EMRS/KVS Revision

ExamPill · EMRS / NVS · TGT / PGT

Computer Science
Superfast Revision Guide

Definitions · Memory Tricks · Mnemonics · Key Tables

14Units

200+Keywords

50+Memory Tricks

📚 Quick Navigation

Unit 1

Computer Systems

Unit 2

Application Software

Unit 3

Programming & Python

Unit 4

Data Structures

Unit 5

Computer Networks

Unit 6

Database & SQL

Unit 7

Cybersecurity

Unit 8

Emerging Tech

Unit 9

Society & Ethics

Quick Reference

Abbreviations & Tips

1

Computer Systems & Organisation

🖥️ Core Concepts

Computer

Takes input → processes it → gives output

Hardware

Physical parts you can touch (monitor, keyboard)

Software

Instructions that tell hardware what to do

Data

Raw facts — no meaning alone (e.g., 42, "A")

Information

Processed data that has meaning and is useful

💡 Trick

Data → Process → Information = DPI (like screen DPI!)

⚙️ CPU Parts

ALU

Does maths (+, -, ×, ÷) and logic (AND, OR, NOT)

CU (Control Unit)

The manager — fetches, decodes, executes instructions

Registers

Tiny super-fast memory INSIDE the CPU

Clock Speed

How many instructions per second (GHz). Higher = faster

🧠 Mnemonic — CPU Registers

PC, IR, MAR, MDR, Accumulator

"Please Immediately Make My Assignment"

📌 Key Registers

PC (Program Counter)

Points to NEXT instruction address

IR (Instruction Register)

Holds CURRENT instruction being executed

MAR

Memory Address Register — which address to access

MDR

Memory Data Register — holds data going to/from memory

Accumulator

Stores results of ALU operations

💾 Memory Types

RAM

Volatile (data lost on power off). Stores running programs

ROM

Non-volatile (permanent). Stores BIOS/firmware

DRAM

Needs constant refresh. Used as main RAM. Cheaper

SRAM

No refresh needed. Faster. Used in cache

EPROM

Erase with UV light and reprogram

EEPROM

Erase/reprogram electrically (pen drives use this concept)

💡 Trick

RAM = Temp storage (like your desk) | ROM = Permanent (like a printed book)

⚡ Cache Memory

Cache

Super-fast memory between CPU and RAM. Stores frequently used data

L1 Cache

Smallest + fastest. Directly on CPU chip

L2 Cache

Larger, slightly slower. Usually on CPU chip

L3 Cache

Largest, slowest cache. Shared by all cores

Cache Hit

✅ CPU found data in cache — fast!

Cache Miss

❌ Not in cache — must fetch from RAM — slow

🧠 Levels

L1 Smallest-Fastest → L2 → L3 Largest-Slowest

🔢 Number Systems

System	Base	Digits
Binary	2	0, 1
Octal	8	0–7
Decimal	10	0–9
Hexadecimal	16	0–9, A–F

💡 Conversion Tips

Binary → Hex: Group 4 bits from right (1111=F, 1010=A)

Binary → Octal: Group 3 bits from right (101=5, 110=6)

Decimal → Binary: Divide by 2, read remainders bottom-up

📏 Memory Units (Must Know!)

Unit	Symbol	Size	Power of 2
Bit	b	0 or 1	—
Nibble	—	4 bits	2⁴ = 16 values
Byte	B	8 bits	2⁸ = 256 values
Kilobyte	KB	1,024 Bytes	2¹⁰
Megabyte	MB	1,024 KB	2²⁰
Gigabyte	GB	1,024 MB	2³⁰
Terabyte	TB	1,024 GB	2⁴⁰

🧠 Mnemonic

Bite Nibble Byte, Kids Might Get Tired Playing

Kilo → Mega → Giga → Tera → Peta (each ×1024)

⚡ Logic Gates — Quick Reference

Gate	Output Rule
NOT	Flips 0→1 or 1→0
AND	Output 1 only if ALL inputs = 1
OR	Output 1 if ANY input = 1
NAND	Opposite of AND (universal gate)
NOR	Opposite of OR (universal gate)
XOR	Output 1 if inputs are DIFFERENT
XNOR	Output 1 if inputs are SAME

💡 Trick

NAND & NOR = "Universal Gates" — can build ANY other gate from them!

