Exam Scheme

Note :-

1. Objective type paper.
2. All questions carry equal marks.
3. There will be Negative Marking.

---

Syllabus : Computer Science-II

---

1. Discrete Mathematical Structures:
   1. Counting principles, linear recurrence, mathematical induction, relations and functions, predicate and propositional logic.
   2. Graph: Definition and properties, connected graph, cycles & circuits.
   3. Tree: rooted tree, spanning trees.
   4. Models of Computability: Regular Expressions and Finite Automata.
   5. Context free grammars and Push down Automata.
   6. Regular and Context free languages, pumping lemma.
   7. Turing Machines and undecidability.
2. Data Structures and Algorithms:
   1. Analysis, Asymptotic notation, Notions of space and time complexity, Best, Worst and average case analysis.
   2. Design: Greedy approach, Dynamic programming, Divide-and conquer.
   3. Tree and graph traversals, Spanning tree algorithms, Shortest paths.
   4. Hashing, Sorting, Searching.
   5. Basic concepts of complexity classes P, NP, NP-hard, NP-complete.
3. Database Management System:
   1. ER-model, Relational model (relational algebra, tuple calculus).
   2. Database design (integrity constraints, normalization-1NF, 2NF, 3NF, BCNF and 4NF).
   3. Structured Query languages (SQL).
   4. File structures (sequential files, indexing, B and B+ trees).
   5. Transactions and concurrency control.
4. System Software:
   1. Assemblers: one pass & two pass assemblers design.
   2. Macros & Macro processors, loaders & linkers.
   3. Text editors & debuggers, Program generators.
   4. Compiler & Interpreter, Different phases of compilation process.
5. Emerging Trends and Technologies:
   1. Concept of Parallel Computing (Parallel Virtual Machine and Message passing Interface).
   2. Mobile Computing: Cellular system, Handoff, Location Management, Pervasive Computing.
   3. WLAN.
   4. E-Technologies: E-commerce framework and applications, Business models.
   5. Electronic payment System: Digital Token, Smart Cards, Credit Cards, risks in e-payment systems.
   6. Data Warehousing and Data Mining.