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Tuesday, September 2, 2025

General Information Technology (GIT) G.C.E. A/L English Medium Syllabus Download Notes Classes Questions and Answers

G.C.E. A/L GIT Syllabus – Competency 1 & 2

📘 G.C.E. A/L – General Information Technology (GIT) Syllabus

Competency 1 — Explores the computer and its potential

1.1 Describes the computer as a system using a block diagram (02 Periods)

System concept; introduction to computers
Components:
- Hardware: input/output devices, memory, storage devices (optical, magnetic, semiconductor), processor
- Software: system software (operating system, utilities), application software
Block diagram: input, processing unit (ALU, CU), output, memory/storage; data/control flow
Data & Information; attributes of quality information

Learning Outcomes:

Define a system
Identify the computer as an IPO system
Identify a computer as a component of a larger system
List and describe hardware components
Classify peripherals as input/output/I-O devices
List types of software
Draw and label a computer block diagram
Describe the function of each component
Distinguish between data and information with examples
Name and describe attributes of quality information

1.2 Identifies the specifications of personal computers (01 Period)

Learning Outcomes:

Select PC specifications according to requirements and affordability
Prepare specifications for a computer and its peripherals
Select suitable software based on user requirements (compatibility, support, licensing)
Ensure security: antivirus, anti-malware, firewall

Competency 2 — Explores the representation of data inside a computer

2.1 Data representation and fundamental concepts (02–03 Periods)

Learning Outcomes:

Describe number systems with base, place value, weight
Identify uses of number systems in computing (e.g., RGB, hex)
Convert between decimal and binary

2.2 Basic Boolean operators (01 Period)

Learning Outcomes:

Draw truth tables for AND, OR, NOT operators
Draw truth tables for given simple Boolean expressions

2.3 Character encoding systems (01 Period)

Learning Outcomes:

Explain the need for encoding characters
Compare ASCII and Unicode
Demonstrate ASCII codes with examples
Demonstrate Unicode input in local languages

Competency 3 — Explores the Operating System and its Functions

3.1 Identifies the role of an Operating System (01 Period)

Learning Outcomes:

Define an OS
List the major functions of an OS
Differentiate between CLI and GUI with examples
Classify OS types with examples

3.2 Uses functions of an Operating System (02 Periods)

Basic OS operations:
- Managing files & folders (create, copy, move, delete)
- Working with drives & removable media
- Compression & decompression of files
OS tools and utilities:
- System information
- Task manager
- Disk cleanup & defragmentation
Customizing desktop & taskbar
Installing/uninstalling software
Managing user accounts & privileges

Learning Outcomes:

Use OS tools to manage files/folders
Perform file compression and decompression
Use system utilities to manage system resources
Install and uninstall software applications
Customize desktop environment
Manage user accounts and privileges

Competency 4 — Explores Word Processing, Spreadsheets, and Presentation Tools

4.1 Uses a Word Processor to create professional documents (04 Periods)

Learning Outcomes:

Create, edit, and format a document using a word processor
Insert tables, images, charts, and objects
Use proofing tools effectively
Apply styles and templates
Perform a mail merge
Prepare a document for printing with proper layout

4.2 Uses Spreadsheet software for data organization and analysis (04 Periods)

Learning Outcomes:

Create and format spreadsheets
Apply formulas and functions to solve problems
Use relative and absolute cell references
Organize and analyze data using sorting and filtering
Create and customize charts and graphs
Use conditional formatting to highlight data

4.3 Uses Presentation software to prepare presentations (02 Periods)

Learning Outcomes:

Create and design a presentation with slides
Insert multimedia elements
Apply transitions and animations
Prepare handouts and speaker notes
Deliver a professional presentation

Competency 5 — Explores Database Management Systems (DBMS)

5.1 Explains the concept of databases and DBMS (02 Periods)

Learning Outcomes:

Define database and DBMS
Differentiate between database and file system
List advantages of DBMS
Identify types of DBMS users

5.2 Explains data models with emphasis on relational model (02 Periods)

Learning Outcomes:

Describe the relational model
Identify entities, attributes, and relationships
Explain primary and foreign keys
Draw simple relational diagrams

5.3 Uses DBMS software to manage data (04 Periods)

Learning Outcomes:

Create databases and tables using DBMS
Define fields with appropriate data types
Insert, edit, and delete records
Retrieve data using queries
Generate simple reports and forms

Competency 6 — Explores Programming and Problem Solving

6.1 Understands problem-solving methods (02 Periods)

Learning Outcomes:

Analyze a problem to identify inputs, processes, outputs
Write simple algorithms in pseudocode
Draw flowcharts for given problems

6.2 Applies programming concepts using a high-level language (06 Periods)

Learning Outcomes:

Write simple programs using variables and operators
Implement input and output statements
Apply selection and iteration structures
Use arrays and strings in problem-solving
Test and debug simple programs

6.3 Develops simple programs to solve problems (04 Periods)

Learning Outcomes:

Develop complete programs for given problems
Use structured programming practices
Test and correct errors in programs
Prepare documentation for programs

Competency 7 — Explores Data Communication and Computer Networks

7.1 Explains fundamentals of data communication (02 Periods)

Learning Outcomes:

Identify components of data communication
Describe modes of transmission
List advantages and disadvantages of media

7.2 Explains computer networking concepts (03 Periods)

Learning Outcomes:

Define and classify computer networks
Differentiate network types
Describe common network topologies
Identify functions of networking devices
Differentiate client-server and peer-to-peer models

7.3 Uses Internet and web technologies effectively (04 Periods)

Learning Outcomes:

Use email and search engines efficiently
Identify applications of Internet services
Explain IP addresses, domain names, and URLs
Define cloud computing with examples
Apply cybersecurity practices

Competency 8 — Explores ICT in Society and Emerging Trends

8.1 Identifies the role of ICT in society (02 Periods)

Learning Outcomes:

Discuss the role of ICT in various sectors
Identify social impacts of ICT
Explain ICT’s contribution to globalization

8.2 Explores ethical, legal, and environmental issues in ICT (02 Periods)

Learning Outcomes:

Identify ethical issues in ICT
Explain intellectual property rights and licensing
Describe computer-related laws
Discuss environmental concerns in ICT

8.3 Explores emerging trends in ICT (03 Periods)

Learning Outcomes:

Describe emerging ICT trends
Discuss applications of AI, IoT, Big Data
Identify future directions of ICT

Saturday, August 30, 2025

Project Proposal for your Digital Tax Filing System project. UCSC Colombo UoM Moratuwa SLIIT NIBM Bsc Web development

Project Proposal: Digital Tax Filing System

1. Introduction

Tax filing is an essential responsibility for both individuals and businesses. Traditionally, this process has relied heavily on paper-based submissions, resulting in inefficiencies, higher administrative costs, and risks of errors. The Digital Tax Filing System (DTFS) aims to modernize tax administration by providing a secure, efficient, and user-friendly electronic filing platform.

This system will enable taxpayers to file their tax returns online, make payments digitally, and track their submission status, while also supporting tax authorities with better data management, compliance monitoring, and revenue collection.

2. Problem Statement

The current tax filing process in many regions, including Sri Lanka, suffers from challenges such as:

Manual paperwork leading to errors and delays.
Long processing times for refunds.
Lack of convenient, 24/7 access to filing services.
Difficulty in compliance monitoring by authorities.
High administrative costs for tax departments.

A centralized, digital solution is required to improve taxpayer experience while strengthening compliance and revenue collection mechanisms.

3. Objectives

3.1 General Objective

To design and implement a secure and efficient Digital Tax Filing System that facilitates seamless electronic tax filing and payment for individuals and businesses.

