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Computer Science and Information Technology Curriculum: A Comprehensive Guide, Exercises of Computer Science

An overview of the computer science and information technology curriculum, covering topics from discrete mathematics and linear algebra to digital logic and compiler design. Sections include engineering mathematics, digital logic, computer organization and architecture, programming and data structures, algorithms, theory of computation, compiler design, operating system, and databases. Additionally, computer networks are discussed.

Typology: Exercises

2019/2020

Uploaded on 01/24/2020

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CS
Computer Science and Information Technology
Section1: Engineering Mathematics
Discrete Mathematics: Propositional and first order logic. Sets, relations, functions, partial
orders and lattices. Groups. Graphs: connectivity, matching, coloring. Combinatorics:
counting, recurrence relations, generating functions.
Linear Algebra: Matrices, determinants, system of linear equations, eigenvalues and
eigenvectors, LU decomposition.
Calculus: Limits, continuity and differentiability. Maxima and minima. Mean value
theorem. Integration.
Probability: Random variables. Uniform, normal, exponential, poisson and binomial
distributions. Mean, median, mode and standard deviation. Conditional probability and
Bayes theorem.
Computer Science and Information Technology
Section 2: Digital Logic
Boolean algebra. Combinational and sequential circuits. Minimization. Number
representations and computer arithmetic (fixed and floating point).
Section 3: Computer Organization and Architecture
Machine instructions and addressing modes. ALU, datapath and control unit. Instruction
pipelining. Memory hierarchy: cache, main memory and secondary storage; I/O
interface (interrupt and DMA mode).
Section 4: Programming and Data Structures
Programming in C. Recursion. Arrays, stacks, queues, linked lists, trees, binary search
trees, binary heaps, graphs.
Section 5: Algorithms
Searching, sorting, hashing. Asymptotic worst case time and space complexity.
Algorithm design techniques: greedy, dynamic programming and divideandconquer.
Graph search, minimum spanning trees, shortest paths.
Section 6: Theory of Computation
Regular expressions and finite automata. Context-free grammars and push-down
automata. Regular and contex-free languages, pumping lemma. Turing machines and
undecidability.
Section 7: Compiler Design
Lexical analysis, parsing, syntax-directed translation. Runtime environments. Intermediate
code generation.
Section 8: Operating System
Processes, threads, interprocess communication, concurrency and synchronization.
Deadlock. CPU scheduling. Memory management and virtual memory. File systems.
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CS Computer Science and Information Technology

Section1: Engineering Mathematics

Discrete Mathematics: Propositional and first order logic. Sets, relations, functions, partial orders and lattices. Groups. Graphs: connectivity, matching, coloring. Combinatorics: counting, recurrence relations, generating functions.

Linear Algebra: Matrices, determinants, system of linear equations, eigenvalues and eigenvectors, LU decomposition.

Calculus: Limits, continuity and differentiability. Maxima and minima. Mean value theorem. Integration.

Probability: Random variables. Uniform, normal, exponential, poisson and binomial distributions. Mean, median, mode and standard deviation. Conditional probability and Bayes theorem.

Computer Science and Information Technology

Section 2: Digital Logic

Boolean algebra. Combinational and sequential circuits. Minimization. Number representations and computer arithmetic (fixed and floating point).

Section 3: Computer Organization and Architecture

Machine instructions and addressing modes. ALU, data‐path and control unit. Instruction pipelining. Memory hierarchy: cache, main memory and secondary storage; I/O interface (interrupt and DMA mode).

Section 4: Programming and Data Structures

Programming in C. Recursion. Arrays, stacks, queues, linked lists, trees, binary search trees, binary heaps, graphs.

Section 5: Algorithms

Searching, sorting, hashing. Asymptotic worst case time and space complexity. Algorithm design techniques: greedy, dynamic programming and divide‐and‐conquer. Graph search, minimum spanning trees, shortest paths.

Section 6: Theory of Computation

Regular expressions and finite automata. Context-free grammars and push-down automata. Regular and contex-free languages, pumping lemma. Turing machines and undecidability.

Section 7: Compiler Design

Lexical analysis, parsing, syntax-directed translation. Runtime environments. Intermediate code generation.

Section 8: Operating System

Processes, threads, inter‐process communication, concurrency and synchronization. Deadlock. CPU scheduling. Memory management and virtual memory. File systems.

Section 9: Databases

ER‐model. Relational model: relational algebra, tuple calculus, SQL. Integrity constraints, normal forms. File organization, indexing (e.g., B and B+ trees). Transactions and concurrency control.

Section 10: Computer Networks

Concept of layering. LAN technologies (Ethernet). Flow and error control techniques, switching. IPv4/IPv6, routers and routing algorithms (distance vector, link state). TCP/UDP and sockets, congestion control. Application layer protocols (DNS, SMTP, POP, FTP, HTTP). Basics of Wi-Fi. Network security: authentication, basics of public key and private key cryptography, digital signatures and certificates, firewalls.