MCA 3rd Semester DU Syllabus 2020 – MCA 2nd Year (All Subjects) is provided in this article. Delhi University (दिल्ली विश्वविद्यालय) providing MCA course with different specializations and their respective syllabus. MCA 2nd year – 1st semester revised syllabus with all the subjects is available on this page. Chapter wise new syllabus is updated in this article. For the preparation of semester examinations candidates have to know the DU Syllabus of MCA 3rd Semester. Delhi University official website is www.du.ac.in
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About Delhi University
The University of Delhi is the premier university located in New Delhi, India. It has grown into one of the largest university in India. Five Departments namely Chemistry, Geology, Zoology, Sociology, and History have been awarded the status of the Centres of Advanced Studies. Du offers UG, PG and other certificate courses with the maximum number of specializations in courses. Various departments are located in the Faculty of Arts and the Faculty of Inter-disciplinary and Applied Sciences.
Delhi University MCA Course Structure
|MCA Course structure in Delhi University|
|MCA is a 3 years under graduation course||1st year||Semester 1||4 months Duration|
|Semester 2||4 months|
|2nd year||Semester 3||4 months|
|Semester 4||4 months|
|3rd year||Semester 5||4 months|
|Semester 6||4 months|
Master of Computer Applications is the three-year course divided into a number of semesters which are generally six in number with different specializations that are given below.
- Application Software
- Hardware Technology
- Management Information Systems
- Software Development
- Systems Management
- Systems Development
- Systems Engineering
Subjects in MCA 3rd Semester – Delhi University
The following are the subjects in MCA 3rd Semester
- Design and Analysis of Algorithms
- Software Engineering
- Database Systems
- Automata Theory
- Operating Systems
Download MCA 3rd Semester DU Syllabus 2020
DU MCA 3rd Semester Syllabus
|Course No||Title||L-T-P||Credits||Total marks|
|MCA 301||Design and Analysis of Algorithms||3 – 1 – 0||4||100|
|MCA 302||Software Engineering||3 – 0- 2||4||100|
|MCA 303||Database Systems||3 – 0 -2||4||100|
|MCA 304||Automata Theory||3 – 1 – 0||4||100|
|MCA 305||Operating Systems||3 – 0 – 2||4||100|
- L – T – P: Lectures – Tutorials – Practical
MCA 301: DESIGN AND ANALYSIS OF ALGORITHMS
Introduction: RAM model, O(log n) bit model.Review of data structures: Balanced trees, Mergeable sets.
Algorithm Design Techniques: Iterative techniques, Divide and conquer, dynamic
programming, greedy algorithms.
Searching and Sorting Techniques: Review of elementary sorting techniques-selection sort,
bubble sort, insertion sort; more sorting techniques-quick sort, heap sort, merge sort, shell sort;
Lower bounding techniques: Decision Trees, Adversaries.
String Processing: KMP, Boyre-Moore, Robin Karp algorithms.
Introduction to randomized algorithms: Random numbers, randomized Qsort, randomly Built BST
Number Theoretic Algorithms: GCD, Addition, and Multiplication of two large numbers, polynomial arithmetic, Fast-Fourier Transforms.
Graphs: Analysis of Graph algorithms Depth-First Search and its applications, minimum
Spanning Trees and Shortest Paths.
Introduction to Complexity Theory: Class P, NP, NP-Hard, NP Completeness.
Introduction to Approximation Algorithms
MCA 302: SOFTWARE ENGINEERING
Software Engineering: The software crisis, principles of software engineering, programmingin-the-small vs. programming-in-the-large
Software process: The software lifecycle, the waterfall model and variations, risk-driven
approaches, introduction to evolutionary and prototyping approaches, agile process models,
Project management: Relationship to lifecycle, project planning, project control, project
organization, risk management, cost models, configuration management, version control,
quality assurance, metrics
Software requirements: Requirements analysis, functional and non-functional requirements
elicitation, analysis tools, requirements definition, requirements specification, static and
dynamic specifications, requirements review.
Software design: Design for reuse, design for change, design notations, design evaluation and
Implementation and Maintenance: Programming standards and procedures, modularity, data abstraction, static analysis, unit testing, integration testing, regression testing, verification and validation, tools for testing, fault tolerance, The maintenance problem, the nature of
maintenance, planning for maintenance
MCA 303: DATABASE SYSTEMS
Basic Concepts: Data modeling for a database, abstraction and data integration, three-level
the architecture of a DBMS, overview of relational, network, hierarchical data models.
Database Design: Entity-Relationship model, Extended Entity-Relationship model
Relational Model & Relational Data Manipulations: Relation, conversion of ER diagrams to
relations, integrity constraints, relational algebra, relational domain & tuple calculus
Structured Query Language: DDL, DML, Views, Embedded SQL,
Relational Database Design Concepts: Functional dependencies, determining keys,
normalization-1st, 2nd, 3rd, BCNF, 4th and 5th, lossless join and dependency preserving
Advanced Database Concepts: Security and recovery, Concurrency Control in databases
MCA 304: AUTOMATA THEORY
Introduction: Alphabets, strings, and languages.
Finite Automata and Regular Languages: Deterministic and non-deterministic finite
automata, regular expressions, regular languages and their relationship with finite automata,
pumping lemma and closure properties of regular languages.
Context-Free Grammars and Pushdown Automata: Context-free grammars (CFG), parse
trees, ambiguities in grammars and languages, pushdown automaton (PDA) and the language
accepted by PDA, deterministic PDA, Non- deterministic PDA, properties of context-free
languages; normal forms, pumping lemma, closure properties, decision properties.
Turing Machines: Turing machine as a model of computation, programming with a Turing
machine, variants of Turing machine and their equivalence.
Undecidability: Recursively enumerable and recursive languages, undecidable problems about
Turing machines: halting problem, Post Correspondence Problem, and undecidability problems about CFGs.
MCA 305: OPERATING SYSTEMS
Introduction: Operating System as a resource manager, operating system classification,
system calls, traps, architectures for operating systems.
Device Management: Goals of I/O software, Design of device drivers.
Processor Management: Process overview, process states and state transition, multiprogramming,multi-tasking, levels of schedulers and scheduling algorithms. Process Synchronization – Critical section and mutual exclusion problem, classical synchronization
problems, deadlock prevention. Multithreading
Memory Management: Classical memory management techniques, paging, segmentation,
File Management: Overview of file management system, disk space management, directory
structures. Protection domains, access control lists, protection models.
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