XOR Trick: X = eXclusive OR = "one or the other but NOT both"

📋 De Morgan's Laws

First Law: NOT(A AND B) = NOT A OR NOT B
A·B̄ = Ā + B̄

Second Law: NOT(A OR B) = NOT A AND NOT B
A+B̄ = Ā · B̄

🧠 Trick

De Morgan = "Break the bar, change the operator"
Break the NOT bar → the AND flips to OR (or vice versa)

📐 Boolean Laws

Identity

A·1 = A    A+0 = A (neutral element)

Null

A·0 = 0    A+1 = 1 (dominator)

Complement

A·Ā = 0    A+Ā = 1

Idempotent

A·A = A    A+A = A

🖥️ Operating System

OS Functions

Process Management

Runs multiple programs — scheduling, multitasking

Memory Management

Gives RAM to programs, implements virtual memory

File Management

Create/delete/read/write files on storage

Device Management

Talks to hardware via device drivers

Security

Authentication, access control, protection

OS Types

Batch OS

Jobs grouped and run without user interaction

Time-Sharing OS

Many users share CPU — each gets a small time "quantum"

Real-Time OS (RTOS)

Strict time limits — used in aircraft, medical devices

Distributed OS

Many computers work as one system

Virtual Memory

Uses HDD as extra RAM when RAM is full

Deadlock

Two processes stuck waiting for each other — forever!

🧠 OS Scheduling Algorithms

FCFS · SJF · Round Robin · Priority

FCFS = First Come First Served | SJF = Shortest Job First

RISC — Reduced Instruction Set

• Few, SIMPLE instructions
• Fixed-length instructions
• 1 clock cycle per instruction
• Large number of registers
• Load/Store architecture
• Examples: ARM, MIPS, RISC-V

CISC — Complex Instruction Set

• Many, COMPLEX instructions
• Variable-length instructions
• Multiple clock cycles
• Fewer registers
• Many memory-access instructions
• Examples: Intel x86, x86-64

💡 Trick

RISC = Simple & Fast (like a sprinter) | CISC = Complex & Powerful (like a weightlifter)
Mobile phones use RISC (ARM) — that's why they're power-efficient!

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2

Application Software

📝 Word Processor

WYSIWYG

"What You See Is What You Get" — screen = printed output

Mail Merge

Auto-create personalised letters by combining template + data

Macro

Recorded sequence of commands to automate repetitive tasks

Track Changes

Record edits so they can be accepted or rejected later

Watermark

Faint background text/image (e.g., "CONFIDENTIAL")

💡 Examples

MS Word · LibreOffice Writer · Google Docs

📊 Spreadsheet

Cell

Single box — identified by column letter + row number (A1)

Absolute Reference

$A$1 — does NOT change when formula is copied

Relative Reference

A1 — DOES change relative to new position when copied

Pivot Table

Flexible data summary tool — drag and drop to analyse

Conditional Formatting

Auto-colour cells based on their values (e.g., red if < 0)

💡 Trick: $ means STUCK!

$A$1 = dollar signs = the cell address is "stuck/fixed" when you copy

=SUM(A1:A10) ← add range
=IF(A1>50,"Pass","Fail") ← logic
=VLOOKUP(val,range,col,0)

Compiler

• Translates ENTIRE program at once
• Creates executable (.exe) file
• FASTER execution
• Shows ALL errors at once
• Examples: C, C++

Interpreter

• Translates LINE BY LINE
• No separate output file
• SLOWER execution
• Stops at FIRST error
• Examples: Python, JavaScript

🧠 Trick

Compiler = Book translator (translates whole book first, then you read) | Interpreter = Live translator (translates each sentence as you speak)

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3

Python Programming

🐍 Python Basics

Interpreted

Code runs line by line (no compilation needed)

Case Sensitive

"name" ≠ "Name" — they are different!