3.2 Specific Objectives

To allow taxpayers to file tax returns online at any time.
To reduce errors by automating calculations and validations.
To enable secure online tax payments through banking integrations.
To provide taxpayers with access to their filing history and refund status.
To support tax authorities in compliance monitoring, reporting, and analytics.
To promote paperless operations and reduce administrative costs.

4. Scope of the Project

The proposed DTFS will cover the following features:

For Taxpayers:

Online registration and account management.
Filing of income, business, and corporate tax returns.
Automated tax calculations and validations.
Uploading of supporting documents in digital format.
Online payment integration via banks or digital wallets.
Notifications and acknowledgment receipts.
Dashboard to track filing status, payments, and refunds.

For Tax Authorities:

Administrative dashboard to manage taxpayer records.
Automated data entry and validation system.
Real-time monitoring of submissions and payments.
Data analytics for compliance tracking and fraud detection.
Reporting and audit features.

5. Literature Review / Related Work

Several countries have successfully implemented digital tax systems:

Sri Lanka: The Inland Revenue Department uses RAMIS for e-filing, along with the Online Tax Payment Platform (OTPP).
United Kingdom: The "Making Tax Digital" initiative requires digital record-keeping and quarterly online updates.
United States: The IRS provides e-filing through Free File, Direct File, and EFTPS for online payments.

These systems demonstrate global best practices, highlighting the benefits of automation, security, and user convenience.

6. Methodology

The project will be developed in phases using the Agile methodology, ensuring continuous feedback and improvements.

Requirement Analysis – Collect requirements from taxpayers, tax authorities, and financial institutions.
System Design – Develop system architecture, database design, and user interface prototypes.
Implementation – Build modules for taxpayer portal, admin portal, and payment gateway integration.
Testing – Perform unit testing, system testing, and security testing.
Deployment – Deploy the system on a secure cloud/server environment.
Maintenance – Regular updates, bug fixes, and user support.

7. Technologies to be Used

Frontend: React.js / Angular for responsive interfaces.
Backend: PHP / Node.js / Java Spring Boot.
Database: MySQL / PostgreSQL.
Security: SSL encryption, Two-Factor Authentication (2FA), and role-based access control.
Cloud/Hosting: AWS / Azure / On-premises government servers.
Integration: Banking APIs for online payments.

8. Expected Outcomes

A fully functional digital platform for taxpayers to file and pay taxes online.
Increased taxpayer satisfaction due to convenience and faster refunds.
Reduced administrative workload and operational costs for authorities.
Improved compliance and reduced tax evasion through automated monitoring.
Availability of real-time data for revenue forecasting and policymaking.

9. Benefits

For Taxpayers:

24/7 access to filing and payment services.
Reduced manual errors and faster refunds.
Improved transparency and security of personal data.

For Tax Authorities:

Streamlined operations and reduced paperwork.
Enhanced compliance monitoring and enforcement.
Increased efficiency in tax collection and reporting.
Ability to leverage big data and AI for policy decisions.

10. Project Timeline (Indicative)

Phase	Duration
Requirement Analysis	2 weeks
System Design	3 weeks
Development	8 weeks
Testing	3 weeks
Deployment	2 weeks
Maintenance	Ongoing

Total estimated timeline: 18 weeks (approx. 4–5 months)

11. Budget (Indicative)

Software Development & Testing: $XX,XXX
Hosting & Cloud Services: $X,XXX
Security & Compliance: $X,XXX
Training & User Support: $X,XXX
Maintenance & Updates: $X,XXX annually

(Exact budget to be finalized after requirement analysis.)

12. Conclusion

The Digital Tax Filing System represents a crucial step towards modernizing tax administration in Sri Lanka and beyond. By providing a secure, convenient, and efficient platform, the system will improve taxpayer satisfaction, strengthen compliance, and enhance government revenue collection.

This project has the potential to align Sri Lanka’s taxation processes with global best practices while promoting transparency, efficiency, and digital transformation in public services.

Friday, August 22, 2025

Introduction to Object Orientation Encapsulation Inheritance Polymorphism Abstraction Classes & Objects Python

📘 Part 1: Introduction to Object Orientation

Object Orientation = A way of designing programs around objects (real-world things).
Each object has:
- Properties (attributes/data) → e.g., a Car has color, model
- Methods (functions/behavior) → e.g., a Car can start(), stop()

✅ Why use Object Orientation?

Models the real world better
Easy to reuse and extend code
Easier maintenance
Saves development time

📘 Part 2: Main Principles of OOP

Encapsulation → hiding details
- Example: You just call tv.turnOn(), you don’t care how it works inside.
Inheritance → child class gets features of parent class
- Example: Dog and Cat inherit from Animal.
Polymorphism → same function, different behavior
- Example: draw() works differently for Circle and Square.
Abstraction → show only important things, hide details
- Example: A car’s steering wheel hides the complex engine mechanism.
Classes & Objects
- Class = blueprint (like a recipe)
- Object = actual thing created from blueprint (like a cake baked from recipe)

📘 Part 3: Python Basics Refresher

✅ Data Structures

Structure	Written With	Ordered?	Changeable?	Allows Duplicates?	Example
Tuple	()	Yes	❌ No	✅ Yes	(1, 2, "Hi")
List	[]	Yes	✅ Yes	✅ Yes	[1,2,2,3]
Set	{}	No	✅ Yes	❌ No	{1,2,3}
Dictionary	{key:val}	Yes	✅ Yes	Keys ❌ dupes, Values ✅	{"A":10, "B":20}

✅ Variables

Must start with a letter or _
Cannot start with number
Case-sensitive (Age ≠ age)
Use meaningful names (student_age ✔ vs x ✘)

✅ Operators

Arithmetic: + - * / % ** //
Comparison: == != > < >= <=
Logical: and, or, not
Assignment: =, +=, -=
Membership: in, not in
Identity: is, is not

✅ Indentation in Python

Python uses spaces instead of { }.
Example:

if age >= 18:
    print("Adult")
else:
    print("Child")

📘 Part 4: Control Flow

Sequence → run line by line
Selection (if/else) → decision-making
Repetition (loops) → repeat tasks
- for loop → repeat fixed times
- while loop → repeat until condition false
- break → exit loop early
- continue → skip one loop step

📘 Part 5: Functions

A function = block of code that does something specific.

def greet(name):
    return "Hello " + name

print(greet("Faaz"))

Functions improve reusability and organization.

📘 Part 6: Sorting & Searching

Bubble Sort → repeatedly swap until sorted (slow for big data).
Selection Sort → pick smallest, put in front.
Insertion Sort → place each new item in correct place.
Merge & Quick Sort → faster, used in real life.

📘 Part 7: Advanced Math

Factorial → 5! = 5×4×3×2×1 = 120
Permutations (order matters) → number of ways to arrange items
Combinations (order doesn’t matter) → number of ways to choose items

📘 Part 8: OOP in Python

class Dog:
    def __init__(self, name):  # constructor
        self.name = name       # attribute

    def bark(self):            # method
        print(self.name + " says Woof!")

dog1 = Dog("Buddy")  # create object
dog1.bark()          # Output: Buddy says Woof!

self → refers to the object itself (must always be used inside class).
Method vs Function
- Function → independent
- Method → belongs to a class/object

📘 Part 9: Flowcharts & Problem Solving

Flowcharts help visualize logic.
Example: A game where user inputs a number, computer generates random number → compare → check win/loss.

🔹 Cohesion (togetherness inside a class/module)

Meaning: How strongly related the functions inside one class are.
High Cohesion = everything in the class is focused on one clear job.
Low Cohesion = class does many unrelated jobs → confusing & hard to maintain.

