SOE Archive

Question Papers

• 2024
• CIE

Notes

• Introduction: meaning, nature and characteristics of management, scope and functional areas of management, goals of management, levels of management, brief overview of evolution of management theories, Planning- Nature, importance, types of plans, steps in planning, Organizing- nature and purpose, types of organization, Staffing- meaning, process of recruitment and selection.

  Module 1

• Directing and Controlling: meaning and nature of directing, leadership styles, motivation theories, Communication- meaning and importance, Coordination- meaning and importance, Controlling- meaning, steps in controlling, methods of establishing control.

  Module 2

• Project Management: Project/Program/Portfolio Management, Phases in Project Life Cycle, Top Down and Bottoms up Estimation, WBS, Stake Holder Management. Identification of new ideas, Evaluation of Alternatives.
  
  Human Resource Management: Functions of HRM, Recruitment and Selection, Interviewing Candidates. Human Resource Development, Training and Development, Performance Appraisal and Employee Compensation

  Module 3

• Marketing Management: Introduction, 5 Ps of Marketing, product life cycle, market Strategy.
  
  Financial Management: Introduction, Types of Finance, Balance Sheet and Profit and Loss account statement, working capital, International Finance

  Module 4

• Entrepreneurship: Introduction, Management & Administration, Types of ownership and Organization structures. Concept of Entrepreneur, kind of Entrepreneurs, Entrepreneurship development and Govt. support in India. Role of Entrepreneurs in Economic Development.
  
  Micro and Small Enterprises: Definition of micro and small enterprises, characteristics and advantages of micro and small enterprises, steps in establishing micro and small enterprises, Introduction to IPR.

  Module 5

Question Papers

• 2024
• CIE

Notes

• Introduction to Java: Basics of Java programming, Data types, Variables, Operators, Control structures including selection, Looping, Java methods, Overloading, Math class, Arrays in java, Java Is a Strongly Typed Language, The Primitive Types, Integers, Floating-Point Types, Characters, Booleans, A Closer Look at Literals, Type Conversion and Casting, Automatic Type Promotion in Expressions, A Few Words About Strings

  Module 1

• Objects and Classes: Basics of objects and classes in java, Constructors, Finalizer, Visibility modifiers, Methods and objects, Inbuilt classes like String, Character
  
  Operators: Arithmetic Operators, The Bitwise Operators, Relational Operators, Boolean Logical Operators, The Assignment Operator, The ? Operator, Operator Precedence, Using Parentheses.
  
  Control Statements: Java’s Selection Statements, Iteration Statements, Jump Statements.

  Module 2

• Event and GUI programming: Event handling in java, Event types, Mouse and key events, GUI Basics, Panels, Frames, Layout Managers: Flow Layout, Border Layout, Grid Layout, GUI components like Buttons, Check Boxes, Radio Buttons, Labels, Text Fields, Text Areas, Combo Boxes, Lists, Scroll Bars, Sliders, Windows, Menus, Dialog Box, Applet and its life cycle.

  Module 3

• Packages and Interfaces: Packages, Access Protection, Importing Packages, Interfaces.
  
  Exception Handling: Exception-Handling Fundamentals, Exception Types, Uncaught Exceptions, Using try and catch, Multiple catch Clauses, Nested try Statements, throw, throws, finally, Java’s Built-in Exceptions, Chained Exceptions, Using Exceptions.

  Module 4

• I/O Programming: Text and Binary I/O, Binary I/O classes, Object I/O, Random Access Files.
  
  Multithreading in Java: Thread life cycle and methods, Runnable interface, Thread synchronization, Exception handling with try-catch-finally, Collections in java, Introduction to JavaBeans.

  Module 5

Question Papers

• 2024
• CIE

Notes

• Introduction to Databases: Introduction, Characteristics of database approach, Advantages of using the DBMS approach, History of database applications.
  
  Overview of Database Languages and Architectures: Data Models, Schemas and Instances. Three schema architecture, Data independence, Database languages and interfaces, The Database System Environment.
  
  Conceptual Data Modelling using Entities and Relationships: Entity types, Entity sets, Attributes, Roles and Structural constraints, Weak entity types, ER diagrams, Examples.