Indentation

Uses spaces/tabs to define code blocks (NOT curly braces {})

Dynamic Typing

No need to declare data type — Python figures it out

💡 Trick

Python = Pretty, Yet Tremendously Helpful, Open, Nested language 😄

📦 Data Types

Type	Example	Key Trait
int	42, -7	Whole numbers
float	3.14	Decimal numbers
str	'Hello'	Text (immutable)
bool	True/False	Logic values
list	[1,2,3]	Ordered, mutable
tuple	(1,2,3)	Ordered, immutable
dict	{'a':1}	Key-value pairs
set	{1,2,3}	Unordered, unique

💡 Mutable vs Immutable

Can change: list, dict, set  |  Cannot change: str, tuple, int, float

🔢 Operators Cheatsheet

# Arithmetic
5 + 3 = 8    5 - 3 = 2
5 * 3 = 15   5 / 2 = 2.5 (float!)
5 // 2 = 2   5 % 2 = 1   2**3 = 8

# Comparison → returns True/False
==  !=  >  <  >=  <=

# Logical
and  or  not

💡 Trick: // vs /

// = floor division (drops decimal)  |  / = always gives float
5//2 = 2    5/2 = 2.5

🔁 Loops & Control

# for loop
for i in range(1, 6):
    print(i) # prints 1 to 5

# while loop
while x > 0:
    x -= 1

break   ← exit loop now
continue ← skip this iteration
pass    ← placeholder (do nothing)

💡 range() trick

range(5) = 0,1,2,3,4  |  range(1,6) = 1,2,3,4,5  |  range(0,10,2) = 0,2,4,6,8

📋 List Methods

lst = [3, 1, 4, 1, 5]
lst.append(9) # add to end
lst.insert(0, 7) # insert at index 0
lst.remove(1) # remove first '1'
lst.pop(2) # remove at index 2
lst.sort() # sort in place
lst.reverse() # reverse in place
len(lst) # length

💡 Slicing

lst[1:4] = elements at index 1,2,3 (stop not included!)
lst[-1] = last element

⚠️ Exception Handling

try:
    x = 10 / 0
except ZeroDivisionError:
    print("Can't divide by zero!")
else:
    print("Success!")
finally:
    print("Always runs")

Error	Cause
ZeroDivisionError	Division by zero
ValueError	int('abc')
IndexError	List index out of range
KeyError	Dict key not found
FileNotFoundError	File doesn't exist

🐛 Types of Errors

Syntax Error

Grammar rule broken — program won't run at all

if x > 5 # ← missing colon!

Logical Error

Program runs BUT gives wrong output. Hardest to find!

area = l + w # should be l * w

Runtime Error

Crashes WHILE running. Also called Exception

x = 10 / 0 # ZeroDivisionError

📐 Operator Precedence (High → Low)

( ) Parentheses → ** Exponent → * / // % → + - → Comparison → not → and → or

🧠 Mnemonic

PEMDAS → Please Excuse My Dear Aunt Sally

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4

Data Structures

📚 Stack — LIFO

← TOP (last in)

Item 3

Item 2

Item 1 (first in)

LIFO

Last In, First Out — like a stack of plates!

Push

Add element to TOP. Stack Pointer decrements

Pop

Remove from TOP. Stack Pointer increments

Overflow

Push on a FULL stack → error

Underflow

Pop from an EMPTY stack → error

💡 Real Uses

Undo button · Browser back button · Function calls · Expression evaluation

🚶 Queue — FIFO

FRONT→

First

Item

Last

←REAR

FIFO

First In, First Out — like a queue at a ticket counter!