✅ Example:

# High Cohesion (Payment related only)
class PaymentProcessor:
    def validate_payment(self): pass
    def process_payment(self): pass
    def send_receipt(self): pass

This class only handles payment-related work → high cohesion.

# Low Cohesion (Mixing many jobs)
class Utility:
    def send_email(self): pass
    def calculate_salary(self): pass
    def draw_graph(self): pass

Here, one class is trying to do too many different things → low cohesion.

🔹 Coupling (connections between classes/modules)

Meaning: How much one class depends on another class.
Tightly Coupled = classes know too much about each other → hard to change one without breaking the other.
Loosely Coupled = classes depend only on essential information → flexible and easy to maintain.

✅ Example:

# Loose Coupling (better)
class PaymentProcessor:
    def process(self, payment_method):
        payment_method.pay()

class CreditCard:
    def pay(self): print("Paying with Credit Card")

class PayPal:
    def pay(self): print("Paying with PayPal")

processor = PaymentProcessor()
processor.process(PayPal())  # Can easily swap methods

Here, PaymentProcessor only needs to know that payment_method has a pay() function.
It doesn’t care how PayPal or CreditCard works inside → loosely coupled.

# Tight Coupling (bad)
class PaymentProcessor:
    def pay_with_creditcard(self): pass
    def pay_with_paypal(self): pass

If you add a new method (e.g., Bitcoin), you must modify the class.
This makes the system hard to extend → tightly coupled.

🔹 Rule of Thumb

👉 Good software should be Highly Cohesive + Loosely Coupled:

Each class does one job well (high cohesion).
Classes know only what they must about each other (loose coupling).

That’s how professional software is easier to read, test, reuse, and maintain.

🔹 What is Abstraction?

Abstraction = show only important details and hide the unnecessary ones.
👉 Example: When you drive a car, you just use the steering wheel & pedals.
You don’t see the engine’s wires or fuel injection system — that’s hidden.

🔹 Types of Abstraction in OOP

1. Classification Abstraction

Meaning: Grouping similar objects into classes.
Analogy: Labrador, Poodle, Bulldog → all grouped as Dog.
Focus: Looks at similarities.

class Dog:
    def __init__(self, breed):
        self.breed = breed

dog1 = Dog("Labrador")
dog2 = Dog("Poodle")

Here, Dog is a general class for all breeds.

2. Generalization Abstraction

Meaning: Creating parent-child relationships (inheritance).
Analogy: "Mammal" is a general class → Dog, Cat, Horse are children.
Focus: Top-down → from general → specific.

class Animal:   # Parent
    def breathe(self): print("Breathing")

class Dog(Animal):   # Child
    def bark(self): print("Woof!")

d = Dog()
d.breathe()  # Inherited
d.bark()

Here, Dog inherits general features of Animal.

3. Aggregation Abstraction (weak “has-a” relation)

Meaning: One object contains another, but parts can live independently.
Analogy: A Car has a Radio. The Radio can exist without the Car.

class Radio:
    def play(self): print("Playing music")

class Car:
    def __init__(self, radio):
        self.radio = radio   # "has-a" relation

my_radio = Radio()
my_car = Car(my_radio)
my_car.radio.play()

4. Composition Abstraction (strong “part-of” relation)

Meaning: Stronger form of aggregation → parts cannot exist independently.
Analogy: A House has Rooms. Rooms do not exist outside the house.

class Room:
    def __init__(self, name):
        self.name = name

class House:
    def __init__(self):
        self.rooms = [Room("Living"), Room("Bedroom")]

h = House()
for r in h.rooms:
    print(r.name)

Here, Room objects exist only because the House exists.

5. Behavioral Abstraction

Meaning: Hiding implementation details of methods, only showing what they do.
Analogy: You click “Print” → you don’t know if it’s laser/inkjet, but you get output.
Focus: Method signatures, not how they work inside.

class Printer:
    def print_document(self):   # behavior is abstract
        raise NotImplementedError("Subclasses must implement")

class LaserPrinter(Printer):
    def print_document(self):
        print("Printing with laser...")

class InkjetPrinter(Printer):
    def print_document(self):
        print("Printing with inkjet...")

p = InkjetPrinter()
p.print_document()

Here, print_document() hides details, but each printer implements it differently.

🔹 Summary

Type	Focus	Example
Classification	Grouping similar objects	Dogs → Dog class
Generalization	Parent-child hierarchy	Animal → Dog, Cat
Aggregation	Weak "has-a"	Car has a Radio
Composition	Strong "part-of"	House has Rooms
Behavioral	Hide method details	Printer with different implementations

🔹 Classification

Meaning: Grouping similar objects into classes based on common properties.
Approach: Bottom-Up → start from specific objects → group them.
Question it answers: “What category does this object belong to?”

✅ Example:

Labrador, Poodle, Bulldog → all grouped as Dog.
Cat, Tiger, Lion → all grouped as Cat family.

# Classification Example
class Dog:
    def __init__(self, breed):
        self.breed = breed

dog1 = Dog("Labrador")
dog2 = Dog("Poodle")
print(dog1.breed)   # Labrador

Here, classification means: we group similar objects → all are Dogs.

🔹 Generalization

Meaning: Create hierarchies where specific classes inherit from general ones.
Approach: Top-Down → start from general concept → create specialized ones.
Question it answers: “What is the more general concept that covers this?”

✅ Example:

“Dog”, “Cat”, “Horse” → all are generalized as Animal.

# Generalization Example
class Animal:  # General (parent)
    def breathe(self): print("Breathing")

class Dog(Animal):  # Specific (child)
    def bark(self): print("Woof!")

class Cat(Animal):  # Specific (child)
    def meow(self): print("Meow!")

d = Dog()
d.breathe()   # Inherited from Animal
d.bark()

Here, generalization means: we create a general Animal class → and let Dog & Cat inherit from it.

🔹 Key Differences (Side-by-Side)

Feature	Classification	Generalization
Definition	Grouping similar objects into categories	Building parent-child relationships
Direction	Bottom-Up (from specific → category)	Top-Down (from general → specialized)
Focus	Similarities among objects	Hierarchies & inheritance
Example	Labrador + Poodle + Bulldog = Dog class	Dog, Cat, Horse → inherit from Animal class
Question	“What category is this object in?”	“What general concept does this belong to?”

🔹 Real-Life Analogy

Classification:
- You look at fruits → Apple, Banana, Orange → group them as Fruits.
Generalization:
- You start with “Plant” → then generalize into “Fruit” and “Vegetable”.

✅ In short:

Classification organizes objects into groups.
Generalization creates parent-child hierarchies among those groups.

🃏 Flashcards for OOP with Python

🔹 Beginner (Basics)

Q1: What is Object Orientation?
A1: A way of designing programs around objects (real-world entities) that have attributes (data) and methods (behavior).

Q2: What is a Class?
A2: A blueprint/template for creating objects.

Q3: What is an Object?
A3: An instance of a class (real thing created from the blueprint).

Q4: What are the 4 main principles of OOP?
A4: Encapsulation, Inheritance, Polymorphism, Abstraction.

Q5: What is the difference between Attributes and Methods?
A5: Attributes = variables (data of object). Methods = functions (behavior of object).

🔹 Encapsulation & Abstraction

Q6: What is Encapsulation?
A6: Hiding internal details of a class and controlling access using getters & setters.

Q7: Example of Encapsulation in Python?
A7:

class Bank:
    def __init__(self, balance):
        self.__balance = balance
    def get_balance(self):
        return self.__balance

Q8: What is Abstraction?
A8: Showing only necessary features, hiding the implementation details.