  Module 1

• Relational Model: Relational Model Concepts, Relational Model Constraints and Relational database schemas, Update operations, Transactions, and dealing with constraint violations.
  
  Relational Algebra: Unary and Binary relational operations, additional relational operations (aggregate, grouping, etc.) Examples of Queries in relational algebra.
  
  Mapping Conceptual Design into a Logical Design: Relational Database Design using ER-to-Relational mapping.

  Module 2

• SQL: SQL data definition and data types, specifying constraints in SQL, retrieval queries in SQL, INSERT, DELETE, and UPDATE statements in SQL, Additional features of SQL.
  
  Advances Queries: More complex SQL retrieval queries, Specifying constraints as assertions and action triggers, Views in SQL, Schema change statements in SQL.
  
  Database Application Development: Accessing databases from applications, An introduction to JDBC, JDBC classes and interfaces, SQLJ, Stored procedures, Case study: The internet Bookshop.

  Module 3

• Normalization: Database Design Theory – Introduction to Normalization using Functional and Multivalued Dependencies, Informal design guidelines for relation schema, Functional Dependencies, Normal Forms based on Primary Keys, Second and Third Normal Forms, Boyce-Codd Normal Form, Multivalued Dependency and Fourth Normal Form, Join Dependencies and Fifth Normal Form. Examples on normal forms.
  
  Normalization Algorithms: Inference Rules, Equivalence, and Minimal Cover, Properties of Relational Decompositions, Algorithms for Relational Database Schema Design, Nulls, Dangling tuples, and Alternate relational designs.

  Module 4

• Transaction Processing: Introduction to Transaction Processing, Transaction and System Concepts, Desirable Properties of Transactions, characterizing schedules based on recoverability, characterizing schedules based on Serializability, Transaction support in SQL.
  
  Concurrency Control in Databases: Two-phase locking techniques for Concurrency control, Concurrency control based on Timestamp ordering, Multiversion Concurrency control techniques, Validation Concurrency control techniques, Granularity of Data items and Multiple Granularity Locking.

  Module 5

Question Papers

• 2024
• CIE

Notes

• Why study the Theory of Computation, Languages and Strings: Strings, Languages. A Language Hierarchy, Computation.
  
  Finite State Machines (FSM): Deterministic FSM, Regular languages, Designing FSM, Nondeterministic FSMs, From FSMs to Operational Systems, Simulators for FSMs, Minimizing FSMs, Canonical form of Regular languages, Finite State Transducers, Bidirectional Transducers.

  Module 1

• Regular Expressions (RE): what is a RE, Kleene‟s theorem, Applications of REs, Manipulating and Simplifying REs. Regular Grammars: Definition, Regular Grammars and Regular languages. Regular Languages (RL) and Non-regular Languages: How many RLs, to show that a language is regular, Closure properties of RLs, to show some languages are not RLs.

  Module 2

• Context-Free Grammars (CFG): Introduction to Rewrite Systems and Grammars, CFGs and languages, designing CFGs, simplifying CFGs, proving that a Grammar is correct, Derivation and Parse trees, Ambiguity, Normal Forms.
  Pushdown Automata (PDA): Definition of non-deterministic PDA, Deterministic and Non-deterministic PDAs, Non - determinism and Halting, alternative equivalent definitions of a PDA, alternatives that are not equivalent to PDA.

  Module 3

• Algorithms and Decision Procedures for CFLs: Decidable questions, Un-decidable questions. Turing Machine: Turing machine model, Representation, Language acceptability by TM, design of TM, Techniques for TM construction. Variants of Turing Machines (TM), The model of Linear Bounded automata.

  Module 4

• Decidability: Definition of an algorithm, decidability, decidable languages, Undecidable languages, halting problem of TM, Post correspondence problem. Complexity: Growth rate. of functions, the classes of P and NP, Quantum
  Computation: quantum computers, Church-Turing thesis.
  Applications: G.1 Defining syntax of programming language, Appendix J: Security

  Module 5

Question Papers

• 2024
• CIE

Notes

• Systems and complexity, fundamental abstractions, naming introduction, Names and layers, Unix file system case study, Client/service modularity, NFS case study.