Enqueue

Add element at REAR (back)

Dequeue

Remove element from FRONT

💡 Real Uses

Print spooling · CPU scheduling · Keyboard buffer · BFS algorithm

🧠 Stack vs Queue

Stack = Plates on a table (top only) | Queue = People in a line (join back, leave front)

🔗 Linked List

Node

Each element = data + pointer to next node

Head

Pointer to the FIRST node

Null/None

Last node's pointer = None (marks the end)

Singly

Each node → next only (one direction)

Doubly

Each node → next AND previous (both directions)

Circular

Last node points BACK to first (forms a circle)

💡 Linked List vs Array

Array: Fixed size, contiguous memory | Linked List: Dynamic size, scattered memory connected by pointers

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5

Computer Networks

🌐 Network Types

Type	Range	Example
PAN	Few meters	Bluetooth
LAN	Building/Campus	Office network
MAN	City	Cable TV network
WAN	Country/World	The Internet

🧠 Mnemonic

People Love Making Wide networks

PAN → LAN → MAN → WAN (size increases!)

🔧 Network Devices

Hub

Broadcasts to ALL devices (dumb) — Layer 1

Switch

Sends to SPECIFIC device using MAC address — Layer 2

Router

Connects DIFFERENT networks using IP — Layer 3

Modem

Converts digital ↔ analog signals (computer ↔ phone line)

Gateway

Connects networks using DIFFERENT protocols

💡 Trick

Hub = Shouts (everyone hears) | Switch = Whispers (only target hears) | Router = GPS (finds the path)

📡 OSI Model — 7 Layers

7

Application

HTTP, FTP, SMTP, DNS — user-facing services

6

Presentation

Data format, encryption, compression

5

Session

Manages sessions between applications

4

Transport

TCP/UDP — end-to-end delivery, error checking

3

Network

IP addresses, routing — Routers work here

2

Data Link

MAC addresses — Switches work here

1

Physical

Raw bits over cable/wireless — Hubs work here

🧠 Mnemonic (Top→Bottom: 7→1)

"All People Seem To Need Data Processing"

Application · Presentation · Session · Transport · Network · Data Link · Physical

📋 Key Networking Protocols

Protocol	Full Form	Purpose
HTTP	HyperText Transfer Protocol	Web page transfer
HTTPS	HTTP Secure	Encrypted web (uses SSL/TLS)
FTP	File Transfer Protocol	Transfer files between computers
SMTP	Simple Mail Transfer Protocol	SEND email
POP3	Post Office Protocol 3	RECEIVE email (downloads to device)
IMAP	Internet Message Access Protocol	RECEIVE email (stays on server)
DNS	Domain Name System	Domain name → IP address
DHCP	Dynamic Host Config Protocol	Auto-assign IP addresses
TCP	Transmission Control Protocol	Reliable, ordered delivery
UDP	User Datagram Protocol	Fast but unreliable (video calls, gaming)

💡 POP3 vs IMAP Trick

POP3 = Downloads email to your device (like picking up your mail) | IMAP = Keeps on server, syncs everywhere (like reading mail online)

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6

Database Management & SQL

🗃️ Key Terms

DBMS

Software to create/manage databases (MySQL, Oracle, SQLite)

RDBMS

Relational DBMS — data stored in tables with relationships

Primary Key

UNIQUE identifier for each row. Can't be NULL or duplicate

Foreign Key

Links two tables — references another table's primary key

Candidate Key

Any field that COULD be a primary key

Cardinality

Number of ROWS (tuples) in a table

Degree

Number of COLUMNS (attributes) in a table

💡 Trick

Cardinality = Cars in a parking lot (rows, can change) | Degree = Degrees/angles (columns, structure)

📊 SQL Command Types

Category	Commands	Purpose
DDL	CREATE, ALTER, DROP	Define structure
DML	SELECT, INSERT, UPDATE, DELETE	Work with data
DCL	GRANT, REVOKE	Permissions
TCL	COMMIT, ROLLBACK	Transactions

🧠 Mnemonic

DDL Defines · DML Manipulates · DCL Controls · TCL Transacts

💻 SQL Commands — Quick Reference

CREATE TABLE

CREATE TABLE Students (
  RollNo INT PRIMARY KEY,
  Name VARCHAR(50),
  Marks INT
);