Q9: Types of Abstraction?
A9: Classification, Generalization, Aggregation, Composition, Behavioral.

Q10: Example of Abstraction in real life?
A10: Driving a car → you use the steering wheel (interface), but don’t see engine details.

🔹 Inheritance & Polymorphism

Q11: What is Inheritance?
A11: When a class (child) inherits attributes & methods from another class (parent).

Q12: What is Polymorphism?
A12: Same method name, different behavior depending on object.

Q13: Python Example of Polymorphism?
A13:

class Dog:
    def speak(self): print("Woof!")
class Cat:
    def speak(self): print("Meow!")
for animal in [Dog(), Cat()]:
    animal.speak()

🔹 Cohesion & Coupling

Q14: What is High Cohesion?
A14: A class does only one job well (focused).

Q15: What is Low Coupling?
A15: Classes are independent and interact only through simple interfaces.

Q16: Ideal design principle?
A16: High Cohesion + Low Coupling → modular, reusable code.

🔹 Python Basics from PDF

Q17: List vs Tuple vs Set vs Dictionary?
A17:

List → ordered, mutable, allows duplicates
Tuple → ordered, immutable
Set → unordered, unique values only
Dictionary → key-value pairs

Q18: What is Indentation in Python?
A18: Spaces at the start of a line that define blocks of code (instead of {}).

Q19: What does break and continue do in loops?
A19: break exits loop, continue skips current iteration.

🔹 Control Flow

Q20: Difference between Sequence, Selection, and Repetition?
A20:

Sequence → step-by-step execution
Selection → decision-making (if/else)
Repetition → looping (for, while)

Q21: Deterministic vs Non-Deterministic Loops?
A21:

Deterministic → fixed iterations (e.g., for i in range(5))
Non-Deterministic → unknown iterations (e.g., while user_input != "stop")

🔹 Functions & Recursion

Q22: What is a Function?
A22: A reusable block of code with name, parameters, and optional return value.

Q23: Difference between Function and Method?
A23:

Function = standalone block
Method = belongs to a class/object

Q24: What is Recursion?
A24: A function calling itself until a base case is reached.

Q25: Recursion vs Iteration?
A25:

Recursion → uses call stack, may risk stack overflow
Iteration → uses loops, more memory efficient

🔹 Algorithms

Q26: What is Bubble Sort?
A26: Repeatedly swap adjacent elements if out of order.

Q27: What is Selection Sort?
A27: Repeatedly find the minimum element and place it in order.

Q28: What is Insertion Sort?
A28: Insert each element into the correct position in sorted part.

Q29: What is Merge Sort?
A29: Divide & conquer → split list, sort halves, merge results.

Q30: What is Quick Sort?
A30: Choose a pivot, partition list, sort sublists recursively.

🔹 Math & Probability

Q31: What is Factorial?
A31: n! = n × (n-1) × ... × 1

Q32: What is a Permutation?
A32: Selection where order matters → nPk = n! / (n-k)!

Q33: What is a Combination?
A33: Selection where order does NOT matter → nCk = n! / (k!(n-k)!)

🔹 Advanced OOP in Python

Q34: What is self in Python classes?
A34: Refers to the current object instance (needed for attributes & methods).

Q35: Why use __ (double underscore) before variable names?
A35: To make them private → accessed only through getters/setters.

Q36: What is the difference between Public, Protected, and Private attributes in Python?
A36:

Public → normal (name) → accessible anywhere
Protected → _name → “internal use only” (by convention)
Private → __name → hidden, only accessible inside class

🔹 Flowcharts & Problem Solving

Q37: Why use Flowcharts for algorithms?
A37: Visual clarity, easier debugging, error detection, and communication.

Q38: Example: Game logic flashcard
Q38A: User inputs number → computer generates random → compare → if 2+ matches in 3 tries → Win.

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🚀 Join the Best BIT Software Project Classes in Sri Lanka! 🎓

Are you a BIT student struggling with your final year project or looking for expert guidance to ace your UCSC final year project? 💡 We've got you covered!

✅ What We Offer:

- Personalized project consultations

- Step-by-step project development guidance

- Expert coding and programming assistance (PHP, Python, Java, etc.)

- Viva preparation and documentation support

- Help with selecting winning project ideas

📅 Class Schedules:

- Weekend Batches: Flexible timings for working students

- Online & In-Person Options

🏆 Why Choose Us?

- Proven track record of guiding top BIT projects

- Hands-on experience with industry experts

- Affordable rates tailored for students

🔗 Enroll Now: Secure your spot today and take the first step toward project success!

📞 Contact us: https://web.facebook.com/itclasssrilanka

📍 Location: Online

🌐 Visit us online: https://localedxcelcambridgeictcomputerclass.blogspot.com/

✨ Don't wait until the last minute! Start your BIT final year project with confidence and guidance from the best in the industry. Let's make your project a success story!

---

Individual attention to all students

🎓 Final Year IT & Computer Science Students! 🚀

Get Expert Guidance for Your Degree Projects & Reports!

💡 We Specialize In:

✅ Project Proposal Writing (University-Ready)

✅ Interim Report Assistance

✅ Final Dissertation / Use Case Document Support

✅ Test Manual & Installation Guides

✅ Complete Final-Year Project System (Fully Working)

✅ Test Document Preparation

✅ Computer Studies / BIT / Software Engineering / IT / VLE Courses

👨‍🏫 Supervision by Experienced Software Developers & University Project Guides

📘 Covers: Java, Python, PHP, MySQL, AI, Web & Mobile Development, Machine Learning

📞 Contact Now to Book Your Slot – Limited Project Guidance Available!

🚀 **LEARN COMPUTER SCIENCE & TECH SKILLS FROM ZERO TO PRO!** 🎓💻

✨ *Future-Proof Your Career with Our Practical Courses!*

📚 **Courses We Offer:**

🎓 **ICT for School Leavers (Post O/L or A/L)**

✅ Intro to IT & Careers in ICT

✅ MS Office (Word, Excel, PowerPoint, Access)

✅ Email, Conferencing & Digital Communication

✅ Databases & Queries

✅ Intro to Python Programming

✅ Basic Graphic Design & Photo Editing

✅ Project Work: Resume, Reports, Presentations

💻 Web Development (Beginner → Intermediate)

🌐 Web Basics: HTML5, CSS3, Responsive Design

⚡ JavaScript, Forms & Validation

🖥️ Backend with PHP/Node.js + MySQL

🌟 Hosting, Domain Setup, GitHub Deployment

🎨 Optional: WordPress, Figma, Canva

📱 **Social & Digital Media Marketing**

📈 SEO, Google Ads & Content Marketing

📲 Facebook, Instagram, TikTok & YouTube Marketing

🎯 Ads Manager, Email Marketing, Analytics

🛠️ Capstone Project: Create a Real Campaign!