  Module 1

• Virtualization abstractions-Threads Virtual Memory Bounded Buffer Operating System Interface, virtual links-An Interface for SEND and RECEIVE with Bounded Buffers Sequence Coordination with a Bounded Buffer Race Conditions Locks and Before-or-After Actions Deadlock Implementing ACQUIRE and RELEASE, Memory modularity, virtual memory Virtual processor threads

  Module 2

• Designing for performance-Performance Metrics Capacity, Utilization, Overhead, and Useful Work Latency Throughput, scheduling-Scheduling Resources Scheduling metrics Scheduling Policies First-Come, First-Served Shortest-job-first Round-Robin Priority Scheduling

  Module 3

• Network properties- Isochronous and Asynchronous Multiplexing Packet Forwarding; Delay Buffer Overflow and Discarded Packets Duplicate Packets and Duplicate Suppression Damaged Packets and Broken Links Reordered Delivery, network layers-Addressing Interface Managing the Forwarding Table: Routing Hierarchical Address Assignment and Hierarchical Routing Reporting Network Layer Errors Network Address Translation.

  Module 4

• Network case studies-Case Study: Mapping the Internet to the Ethernet, fault tolerance-Faults, Failures and Modules. The Fault-Tolerance Design Process. Redundancy-Systematically Applying Redundancy, Atomicity-All-or-Nothing Atomicity in a Database All-or-Nothing Atomicity in the Interrupt Interface

  Module 5

Question Papers

• 2024
• CIE

Notes

• Introduction to HTML: What is HTML and Where did it come from?, HTML Syntax, Semantic Markup, Structure of HTML Documents, Quick Tour of HTML Elements, HTML5 Semantic Structure Elements, Introduction to CSS, What is CSS, CSS Syntax, Location of Styles, Selectors, The Cascade: How Styles Interact, The Box Model, CSS Text Styling

  Module 1

• HTML Tables and Forms: Introducing Tables, Styling Tables, Introducing Forms, Form Control Elements, Table and Form Accessibility, Microformats, Advanced CSS: Layout, Normal Flow, Positioning Elements, Floating Elements, Constructing Multicolumn Layouts, Approaches to CSS Layout, Responsive Design, CSS Frameworks

  Module 2

• JavaScript: Client-Side Scripting, what is JavaScript and What can it do? JavaScript Design Principles, Where does JavaScript Go?, Syntax, JavaScript Objects, The Document Object Model (DOM), JavaScript Events, Forms, Introduction to Server-Side Development with PHP, What is Server-Side Development, A Web Server’s Responsibilities, Quick Tour of PHP, Program Control, Functions.

  Module 3

• PHP: Arrays and Superglobals, Arrays, $_GET and $_POST Superglobal Arrays, $_SERVER Array, $_Files Array, Reading/Writing Files, PHP Classes and Objects, Object-Oriented Overview, Classes and Objects in PHP, Object Oriented Design, Error Handling and Validation, What are Errors and Exceptions?, PHP Error Reporting, PHP Error and Exception Handling

  Module 4

• Managing State: The Problem of State in Web Applications, Passing Information via Query Strings, Passing Information via the URL Path, Cookies, Serialization, Session State, HTML5 Web Storage, Caching, Advanced JavaScript and jQuery, JavaScript Pseudo-Classes, jQuery Foundations, AJAX, Asynchronous File Transmission, Animation, Backbone MVC Frameworks, XML Processing and Web Services, XML Processing, JSON, Overview of Web Services

  Module 5

Question Papers

• 2024
• CIE

Notes

• Module 1
• Module 2
• Module 3
• Module 4
• Module 5

• Module 1
  

  Introduction to Linear Programming: Introduction, The origin, nature and impact of OR; Defining the problem and gathering data; Formulating a mathematical model; Deriving solutions from the model; Testing the model; Preparing to apply the model; Implementation.
  
  Introduction to Linear Programming Problem (LPP): Prototype example, Assumptions of LPP, Formulation of LPP and Graphical method various examples.