SELECT with conditions

SELECT Name, Marks
FROM Students
WHERE Marks > 80
ORDER BY Marks DESC;

Aggregate Functions

SELECT COUNT(*), AVG(Marks),
       MAX(Marks), MIN(Marks)
FROM Students
GROUP BY City
HAVING COUNT(*) > 2;

LIKE & BETWEEN

-- Name starts with 'R'
WHERE Name LIKE 'R%'
-- _ = any ONE character
WHERE Marks BETWEEN 60 AND 90

💡 WHERE vs HAVING

WHERE filters individual ROWS (before grouping) | HAVING filters GROUPS (after GROUP BY) — "Having filters the groups you've grouped!"

🔗 SQL Joins

INNER JOIN

Returns rows with MATCH in BOTH tables

LEFT JOIN

ALL rows from LEFT + matching from right (NULL if no match)

NATURAL JOIN

Joins on columns with SAME NAME automatically

CROSS JOIN

Cartesian product — every row × every row

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7

Cybersecurity

🦠 Malware Types

Virus

Attaches to files. Spreads when infected file runs

Worm

Self-replicates ACROSS networks — no host file needed

Trojan Horse

Disguised as legit software. Gives attacker backdoor access

Ransomware

Encrypts your files → demands money for decryption key

Spyware

Secretly watches you — steals passwords, activity

Keylogger

Records every keystroke — captures passwords!

Botnet

Network of zombie computers controlled by attacker

💡 Virus vs Worm

Virus = Needs a HOST to spread (like a biological virus) | Worm = Spreads ALONE through networks (like a worm in soil!)

⚔️ Cyber Attacks

Phishing

Fake emails/messages to steal your info

DoS Attack

Flood a server with traffic to crash it

DDoS

DoS from MANY computers at once (using botnet)

MitM

Man-in-Middle: secretly intercepts communication

SQL Injection

Inserts malicious SQL into web forms to attack database

Brute Force

Try ALL possible passwords until one works

Social Engineering

Manipulate PEOPLE psychologically to give info

🔐 Cryptography

Plaintext

Original readable data (before encryption)

Ciphertext

Encrypted, unreadable data

Encryption

Plaintext → Ciphertext (scramble it!)

Decryption

Ciphertext → Plaintext (unscramble it!)

Symmetric

SAME key for encrypt + decrypt. Fast. (AES, DES)

Asymmetric

Public key encrypts, Private key decrypts. (RSA)

Hash Function

One-way → converts data to fixed-size fingerprint. Can't reverse!

💡 Symmetric vs Asymmetric

Symmetric = Same key (like one key opens both lock & unlock) | Asymmetric = Public key is a padlock you can share; Private key opens it

🛡️ Security Measures

Firewall

Monitors & controls network traffic based on rules

Antivirus

Detects, prevents, removes malware

VPN

Encrypted tunnel for secure communication

2FA

Two-Factor Auth: password + OTP for extra security

SSL/TLS

Secure web communication (HTTPS uses this)

Backup

Copy data regularly to protect against ransomware

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8

Emerging Technologies

🤖 AI & Machine Learning

AI

Machines that simulate human thinking & learning

ML

AI subset: learns from data WITHOUT being explicitly programmed

Deep Learning

ML using neural networks with many layers

NLP

AI understands/generates human language (chatbots, voice assistants)

Supervised Learning

Train on LABELLED data — learns from examples with answers

Unsupervised Learning

Finds patterns in UNLABELLED data on its own

Reinforcement Learning

Learns by trial & error — reward good actions, penalize bad ones

💡 ML Types Trick

Supervised = Teacher gives answers | Unsupervised = Self-study | Reinforcement = Learn from mistakes (like a game)

☁️ Cloud Computing

Model	What You Get	Example
SaaS	Ready software via browser	Gmail, Google Docs
PaaS	Dev tools & environment	Heroku, App Engine
IaaS	Virtual machines, storage	AWS EC2, Azure VMs

🧠 Trick: SaaS > PaaS > IaaS

SaaS = Someone else handles everything (just use) | PaaS = Platform provided, you build app | IaaS = Raw infrastructure, you manage everything