🖥️ **Computer Programming (Beginner → Intermediate)**

🐍 Python/Scratch Basics – Logic, Loops, Functions

👨‍💻 Object-Oriented Programming

🎮 Mini Projects: Games, GUIs, Databases

🤖 **Artificial Intelligence (AI) – Beginner Level**

🔍 AI Basics: History, Applications, AI vs ML

📊 Machine Learning with Python & scikit-learn

🧠 Projects: Image Recognition, Chatbots, Voice Assistant

⚖️ AI Ethics, Jobs & Future Trends

🔥 **WHY JOIN US?**

✅ Short-term, practical & career-focused training

✅ Hands-on projects & real-world applications

✅ Ideal for students, job-seekers & tech enthusiasts

📞 **Call/WhatsApp Now:** 0777337279

🌐 **Register Today & Start Your Journey in Tech!**

✨ *Limited Seats | Certificates Provided | Learn with Experts!*

💡 **Tag a Friend Who Needs This!** 🔖

Thursday, August 21, 2025

E-Prescription Generator system healthcare providers to electronically create, transmit, and manage prescriptions, replacing traditional paper-based prescriptions BIT BSc Software Web Development Tamil

✨💊 The Future of Prescriptions is Digital! 💊✨

Say goodbye to messy handwriting and paper slips!
An E-Prescription Generator System is changing healthcare by making prescriptions smarter, safer, and faster 🚀

✅ Electronic Generation & Transmission – Doctors can send prescriptions directly to pharmacies with just a click!
✅ Integrated with Patient Records – Access to medical history & allergies ensures safer prescribing 🧾
✅ Improved Accuracy & Safety – No more errors from illegible handwriting, plus automatic checks for drug interactions ⚡
✅ Faster & Efficient – Save time for doctors, pharmacies, and patients ⏱️
✅ Patient Friendly – Get prescriptions via QR code or token & choose your pharmacy 🏥
✅ Compliance & Reporting – Stay updated with healthcare regulations 📊

🌍 Examples Worldwide:
🇬🇧 Electronic Prescription Service (UK)
🇦🇺 Active Script List (Australia)
🇬🇧 signatureRx (UK)

👉 Whether integrated with EHRs or as stand-alone systems, e-prescriptions are shaping the future of healthcare 💡

💡 E-Prescription = Accuracy + Safety + Speed + Patient Control 💡

Would you trust an E-Prescription system for your medicines? 🤔💬

#Healthcare #DigitalHealth #Eprescription #FutureOfMedicine #PatientSafety

📌 Modules of an E-Prescription Generator System

1. 🖥️ Electronic Generation & Transmission

Doctors create prescriptions digitally.
Prescriptions are transmitted directly to pharmacies.
Eliminates manual writing & reduces handwriting errors.

2. 📂 Integration with Electronic Health Records (EHR)

Connects seamlessly with EHR platforms.
Provides access to patient history, allergies, medications.
Supports safer and more informed prescribing.

3. ✅ Accuracy & Patient Safety

Prevents errors caused by illegible handwriting.
Automatic checks for:
- Drug interactions 💊
- Allergy conflicts ⚠️
Improves overall patient safety.

4. ⚡ Efficiency Module

Faster communication between doctors & pharmacies.
Reduces unnecessary phone calls.
Speeds up prescription fulfillment for patients.

5. 👨‍⚕️ Patient Access & Control

Patients can receive prescriptions via:
- QR codes
- Digital tokens
Patients choose which pharmacy to fill their medication.

6. 📊 Compliance & Reporting

Helps healthcare facilities meet legal regulations.
Generates reports for audits, tracking & analytics.
Ensures transparency & accountability.

📌 Types of E-Prescribing Systems

Integrated with EHRs
- Part of a larger hospital/clinic system.
- Provides a complete patient health overview.
- Best for large healthcare providers.
Stand-alone Systems
- Independent software.
- Easier & cheaper to set up.
- Suitable for smaller clinics but less integration.

📌 Examples of E-Prescribing Systems

EPS (UK) → Sends prescriptions directly to nominated pharmacies.
ASL (Australia) → Patients manage prescriptions via a digital list.
MediSecure (Australia) → Previously used national system.
SignatureRx (UK) → Offers private electronic prescription services.

⭐ Summary

An E-Prescription Generator System:
👉 Improves accuracy ✍
👉 Ensures safety ⚕️
👉 Boosts efficiency ⚡
👉 Empowers patients 👩‍⚕️👨‍⚕️
👉 Supports compliance & reporting 📊

🚀 Join the Best BIT Software Project Classes in Sri Lanka! 🎓

🔄 Flow of an E-Prescription Generator System

Doctor Login & Patient Selection
- Doctor securely logs into the system.
- Selects patient profile from EHR (Electronic Health Records).
Review Patient Medical History
- Doctor checks allergies, past medications, and conditions.
- System provides alerts for possible risks.
Prescription Creation
- Doctor enters prescription digitally.
- System auto-suggests correct dosage, alternatives, and safety checks.
Accuracy & Safety Check
- System scans for:
  - Drug interactions 💊
  - Allergy conflicts ⚠️
  - Duplicate medicines
- If issues found → system warns doctor.
Electronic Transmission
- Once approved, prescription is sent directly to the patient’s chosen pharmacy.
- Copy stored in patient’s EHR for record keeping.
Pharmacy Processing
- Pharmacy receives digital prescription.
- Prepares medicine and notifies patient when ready.
Patient Access
- Patient gets prescription via:
  - QR code 📱
  - Digital token or app
- Patient can choose which pharmacy to use.
Compliance & Reporting
- System logs prescription data.
- Generates reports for audits, regulations, and analytics.

👉 So the flow is:
Doctor → EHR Check → Create Prescription → Safety Check → Send to Pharmacy → Patient Access → Compliance Reports

Are you a BIT student struggling with your final year project or looking for expert guidance to ace your UCSC final year project? 💡 We've got you covered!

✅ What We Offer:

- Personalized project consultations

- Step-by-step project development guidance

- Expert coding and programming assistance (PHP, Python, Java, etc.)

- Viva preparation and documentation support

- Help with selecting winning project ideas

📅 Class Schedules:

- Weekend Batches: Flexible timings for working students

- Online & In-Person Options

🏆 Why Choose Us?

- Proven track record of guiding top BIT projects

- Hands-on experience with industry experts

- Affordable rates tailored for students

🔗 Enroll Now: Secure your spot today and take the first step toward project success!

📞 Contact us: https://web.facebook.com/itclasssrilanka

📍 Location: Online

🌐 Visit us online: https://localedxcelcambridgeictcomputerclass.blogspot.com/

✨ Don't wait until the last minute! Start your BIT final year project with confidence and guidance from the best in the industry. Let's make your project a success story!

---

Individual attention to all students

🎓 Final Year IT & Computer Science Students! 🚀

Get Expert Guidance for Your Degree Projects & Reports!

💡 We Specialize In:

✅ Project Proposal Writing (University-Ready)

✅ Interim Report Assistance

✅ Final Dissertation / Use Case Document Support

✅ Test Manual & Installation Guides

✅ Complete Final-Year Project System (Fully Working)

✅ Test Document Preparation

✅ Computer Studies / BIT / Software Engineering / IT / VLE Courses

👨‍🏫 Supervision by Experienced Software Developers & University Project Guides

📘 Covers: Java, Python, PHP, MySQL, AI, Web & Mobile Development, Machine Learning

📞 Contact Now to Book Your Slot – Limited Project Guidance Available!

🚀 **LEARN COMPUTER SCIENCE & TECH SKILLS FROM ZERO TO PRO!** 🎓💻

✨ *Future-Proof Your Career with Our Practical Courses!*

📚 **Courses We Offer:**

🎓 **ICT for School Leavers (Post O/L or A/L)**

✅ Intro to IT & Careers in ICT

✅ MS Office (Word, Excel, PowerPoint, Access)

✅ Email, Conferencing & Digital Communication

✅ Databases & Queries

✅ Intro to Python Programming

✅ Basic Graphic Design & Photo Editing

✅ Project Work: Resume, Reports, Presentations

💻 Web Development (Beginner → Intermediate)

🌐 Web Basics: HTML5, CSS3, Responsive Design

⚡ JavaScript, Forms & Validation

🖥️ Backend with PHP/Node.js + MySQL

🌟 Hosting, Domain Setup, GitHub Deployment

🎨 Optional: WordPress, Figma, Canva

📱 **Social & Digital Media Marketing**

📈 SEO, Google Ads & Content Marketing

📲 Facebook, Instagram, TikTok & YouTube Marketing

🎯 Ads Manager, Email Marketing, Analytics

🛠️ Capstone Project: Create a Real Campaign!

