Scheme of examination for master of computer applications (M. C. A.)
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- MCA -16 -33 PROGRAMMING IN JAVA Maximum marks: 100 (External: 75, Internal: 25) Time: 3 hours Credits: 4
- MCA-16-34 THEORY OF COMPUTATION Maximum marks: 100 (External: 75, Internal: 25) Time: 3 hours Credits: 4
- MCA-16-35 OBJECT ORIENTED ANALYSIS AND DESIGN USING UML Maximum marks: 100 (External: 75, Internal: 25) Time: 3 hours Credits: 4
- MCA-16-41 design and analysis of algorithms Maximum marks: 100 (External: 75, Internal: 25) Time: 3 hours Credits: 4
- MCA -16 -42 compiler design Maximum marks: 100 (External: 75, Internal: 25) Time: 3 hours Credits: 4
- MCA -16 -43 data warehousing and mining Maximum marks: 100 (External: 75, Internal: 25) Time: 3 hours Credits: 4
- MCA -16 -44 COMPUTER GRAPHICS Maximum marks: 100 (External: 75, Internal: 25) Time: 3 hours Credits: 4
Text Books:
Reference Books:
CENGAGE learning.
MCA-16-33 PROGRAMMING IN JAVA Maximum marks: 100 (External: 75, Internal: 25) Time: 3 hours Credits: 4 Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks. Objectives: The objective of this course is to provide the detailed coverage of various concepts of JAVA programming language. It prepares the students for the software-industry as Java is one of the most popular languages in software-industry. Learning Outcomes: At the end of this course students should be able to:
UNIT – I Java History: Java features, How Java differs from C++, Java Program Structure, Java Tokens, , Java virtual machine, Constants, variables and data types, operators & expressions, control structures, arrays, class & object, garbage collection , finalize () method, Inheritance, method overriding, Abstract class, Multiple inheritance, Interfaces, extending Interfaces, Accessing Interface variables. UNIT – II Packages, Exception Handling & Multithreading: API Packages, Creating packages, Accessing a package, Adding a class to a package, use of super and final keywords, Wrapper classes, Exception types, uncaught exceptions, multiple catch clauses, nested try statements, built-in exceptions, creating your own exceptions, Multithreading; Java thread model, thread priorities, threads synchronization, thread suspending, resuming and stopping threads. UNIT – III I/O Streams & Applet: Console I/O – reading console input, writing console output, Files I/O-Byte Streams, Character Streams, Collection of inbuilt Interfaces & Classes, Applet programming, Applet life Cycle, creating executable Applet, Applet Tag, Running an applet, passing parameters to applet, Graphics programming, GUI Concepts in Java, managing Input/Output in Applet. UNIT – IV Event Handling: AWT Classes, AWT Button, AWT Label, AWT TextField, AWT TextArea, AWT Checkbox, Event Listeners, Java ActionListener, Java MouseListener, MouseMotionListener, Adapter Classes as Helper Classes in Event Handling. Layout managers- Grid Layout, Flow Layout, Card Layout, Border Layout, Menus. Text Books:-
Reference Books:- 1. Exploring Java: Patrick Nieaneyer and Joshna Peck O, Reilley S Associates, Inc. 2. Programming with JAVA, A Primer. E. Balaguruswamy Publisher: Tata Mc-Graw Hill publication. 3. Hareliy Hahn Teacher the Internets, 1999 By Harley Hahn, P.H.I. 4. Java 2 exam Guide: Barry Boone / William Stanck Tata Mc-Graw Hill. MCA-16-34 THEORY OF COMPUTATION Maximum marks: 100 (External: 75, Internal: 25) Time: 3 hours Credits: 4 Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks. Objectives: The objective of this course is to provide the in-depth coverage of theoretical computer science. It provides an insight about design of all types machines and their applications. Learning Outcomes: At the end of this course students should be able to:
UNIT– I Finite State Machines: Finite Automata, Designing of DFA and NDFA, NFA with E-Transitions, Equivalence of DFA and NFA with proof, Regular Expressions and Regular languages, Laws of Regular Expressions, Kleene’s Theorem 1 and 2, Properties and Limitations of FSM, FSM with Output: Moore and Mealy Machines, Arden’s Theorem with proof, Closure Properties of Regular Sets, Pumping Lemma for Regular Grammers, Myhill-Nerode Theorem, Minimization of FA. UNIT – II Formal Grammars: Definition, Construction of Context Free Grammar, Derivation, Parse Trees, Ambiguity, Removal of Ambiguity, Simplification of Context Free Grammar, CNF and GNF, Closure properties of CFL, Pumping Lemma for CFL. Pushdown Automaton: Introduction, Types of PDA, Designing of PDA’s, Conversion from PDA to CFG and vice-versa, Applications, Parsing: Early's, Cook-Kasami-Young, Tomito's.
Linear Bounded Automata (LBA), Turing Machines (TM), variants of TM: Multitape, Restricted and Universal TM; TM and Computers. Recursive and recursively-enumerable languages and Properties. Decidability: Post’s correspondence problem, Rice's theorem, Cook’s Theorem, decidability of membership, emptiness and equivalence problems of languages.