• Module 2
  

  Simplex Method – 1: The essence of the simplex method; Setting up the simplex method; Types of variables, Algebra of the simplex method; the simplex method in tabular form; Tie breaking in the simplex method, Big M method, Two phase method

• Module 3
  

  Simplex Method – 2: Duality Theory - The essence of duality theory, Primal dual relationship, conversion of primal to dual problem and vice versa. The dual simplex method

• Module 4
  

  Transportation and Assignment Problems: The transportation problem, Initial Basic Feasible Solution (IBFS) by North West Corner Rule method, Matrix Minima Method, Vogel’s Approximation Method. Optimal solution by Modified Distribution Method (MODI). The Assignment problem; A Hungarian algorithm for the assignment problem. Minimization and Maximization varieties in transportation and assignment problems.

• Module 5
  

  Game Theory: The formulation of two persons, zero sum games; saddle point, maximin and minimax principle, Solving simple games - a prototype example; Games with mixed strategies; Graphical solution procedure.

• Module 1
  

  Introduction: Significance of simulation and modelling, Advantages and disadvantages of Simulation; Areas of application, Systems and system environment; Components of a system; Discrete and continuous systems, Model of a system; Types of Models, Discrete-Event System Simulation, Simulation examples: Simulation of queuing systems.
  
  General Principles, Simulation Software: Concepts in Discrete-Event Simulation. The Event-Scheduling/Time-Advance Algorithm, Manual simulation Using Event Scheduling

• Module 2
  

  Statistical Models in Simulation: Review of terminology and concepts, Useful statistical models, Discrete distributions. Continuous distributions, Poisson process, Empirical distributions.
  
  Queuing Models: Characteristics of queuing systems, Queuing notation, Long-run measures of performance of queuing systems, Long-run measures of performance of queuing systems, Steady-state behaviour of M /G/1 queue, Networks of queues,

• Module 3
  

  Random-Number Generation: Properties of random numbers; Generation of pseudo-random numbers, Techniques for generating random numbers, Tests for Random Numbers, Random-Variate Generation: Inverse transform technique, Acceptance-Rejection technique.

• Module 4
  

  Input Modelling: Data Collection; Identifying the distribution with data, Parameter estimation, Goodness of Fit Tests, fitting a non-stationary Poisson process, selecting input models without data, Multivariate and Time-Series input models.
  
  Estimation of Absolute Performance: Types of simulations with respect to output analysis, Stochastic nature of output data, Measures of performance and their estimation

• Module 5
  

  Measures of performance and their estimation: Output analysis for terminating simulations, Output analysis for steady-state simulations.
  
  Verification, Calibration and Validation: Optimization: Model building, verification and validation, Verification of simulation models, Verification of simulation models, Calibration and validation of models, Optimization via Simulation.

• Module 1
  

  Introduction to C: Constants, variables, data types, input output operations, operators and expressions, control statements, arrays, strings, string handling functions, structures, unions and pointers, Dynamic Memory Allocation.

• Module 2
  

  Algorithms: Introduction to algorithms, Performance Analysis: Estimating Space complexity and Time complexity of algorithms, Asymptotic notations, Introduction to data structures, Types of data structures.

• Module 3
  

  Stacks: Definition, Stack Operations, Array Representation of Stacks, Stack Applications: Polish notation, Infix to postfix conversion, evaluation of postfix expression.
  
  Queues: Definition, Array Representation, Queue Operations, Circular Queues, Deque, Priority Queues

• Module 4
  

  Linked Lists: Definition, Representation of linked lists in Memory, Singly linked list, Doubly linked lists, Circular linked lists.
  
  Trees: Terminology, Binary Trees, Array and linked Representation of Binary Trees, Binary Tree Traversals, Threaded binary trees, Binary Search Trees, Expression Tree

• Module 5
  

  Graphs: Definitions, Terminologies, Matrix and Adjacency List Representation of Graphs, Graph Traversal methods: Breadth First Search and Depth First Search
  Hashing: Hash Table organizations, Hashing Functions.
  Files and Their Organization: Data Hierarchy, File Attributes Text Files and Binary Files, Basic File Operations.

• Module 1
  

  Introduction to Databases: Introduction, Characteristics of database approach, Advantages of using the DBMS approach, History of database applications.
  
  Overview of Database Languages and Architectures: Data Models, Schemas, and Instances. Three schema architecture and data independence, database languages, and interfaces, The Database System environment.