🖥️ **Computer Programming (Beginner → Intermediate)**

🐍 Python/Scratch Basics – Logic, Loops, Functions

👨‍💻 Object-Oriented Programming

🎮 Mini Projects: Games, GUIs, Databases

🤖 **Artificial Intelligence (AI) – Beginner Level**

🔍 AI Basics: History, Applications, AI vs ML

📊 Machine Learning with Python & scikit-learn

🧠 Projects: Image Recognition, Chatbots, Voice Assistant

⚖️ AI Ethics, Jobs & Future Trends

🔥 **WHY JOIN US?**

✅ Short-term, practical & career-focused training

✅ Hands-on projects & real-world applications

✅ Ideal for students, job-seekers & tech enthusiasts

📞 **Call/WhatsApp Now:** 0777337279

🌐 **Register Today & Start Your Journey in Tech!**

✨ *Limited Seats | Certificates Provided | Learn with Experts!*

💡 **Tag a Friend Who Needs This!** 🔖

🚀 Chatbots in Healthcare – The Future of Digital Health! 💡

🤖 What is a Chatbot in Healthcare?
A healthcare chatbot is an AI-powered digital assistant that helps patients and doctors with instant responses, appointment scheduling, symptom checks, medical knowledge access, and 24/7 support. 🌍

💬 Which AI Chatbot is Best for Medical Use?
Popular choices include ChatGPT, HealthTap, Buoy Health, Babylon Health, and Tars – each offering advanced AI-driven healthcare support for patients and providers.

🛠 How to Create a Medical Agent (Step-by-Step Guide)
✅ Step 1: Define the pain points & problems you want to solve.
✅ Step 2: Choose a reliable platform (e.g., Tars, Rasa, Dialogflow, or custom AI).
✅ Step 3: Design the conversation flow for patient interaction.
✅ Step 4: Develop the chatbot using AI & ML algorithms.
✅ Step 5: Test & refine for accuracy and usability.
✅ Step 6: Ensure compliance with HIPAA/GDPR and secure patient data.

🧑‍⚕️ Can Chatbots Replace Doctors?
👉 No, but they can assist doctors by reducing workload, improving patient experience, and offering 24/7 availability.

💰 Cost of Creating an AI Medical Chatbot
Building a healthcare chatbot can cost from $500 (basic) to $50,000+ (enterprise-grade with AI & ML), depending on complexity.

🔍 Types of Chatbots in Healthcare
1️⃣ Rule-based Chatbots
2️⃣ AI-powered Chatbots
3️⃣ Contextual Chatbots
4️⃣ Voice-enabled Chatbots

🎯 Initial Goals for a Medical Chatbot
✔ Provide instant responses
✔ Reduce patient wait time
✔ Offer symptom checkers & FAQs
✔ Improve patient satisfaction
✔ Lower hospital readmission rates

🌟 The Future: AI chatbots will not replace doctors, but they will revolutionize healthcare delivery by making it smarter, faster, and more patient-friendly.

✨ Ready to build your own Healthcare AI Chatbot?
💡 Start today with tools like Tars, Rasa, Dialogflow, or OpenAI-powered platforms.

🔖 Hashtags for SEO & Reach:
#HealthcareChatbots #AIinHealthcare #DigitalHealth #HealthTech #MedicalAI #ChatbotDevelopment #FutureOfHealthcare #AIChatbot #PatientCare #HealthInnovation #MedTech #ArtificialIntelligence

📊 Understanding Health Insurance DFD (Data Flow Diagram) 🏥💻

A Health Insurance DFD visually shows how data flows through an insurance system – from patients and healthcare providers to claims, billing, and payment management. It maps out sources, destinations, processes, and data stores to make complex systems easier to understand.

✨ Key Components of a Health Insurance DFD:
🔹 External Entities: Patients, employers, providers
🔹 Processes: Validate policy, process claim, generate bill
🔹 Data Stores: Patient records, claims database, billing ledger
🔹 Data Flows: Movement of data between entities, processes & storage

⚡ Levels of a DFD:
✅ Level 0 (Context Diagram): Shows the entire system as one process with main interactions
✅ Level 1: Breaks down into sub-processes (claims, policies, payments)
✅ Level 2 & Beyond: More detailed workflows for complex systems

💡 Why Health Insurance DFDs Matter?
✔ System Analysis: Identify inefficiencies & bottlenecks
✔ System Design: Guide developers in building or upgrading systems
✔ Process Optimization: Improve accuracy & streamline workflows
✔ Communication: Standardized visual language for business & technical teams

🚀 Whether you’re a student, IT professional, or healthcare analyst, mastering DFDs in Health Insurance Systems is key to understanding how data powers modern healthcare and insurance solutions.

🔖 Hashtags for Reach & SEO:
#HealthInsurance #DFD #DataFlowDiagram #SystemDesign #HealthcareIT #InsuranceTech #HealthTech #MedicalData #DataVisualization #ICT #ProcessOptimization #BusinessAnalysis

🔥💡 Students, Ready to Build the Future of Healthcare? 💡🔥

Imagine turning rehabilitation into a high-tech, interactive, and even video game–like experience 🎮✨. That’s exactly what a Rehabilitation Monitoring System does!

🌟 This innovative system uses sensors, software, and real-time data analysis to track patient recovery progress — from strength 💪 and coordination 🤸‍♀️ to body posture 🧍.

Here’s how it works:
1️⃣ Sensors – Capture movement, muscle activity, and body signals.
2️⃣ Connectivity – Transmit data wirelessly via Wi-Fi/IoT to doctors anywhere 🌍.
3️⃣ Smart Software – Analyze recovery patterns using AI & machine learning 🤖.
4️⃣ Real-Time Feedback – Patients get instant guidance through interactive visuals & game-like tasks 🎯.

🚀 Why it matters for students:
✅ Learn how IoT, AI, and biomedical engineering come together in real-world applications.
✅ Contribute to better healthcare solutions while boosting your final-year project.
✅ Gain hands-on experience with cutting-edge technology that’s shaping the future.

💥 Benefits of the System:
✔️ Improved recovery outcomes 🏃‍♂️
✔️ Remote monitoring for patients 👩‍⚕️
✔️ Data-driven treatment adjustments 📊
✔️ Increased patient motivation & independence 🙌

📍 If you’re passionate about healthcare + technology, this project idea can set you apart and showcase your skills in innovation, problem-solving, and impact-driven design.

👉 Students, are you ready to explore the next big thing in rehabilitation technology? Comment “YES” 🙋 if you’d love to work on this idea for your final-year project!