Decidable languages and problems, Halting problem of TM, Diagonalization method, Turing machines and other undecidable problems. Computable Functions: Primitive recursive functions, Recursion theorem. Russels’s Paradox, Tractable and Intractable problems, Computability and Non-computability and examples of non-computable problems.
1. John C. Martin, “Introduction to languages and the theory of computation”, McGraw Hill. 2. Peter Linz, “An introduction to formal language & automata”, Jones & Bartlett publications.
1. Hopcroft, J. E. & Ullman, J. D., “Formal languages and their relation to Automata”, Pearson Education. 2. Lewis, H.R. & Papadimitrious, C.H., “Elements of the theory of computation”. PHI Learning. 3. Michael Sipser, “Introduction to the Theory of Computation”, Cengage Learning. MCA-16-35 OBJECT ORIENTED ANALYSIS AND DESIGN USING UML Maximum marks: 100 (External: 75, Internal: 25) Time: 3 hours Credits: 4 Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks. Objectives: Object Oriented Analysis and Design Using UML course provides instruction and practical experience focusing on the effective use of object -oriented technologies and the judicious use of software modeling as applied to a software development process.
UNIT-I UML: Principles of modeling, UML Things – Structural, Behavioral, Grouping, Annotational. Relationships in UML – Dependency, Association, Generalization, Realization. Overview of diagrams in UML – Class diagram, Object diagram, Use-Case diagram, Sequence diagram, Collaboration diagram, Statechart diagram, Activity diagram, Component diagram, Deployment diagram. UML Semantic Rules – Names, Scope, Visibility, Integrity, Execution. Mechanisms in the UML – Specifications, Adornments, Common Divisions, Extensibility Mechanisms. UNIT-II Modeling as a Design Technique: Abstraction, Encapsulation, Modularity, Hierarchy, Typing, Concurrency, Persistence of objects. Purpose of modeling, Class Model – Object & Class, Links & Associations, Generalization & Inheritance, Association Ends - Multiplicity, Role names, Ordering, Qualification, Aggregation, Link attributes & Link class, Abstract class, Metadata, Constraints. Constructing class diagram.
State Modeling: Event, State, Activity, Action, Transitions & Conditions, State diagrams, Nested state diagrams, signal generalization, concurrency, relationships between class and state models. Interaction Modeling: use case models, use case relationships, sequence models, procedural sequence models, activity models, special constructs for activity models.
System Analysis & design: System development stages, system conception, analysis, domain class model, domain state model, iterating the analysis. Application interaction model, application class model, application state model, adding operations System Design: estimating performance, make a reuse plan, organize the system into subsystem, identifying concurrency, allocating subsystems to processors and tasks, management of data stores, handling global resources, choosing software control strategies, handling boundary conditions, setting trade-off priorities, selecting an architect style. Class Design: bridging gap, realize use cases with operations, designing algorithms, design optimization, adjustment of inheritance, organize classes & associations.
Reference Books:
MCA-16–38 SEMInar Maximum marks: 50 Time: 1/2 hours CREDITS: 1 Seminar Each student shall individually prepare and submit a seminar report within stipulated time. A panel consisting of two teachers (internal) should evaluate the seminar report and the presentation. Marks should be distributed considering report writing, presentation, technical content, depth of knowledge, brevity and references and their participation in seminar. The time allotted for presentation will be 30 minutes. MCA-16-41 design and analysis of algorithms Maximum marks: 100 (External: 75, Internal: 25) Time: 3 hours Credits: 4 Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks. Objectives: The objective of this course is to provide the in-depth coverage of various algorithm design techniques. It focuses on various problems and their solutions using different algorithm design techniques. Learning Outcomes: At the end of this course students should be able to:
UNIT – I Introduction: Algorithms, Role of algorithms in computing, Complexity of algorithms, Analyzing algorithms, designing algorithms, asymptotic notations. Divide and Conquer: Complexity of iterative programs and recursive programs, solving recurrence equations: back substitution method, recursion tree method, masters theorem. Analysis of heap sort and quick sort; Counting sort, Radix sort, Bucket sort, Lower bounds for sorting. UNIT – II Hash Tables, Hash functions, Collision handling in hashing, analyzing various operations on Binary search tree. Introduction to Red-black trees. Dynamic Programming (DP): Elements of DP, Matrix chain multiplication, Longest common subsequence, optimal binary search trees.
Greedy Techniques (GT): Elements of GT, Activity selection problem, Huffman codes, Knapsack Problem. Graph Algorithms: Single source shortest path: Analysis of Dijkstra’s Algorithm, Limitations of Dijkstra’s Algorithm, Negative weight cycle, Bellman-Ford algorithm. All Pairs Shortest Path: Relation of Shortest path and matrix multiplication, Analysis of Floyd Warshall algorithm. Maximum Flow: Flow network, Ford-Fulkerson method.
Strings: Storage of strings, naive string-matching algorithm, Rabin-Karp string matching algorithm. Computational complexity: Notion of Polynomial time algorithms, Complexity classes: P, NP, NP-Hard and NP-Complete, Polynomial time verification, Reducibility, NP-Completeness, Examples of NP-Complete and NP-Hard problems: Traveling Salesman Problem, Knapsack, Bin Packing, Satisfiability, Vertex Cover, Clique, Independent Set.
