Systems | William Stallings |
| Computer Organization & Architecture | William Stallings |
| Computer System Architecture | M. Morris Mano |
| Computer Organization and Design: The Hardware/ Software Interface | David A. Patterson and John L. Hennessy |
| Software Engineering | Ian Sommerville |
| Software Engineering A Practitioner’s Approach | Roger S. Pressman |
| Data Structures and Algorithm Analysis in C++ | Mark Allen Weiss |
| Computer Networking: A Top Down approach featuring the Internet | James F. Kurose and Keith W. Ross |
| Data and Computer Communications | William Stallings |
| Computer Networks | Andrew Tanenbaum |
| Fundamentals of Database Systems | Ramez Elmasri and S. B |
| Database Systems Concepts | Silberchatz, Abraham & Korth, Sudarshan |
| Web Services: Principles and Technology | Michael Papazoglu |
| Electronic Commerce: The Second Wave, Ninth Edition | Gary P. Schneider |
| Electronic-Commerce –A Managerial Perspective | Turban, Lee, King, Chung |
| Web Engineering | Kappel, G., Proll, B. Reich, S. & Retschitzegger |
| Styling Web Pages with CSS | Tom Negrino and Dori Smith |
| PHP: The Good Parts | Peter B. MacIntyre |
| Learn JavaScript | Chuck Easttom |
| ADTs, Data Structures, and Problem Solving with C++ | Larry R. Nayhoff |
| Digital Image Processing | Gonzalez and Woods |
Scoring High in Computer Science (CSS)
Computer Science is a solid 200-mark choice for candidates with a software engineering, IT, or computer science background. It offers an incredibly structured syllabus with objective, highly predictable question patterns.
1. Structuring Technical Answers (Paper I): Paper I focuses on computer architecture, programming concepts, data structures, and software engineering. Practice writing clean pseudo-code, C++ or Java snippets, and drawing accurate flowcharts or UML diagrams for algorithms. Code snippets act as mathematical proofs ensuring full marks.
2. Diagrams and Flowcharts (Paper II): Paper II delves into relational databases, operating systems, and networking protocols. Drawing Entity-Relationship (ER) models, process state diagrams, and understanding OSI layers visually are fundamental to scoring.
3. Emerging Technologies: Stay deeply updated on emerging tech trends like Artificial Intelligence, Cloud Computing, Cyber Security, and Big Data. FPSC examiners highly appreciate and actively test modern tech applications linking legacy knowledge to modern industry uses.
Frequently Asked Questions (FAQs)
1. How many marks does Computer Science carry in the CSS Exam?
Computer Science is a 200-mark subject in the FPSC CSS examination.
2. What are the core topics covered in Computer Science?
The syllabus primarily revolves around Section-A (50 Marks), I. Introduction to Computing, II. Programming Fundamentals and related topics. Check the detailed syllabus breakdown above for the exact structure.
3. Is Computer Science a scoring subject?
Yes, Computer Science is generally considered highly scoring if you stick strictly to the official FPSC syllabus, practice past papers, and use strong analytical arguments rather than generic statements.
4. How long does it typically take to prepare for Computer Science?
For a 200-mark subject, a strategic preparation plan typically requires 4 to 6 weeks of dedicated, consistent study and note-making.
5. What are the best recommended books for Computer Science?
FPSC recommends referring to authentic textbooks and journals. Some key referenced authors include Harvey M. Deitel and Paul J. Deitel. and Alfred V. Aho, Ravi Sethi, and Jeffrey D. Ullman. Avoid purely relying on local guidebooks.
6. Do I need a university degree in Computer Science to opt for it?
While an academic background provides a massive advantage, it is not strictly mandatory. Many candidates successfully prepare for Computer Science from scratch by consulting thoroughly recommended readings.
7. Are past papers important for Computer Science preparation?
Absolutely. Analyzing the last 5 to 7 years of CSS past papers for Computer Science is critical. It helps identify recurring themes, examiner traps, and high-frequency syllabus blocks.
8. How should I structure my answers in the Computer Science subjective paper?
To score highly, structure your subjective answers with clear introductions, relevant headings, bullet points, flowcharts (if applicable), and a balanced, critical conclusion.
9. Does Computer Science overlap with Compulsory CSS subjects?
Many concepts in Computer Science can build a strong analytical foundation for the English Essay and Current Affairs papers. Always look for cross-disciplinary linkages while studying.
10. Is coaching necessary to pass Computer Science?
No, professional coaching is not mandatory. With immense discipline, standard syllabus tracking, and self-evaluation via mock exams, candidates can secure excellent marks on their own.