#FutureOfHealthcare #RehabilitationTech #StudentInnovation #IoT #AIinEducation #BITProjects

📢✨ Calling All Future Developers & Innovators! ✨📢

Are you a student looking to build an exciting project? 🚀💻
Here’s your chance to create something truly impactful – a “Diet Plan System” 🥗⚡

A Diet Plan System is not just about food 🍎🥑🍗 – it’s a smart approach to health using technology. Imagine helping people reach their fitness goals with the right mix of:
✅ Goal setting (weight loss, muscle gain, or overall wellness)
✅ Food selection (fruits, veggies, lean proteins, whole grains)
✅ Portion control & meal planning
✅ Easy methods like MyPlate or 5-4-3-2-1 shopping strategy

🔹 Students working on this project will learn:
💡 How to design user-friendly systems
💡 Data handling for nutrition and meal planning
💡 Practical application of health + technology
💡 Real-world problem solving

👩‍💻👨‍💻 Whether you’re into IT, nutrition, or fitness, this project can boost your portfolio and help you create something that matters. 🌍

👉 Interested? Drop a comment ⬇️ or DM us to get started!
Let’s build a system that makes healthy living smarter 💪💻

#StudentProject #DietPlanSystem #FutureDevelopers #Innovation #HealthyLiving #TechForGood #SriLankaStudents

Friday, August 15, 2025

Python SECTION 2 – Control Flow Conditionals – if, elif, else Loops Comprehensions

SECTION 2 – Control Flow (Weeks 2–3)

2.1 Conditionals – `if`, `elif`, `else`

📚 What: Conditionals let your program make decisions.
🧠 AI/ML Relevance:

Check accuracy thresholds before deployment
Decide model tuning steps based on loss value
Perform different preprocessing for text vs image datasets

💻 Example: Accuracy Evaluation

accuracy = 0.88

if accuracy > 0.9:
    print("Excellent model")
elif accuracy > 0.8:
    print("Good model, but can improve")
else:
    print("Needs more training")

Nested Conditions

📚 What: Condition inside another condition.
🧠 AI/ML Relevance:

Check multiple model performance metrics
Apply rules for different dataset conditions

💻 Example: Accuracy + Loss Check

accuracy = 0.92
loss = 0.15

if accuracy > 0.9:
    if loss < 0.2:
        print("Ready for deployment")
    else:
        print("Accuracy is fine, but reduce loss")

🏋 Exercise:
Write a conditional that:

Checks if accuracy > 0.85
If true, checks if loss < 0.15 → print "Excellent"
Else print "Needs work"

2.2 Loops

For Loops

📚 What: Repeat code for a fixed number of iterations or over a collection.
🧠 AI/ML Relevance:

Iterate over datasets
Process batches in training
Apply transformations to every data point

💻 Example: Processing Dataset Batches

batches = ["Batch 1", "Batch 2", "Batch 3"]

for batch in batches:
    print(f"Processing {batch}")

While Loops

📚 What: Repeat until a condition becomes false.
🧠 AI/ML Relevance:

Continue training until loss is below a threshold
Keep collecting data until dataset size is reached

💻 Example: Training Until Loss Threshold

loss = 1.0
while loss > 0.1:
    print(f"Training... current loss = {loss}")
    loss -= 0.2
print("Training stopped: Loss threshold met")

Break & Continue

📚 What:

break → Stop the loop early
continue → Skip the rest of the current iteration

💻 Example: Stop Training Early

losses = [0.5, 0.3, 0.15, 0.09]

for loss in losses:
    if loss < 0.1:
        print("Loss is low enough, stopping early")
        break
    print(f"Current loss: {loss}")

💻 Example: Skip Bad Data

data_points = [1, None, 3, None, 5]

for point in data_points:
    if point is None:
        continue
    print(f"Processing: {point}")

range()

📚 What: Generates a sequence of numbers for looping.

💻 Example: 5 Epochs Training

for epoch in range(1, 6):
    print(f"Training Epoch {epoch}")

Loop Over Iterables

📚 What: Loop directly over lists, dicts, sets, tuples.
💻 Example: Looping Over Dictionary of Model Parameters

params = {"learning_rate": 0.001, "batch_size": 32, "epochs": 10}

for key, value in params.items():
    print(f"{key}: {value}")

🏋 Exercise:
Loop over a dictionary containing "model", "accuracy", and "loss" and print them in key: value format.

2.3 Comprehensions

📚 What: Shorter, cleaner way to create lists, sets, dicts from loops.
🧠 AI/ML Relevance: Quickly transform datasets without writing long loops.

List Comprehension

💻 Example: Squaring All Loss Values

losses = [0.5, 0.3, 0.15]
squared_losses = [loss**2 for loss in losses]
print(squared_losses)

Tuple Comprehension (Actually Generators in Python)

💻 Example: Generate Accuracy Values on the Fly

accuracies = (round(acc, 2) for acc in [0.82, 0.91, 0.88])
for acc in accuracies:
    print(acc)

Dict Comprehension

💻 Example: Mapping Model Names to Accuracies

models = ["Model_A", "Model_B", "Model_C"]
accs = [0.85, 0.90, 0.88]

model_performance = {model: acc for model, acc in zip(models, accs)}
print(model_performance)

Set Comprehension

💻 Example: Unique Label Extraction

labels = ["cat", "dog", "cat", "bird", "dog"]
unique_labels = {label for label in labels}
print(unique_labels)

🏋 Final Exercise for Section 2:
Given:

models = ["A", "B", "C"]
accuracies = [0.9, 0.85, 0.92]

Create a dictionary mapping each model to its accuracy (dict comprehension)
Create a list of only the accuracies above 0.88 (list comprehension)
Loop over the dictionary and print "Model X has accuracy Y"

Python dictionary methods in action.

# Create a dictionary for months
months = {
    "January": 31,
    "February": 28,
    "March": 31,
    "April": 30,
    "May": 31,
    "June": 30
}

print("Original dictionary:", months)

1. Access values

print("Days in February:", months["February"])
print("Days in May (get method):", months.get("May"))
print("Non-existing month with default:", months.get("December", "Not Found"))

2. Add or update

months["July"] = 31  # Add
months["February"] = 29  # Update (Leap year)
print("After add/update:", months)

3. Remove — `pop()`

removed_days = months.pop("June")
print("Removed June (days =", removed_days, "):", months)

4. Remove last item — `popitem()`

last_item = months.popitem()
print("Removed last item:", last_item)
print("After popitem:", months)

5. Delete — `del`

del months["April"]
print("After deleting April:", months)

6. Clear dictionary

temp_months = months.copy()
temp_months.clear()
print("After clear:", temp_months)

7. Copy dictionary

months_copy = months.copy()
print("Copied dictionary:", months_copy)

8. Keys, Values, Items

print("Keys:", months.keys())
print("Values:", months.values())
print("Items:", months.items())

9. Loop through dictionary

for month, days in months.items():
    print(f"{month}: {days} days")

10. Check membership

print("Is 'March' in months?", "March" in months)
print("Is 'December' not in months?", "December" not in months)

11. Update with another dictionary

months.update({"August": 31, "September": 30})
print("After update:", months)

12. Dictionary comprehension

month_lengths = {month: len(month) for month in months}
print("Month name lengths:", month_lengths)

Tuple example similar to the list and set ones.
Tuples are ordered, immutable collections — so you can’t change items after creation (no append(), remove(), etc.), but you can still use many useful built-in functions.

# Create a tuple of fruits
fruits = ("apple", "banana", "cherry", "date", "elderberry", "banana")

print("Original tuple:", fruits)

1. Access elements by index

print("First fruit:", fruits[0])
print("Last fruit:", fruits[-1])

2. Slicing

print("First 3 fruits:", fruits[:3])
print("Fruits from index 2 onwards:", fruits[2:])

3. Count — `count()`

print("Count of 'banana':", fruits.count("banana"))

Counts occurrences of a value.

4. Index — `index()`

print("Index of 'cherry':", fruits.index("cherry"))

Finds the first occurrence of a value.