Reference Books:
MCA-16-42 compiler design Maximum marks: 100 (External: 75, Internal: 25) Time: 3 hours Credits: 4 Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks. Objectives: The objective of the course is to provide in-depth coverage of underlying concepts & techniques used in compiler design and to cover major topics in compilation Theory. This course will make students ready for job assignments involving compilers and prepare students to undertake projects on compilers Construction. Learning Outcomes: At the end of course the students should be able:
Unit – I Compilers and Translators, Need of Translators, Tools used for compilation, Structure and Phases of Compiler, Single-Pass and Multi-Pass Compilers, Bootstrapping, Compiler Construction Tools, Phases of Compilation process, Classification of grammars Lexical Analysis: Design, Finite Automata and Regular Expressions, Process of Lexical Analysis, Lexical Analyzer generators, Derivations and parse trees
Parsing Techniques: Top down Parsing- Predictive Parsers, Left Recursion and its removal, Recursive Descent Parsers, LL Grammars Bottom-up parsing: Shift Reduce Parsing, Operator Precedence Parsing, LR Parsers, LR grammars, Comparison of parsing methods, Parser Generators
Semantic Analysis: Syntax-Directed Translation Schemes Building Symbol Table, Data Structures for symbol table, representing scope information An overview of Run-time Storage Administration Error Detection and Recovery: Errors, Lexical-Phase Errors, Syntactic Phase Errors, Semantic Errors.
Intermediate Source Forms: Postfix Notation, Syntax Trees, Triples & Quadruples Code Optimization: Potential cases of Code Optimization, Optimization of basic blocks, Local and Global optimizations, Code Improving Transformation Code Generator: Issues in the design of a code generator Text Books 1. Alfred V Aho, “Principles of Compiler Design”, Narosa Publishing House. 2. Jean Paul Tremblay and Sorenson, “The Theory and Practice of Compiler Writing”, McGraw Hill.
1. Dhamdhere D.M, “System programming and operating system”, McGraw Hill. 2. Beck L. Leland, “System Software”, Pearson Education. 3. Aho, Sethi, & Ullman, “Compilers Principles, Techniques and Tools”, Pearson Education. 4. Fischer, “Crafting a compiler in C”, Pearson Education.
Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks. Objectives: The objective of this course is to provide the in- depth coverage of fundamentals of data warehousing and mining. It focus on various concepts of data warehousing like architecture, multidimensional model, data generation by attribute etc. It deals with gathering and analyzing large sets of data, identifying applications of data mining and to discuss next generation technique of data mining. Learning Objective: At the end of this course students should be able to:
UNIT – I Data Warehouse: Basic concepts, The Data Warehouse - A Brief History, Characteristics, Difference between Operational Database Systems and Data Warehouse, Architecture for a Data Warehouse, Fact and Dimension Tables, Data Warehouse Schemas, Data Cube : A Multidimensional Data Model, Data Cube Computation Methods, Typical OLAP Operations, Data Warehouse Design and Usage, Data Warehouse Implementation, Data Generalization by Attribute Oriented Induction. UNIT – II Data Mining: Introduction: Motivation, Importance, Knowledge Discovery Process, Data Mining Functionalities, Interesting Patterns, Classification of Data Mining Systems, Major issues, Data Objects and Attribute Types. Data Preprocessing: Overview, Data Cleaning, Data Integration, Data Reduction, Data Transformation and Data Discretization. Data Mining Models: Directed Data Mining Models, Directed Data Mining Methodology. Data Visualization. Outliers, Types of Outliers and Challenges of Outlier Detection. UNIT – III Data Mining Classical Techniques: Statistics – Similarity Models, Steps for Designing Similarity Models, Table Lookup Model. Clustering- Requirement for Cluster Analysis, Clustering Methods- Partitioning Methods, Hierarchical Methods, Density-Based Methods, Grid-Based Methods, Evaluation of Clustering. Nearest Neighborhood- Memory Based Reasoning, Challenges of Memory Based Reasoning, UNIT – IV Data Mining Next Generation Techniques: Decision Tree- Decision Tree Induction, Attribute Selection Measures, Tree Pruning. Association Rule Mining- Market Basket Analysis, Frequent Itemset Mining using Apriori Algorithm, Improving the Efficiency of Apriori, Neural Network- Bayesian Belief Networks, Classification by Backpropagation. Data Mining Applications, Data Mining Trends and Tools. Reference Books: 1. J Hanes, M. Kamber, “Data Mining Concepts and Techniques”, Elsevier India. 2. G.S. Linoff, M.J.A. Berry, “Data Mining Techniques”, Wiley India Pvt. Ltd. 3. A. Berson, S.J. Smith, “Data Warehousing, Data Mining & OLAP”, Tata McGraw-Hill. MCA-16-44 COMPUTER GRAPHICS Maximum marks: 100 (External: 75, Internal: 25) Time: 3 hours Credits: 4 Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks. Yüklə 0,49 Mb. Dostları ilə paylaş:
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