• Module 2
  

  Relational Model: Relational Model Concepts, Relational Model Constraints and relational database schemas, Update operations, transactions, and dealing with constraint violations.
  
  Mapping Conceptual Design into a Logical Design: Relational Database Design using ER-to-Relational mapping

• Module 3
  

  Relational Algebra: Selection and projection set operations, renaming, joins, division, Examples of algebra over views.
  
  Relational calculus: Tuple relational calculus, Domain relational calculus.
  
  Overview of the SQL Query Language: Basic Structure of SQL Queries, Set Operations, Aggregate Functions – GROUPBY, HAVING, Nested Sub queries, Views, Triggers.

• Module 4
  

  Normalization: Introduction to Normalization using Functional and Multivalued Dependencies: Informal design guidelines for relation schema, Functional Dependencies, Normal Forms based on Primary Keys, Second and Third Normal Forms, Boyce-Codd Normal Form, Multivalued Dependency and Fourth Normal Form, Join Dependencies and Fifth Normal Form. Examples on normal forms.

• Module 5
  

  Transaction Processing: Introduction to Transaction Processing, Transaction and System concepts, Desirable properties of Transactions, characterizing schedules based on recoverability, characterizing schedules based on Serializability,
  Concurrency Control in Databases: Two-phase locking techniques for Concurrency control, Concurrency control based on Timestamp ordering, Multiversion Concurrency control techniques.

• Module 1
  

  Introduction, goals of AI, Types of AI, Types of agents, Intelligent Agent, Agent environment, Turing Test and Chatterbots, AI and Society, Applications of AI, Advantages, Disadvantages.

• Module 2
  

  Propositional Logic – Syntax, Semantics, Proof Systems, Resolution, Horn Clauses, Computability and Complexity, Applications and Limitations. First Order Predicate logic – Syntax, Semantics, Quantifiers and Normal Forms, Proof Calculi, Resolution, Automated Theorem Provers, Mathematical Examples, Applications. Limitations of Logic – The Search Space Problem, Decidability and Incompleteness, Modelling Uncertainty.

• Module 3
  

  Knowledge representation: Knowledge based agent in AI, Architecture of knowledge based agent, Inference system, Operations performed by KBA, Generic KBA, Levels of KBA, approaches to design KBA, Types of Knowledge, Relationship between knowledge and Intelligence, AI knowledge cycle, Approaches to knowledge representation, Requirements for knowledge representation system, Techniques for knowledge representation.

• Module 4
  

  Search algorithms: Properties of search algorithms, Types of search algorithms - Uninformed search algorithm, Informed search algorithms, Hill climbing algorithm, Means-Ends analysis, Adversarial search, Min-Max algorithm, Alpha-Beta pruning.

• Module 5
  

  AI Applications, Expert Systems Learning, Language Models, Information Retrieval, Information Extraction, Natural Language Processing, Machine Translation, Speech Recognition, Robot – Hardware, Perception, Planning, Moving.

• Module 1
  

  Introduction data, expressions, statements: Introduction: Creativity and motivation, understanding programming, Terminology: Interpreter and compiler, Running Python, The First Program; Data types: Int, float, Boolean, string, and list, variables, expressions, statements, Operators and operands.

• Module 2
  

  Control Flow, Loops: Conditionals: Boolean values and operators, conditional (if), alternative (if-else), chained conditional (ifelif-else); Iteration: while, for, break, continue, pass statement.

• Module 3
  

  Functions and strings: Functions: Function calls, adding new functions, definition and uses, local and global scope, return values.
  Strings: strings, length of string, string slices, immutability, multiline comments, string functions and methods;

• Module 4
  

  Lists, Tuples, Dictionaries Lists: List operations, list slices, list methods, list loop, mutability, aliasing, cloning lists, list parameters, List Comprehension;
  Tuples: tuple assignment, tuple as return value, tuple comprehension; Dictionaries: operations and methods, comprehension;

• Module 5
  

  Regular expressions, files and exception: Regular expressions, Character matching in regular expressions, extracting data using regular expressions, Escape character
  Files and exception: Text files, reading and writing files, command line arguments, errors and exceptions, handling exceptions, modules