5. Length — `len()`

print("Number of fruits:", len(fruits))

6. Membership test

print("Is 'apple' in tuple?", "apple" in fruits)
print("Is 'mango' not in tuple?", "mango" not in fruits)

7. Concatenation

more_fruits = ("fig", "grape")
combined = fruits + more_fruits
print("Combined tuple:", combined)

8. Repetition

repeat_fruits = ("apple", "banana") * 2
print("Repeated tuple:", repeat_fruits)

9. Min / Max / Sum (works only if all items are same type)

numbers = (5, 2, 9, 1)
print("Min number:", min(numbers))
print("Max number:", max(numbers))
print("Sum:", sum(numbers))

10. Tuple unpacking

a, b, c, *rest = fruits
print("a:", a)
print("b:", b)
print("c:", c)
print("rest:", rest)

11. Convert to list (to modify) and back

temp_list = list(fruits)
temp_list.append("honeydew")
fruits = tuple(temp_list)
print("Modified tuple:", fruits)

Python set functions/methods with examples.
Remember: a set is unordered, does not allow duplicates, and elements must be immutable.

# Create a set of fruits
fruits = {"apple", "banana", "cherry", "date", "elderberry"}

print("Original set:", fruits)

1. Add — `add()`

fruits.add("fig")
print("After add:", fruits)

Adds a single item.

2. Update — `update()`

fruits.update(["grape", "honeydew"])
print("After update:", fruits)

Adds multiple items.

3. Remove — `remove()`

fruits.remove("banana")
print("After remove:", fruits)

Removes an item; error if not found.

4. Discard — `discard()`

fruits.discard("kiwi")  # No error if not found
print("After discard (kiwi):", fruits)

Removes item without error.

5. Pop — `pop()`

removed = fruits.pop()
print("Popped item:", removed)
print("After pop:", fruits)

Removes a random item (since sets are unordered).

6. Clear — `clear()`

temp_set = fruits.copy()
temp_set.clear()
print("After clear:", temp_set)

Removes all items.

7. Copy — `copy()`

fruits_copy = fruits.copy()
print("Copied set:", fruits_copy)

Shallow copy.

8. Union — `union()` / `|`

set_a = {"apple", "banana", "mango"}
set_b = {"banana", "kiwi", "orange"}
print("Union:", set_a.union(set_b))
print("Union (|):", set_a | set_b)

Combines sets, removes duplicates.

9. Intersection — `intersection()` / `&`

print("Intersection:", set_a.intersection(set_b))
print("Intersection (&):", set_a & set_b)

Items common to both sets.

10. Difference — `difference()` / `-`

print("Difference:", set_a.difference(set_b))
print("Difference (-):", set_a - set_b)

Items in the first set but not the second.

11. Symmetric Difference — `symmetric_difference()` / `^`

print("Symmetric Difference:", set_a.symmetric_difference(set_b))
print("Symmetric Difference (^):", set_a ^ set_b)

Items in either set but not both.

12. isdisjoint()

print("Is disjoint?:", {"pineapple"} .isdisjoint({"mango"}))

True if no elements in common.

13. issubset() / issuperset()

print("Is subset?:", {"apple", "banana"}.issubset(set_a))
print("Is superset?:", set_a.issuperset({"banana"}))

14. len()

print("Number of fruits:", len(fruits))

Counts items in the set.

Python list function / method with examples so you have a ready reference.

# Create a list of fruits
fruits = ["apple", "banana", "cherry", "date", "elderberry"]

print("Original list:", fruits)

1. Append — `append()`

fruits.append("fig")
print("After append:", fruits)

Adds an item to the end.

2. Insert — `insert()`

fruits.insert(2, "blueberry")
print("After insert:", fruits)

Inserts at a specific index.

3. Extend — `extend()`

fruits.extend(["grape", "honeydew"])
print("After extend:", fruits)

Adds multiple items.

4. Remove — `remove()`

fruits.remove("banana")
print("After remove:", fruits)

Removes first occurrence of a value.

5. Pop — `pop()`

popped = fruits.pop(3)
print("Popped item:", popped)
print("After pop:", fruits)

Removes by index (last item if no index given).

6. Clear — `clear()`

temp_list = fruits.copy()
temp_list.clear()
print("After clear:", temp_list)

Removes all items.

7. Index — `index()`

print("Index of cherry:", fruits.index("cherry"))

Finds the first occurrence of a value.

8. Count — `count()`

print("Count of 'apple':", fruits.count("apple"))

Counts how many times a value appears.

9. Sort — `sort()`

fruits.sort()
print("Sorted list:", fruits)

fruits.sort(reverse=True)
print("Reverse sorted list:", fruits)

Sorts in place (alphabetically by default).

10. Reverse — `reverse()`

fruits.reverse()
print("After reverse:", fruits)

Reverses order.

11. Copy — `copy()`

new_fruits = fruits.copy()
print("Copied list:", new_fruits)

Shallow copy of the list.

12. Slicing

print("First 3 fruits:", fruits[:3])
print("Last 2 fruits:", fruits[-2:])

Access sublists.

13. List Comprehension

long_names = [f for f in fruits if len(f) > 5]
print("Fruits with names longer than 5 letters:", long_names)

Create lists with conditions.

14. Length — `len()`

print("Number of fruits:", len(fruits))

Gets number of items.

15. Min / Max

print("Min fruit (alphabetically):", min(fruits))
print("Max fruit (alphabetically):", max(fruits))

import sys

# Join all arguments into one string

full_text = " ".join(sys.argv[1:])

# Example: full_text = "Arguments passed is <123> from command"

# Extract the part between < and >

start = full_text.find("<") + 1

end = full_text.find(">")

number = full_text[start:end]

print(number)

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Tuesday, September 2, 2025

General Information Technology (GIT) G.C.E. A/L English Medium Syllabus Download Notes Classes Questions and Answers

📘 G.C.E. A/L – General Information Technology (GIT) Syllabus

1.1 Describes the computer as a system using a block diagram (02 Periods)

Contents:

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1.2 Identifies the specifications of personal computers (01 Period)

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2.1 Data representation and fundamental concepts (02–03 Periods)

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2.2 Basic Boolean operators (01 Period)

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2.3 Character encoding systems (01 Period)

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3.1 Identifies the role of an Operating System (01 Period)

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3.2 Uses functions of an Operating System (02 Periods)

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4.1 Uses a Word Processor to create professional documents (04 Periods)

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4.2 Uses Spreadsheet software for data organization and analysis (04 Periods)

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4.3 Uses Presentation software to prepare presentations (02 Periods)

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5.1 Explains the concept of databases and DBMS (02 Periods)

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5.2 Explains data models with emphasis on relational model (02 Periods)

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5.3 Uses DBMS software to manage data (04 Periods)

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6.1 Understands problem-solving methods (02 Periods)

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6.2 Applies programming concepts using a high-level language (06 Periods)

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6.3 Develops simple programs to solve problems (04 Periods)

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7.1 Explains fundamentals of data communication (02 Periods)

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7.2 Explains computer networking concepts (03 Periods)

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7.3 Uses Internet and web technologies effectively (04 Periods)

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8.1 Identifies the role of ICT in society (02 Periods)

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8.2 Explores ethical, legal, and environmental issues in ICT (02 Periods)

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8.3 Explores emerging trends in ICT (03 Periods)

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Saturday, August 30, 2025

Project Proposal for your Digital Tax Filing System project. UCSC Colombo UoM Moratuwa SLIIT NIBM Bsc Web development

Project Proposal: Digital Tax Filing System

1. Introduction

2. Problem Statement

3. Objectives

3.1 General Objective

3.2 Specific Objectives

4. Scope of the Project

5. Literature Review / Related Work

2.1 Conditionals – `if`, `elif`, `else`