📡 IoT & Blockchain

IoT

Physical devices connected to internet (smart home, wearables)

Sensor

Detects physical quantities (temp, motion) → digital data

Actuator

Takes physical ACTION from digital commands (e.g., opens door)

Big Data — 5 Vs

Volume · Velocity · Variety · Veracity · Value

Blockchain

Decentralised, immutable digital ledger of transactions

Smart Contract

Self-executing code on blockchain — auto-enforces agreements

🧠 Big Data 5 Vs

Very Very Valuable Vast Varied data

Volume · Velocity · Veracity · Value · Variety

🥽 Immersive Technologies

AR (Augmented Reality)

Overlays digital info on REAL world (Pokémon GO, Maps AR)

VR (Virtual Reality)

Fully REPLACES real world with digital (VR headset required)

MR (Mixed Reality)

Digital objects can INTERACT with real world (combines AR + VR)

XR (Extended Reality)

Umbrella term for AR + VR + MR

💡 AR vs VR

AR = Adds to reality (you still see the real world + digital overlay) | VR = Replaces reality (you're in a completely virtual world)

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9

Society, Law & Ethics

👣 Digital Footprint

Digital Footprint

Data trail you leave online — searches, posts, purchases

Active

Data YOU intentionally share (posts, form submissions)

Passive

Data collected WITHOUT your knowledge (cookies, IP tracking)

Cookie

Small file stored by browser to track activity & preferences

GDPR

EU law protecting your personal data online

⚖️ IT Act 2000 (India)

Section	Deals With
43	Unauthorised access (civil penalty)
66	Hacking — criminal penalty
66C	Identity theft — up to 3 years jail
66D	Cheating by impersonation
66E	Privacy violation — private images
67	Publishing obscene material

©️ Intellectual Property

Copyright

Protects creative works (books, software, music)

Patent

Protects inventions & innovations

Trademark

Protects brand names, logos (Apple logo, Nike swoosh)

Open Source

Source code freely available — use, modify, distribute

Proprietary

Paid license, source code hidden (MS Windows)

Freeware

Free to use but source code NOT shared

Shareware

Free trial → pay to keep using

💡 GPL Licence

GPL = "Virus-like licence" — any modification MUST also be open source (spreads openness!)

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★

Quick Reference & Exam Tips

📖 Important Abbreviations

CPU — Central Processing Unit

ALU — Arithmetic Logic Unit

RAM — Random Access Memory

ROM — Read-Only Memory

LAN — Local Area Network

WAN — Wide Area Network

DNS — Domain Name System

DHCP — Dynamic Host Config Protocol

DBMS — Database Management System

SQL — Structured Query Language

DDL — Data Definition Language

DML — Data Manipulation Language

AI — Artificial Intelligence

ML — Machine Learning

IoT — Internet of Things

NLP — Natural Language Processing

VPN — Virtual Private Network

LIFO — Last In First Out (Stack)

FIFO — First In First Out (Queue)

ASCII — American Standard Code for Info Interchange

RISC — Reduced Instruction Set Computer

CISC — Complex Instruction Set Computer

ARPANET — First packet-switched network (1969)

WWW — World Wide Web (invented by Tim Berners-Lee, 1991)

🎯 Exam Priority — What to Focus On

Topic	Expected Marks	Priority
Python Programming (all concepts)	15–20 marks	★★★ VERY HIGH
SQL Queries & Database	8–10 marks	★★★ VERY HIGH
Computer Networks (OSI, protocols)	8–10 marks	★★ HIGH
Data Structures (Stack, Queue, Linked List)	5–8 marks	★★ HIGH
Number Systems & Boolean Logic	5–8 marks	★★ HIGH
Cybersecurity (threats, encryption)	5 marks	★ MEDIUM
Emerging Technologies (AI, IoT, Cloud)	4–5 marks	★ MEDIUM
CPU, Memory, OS concepts	4–5 marks	★ MEDIUM

🧠 Master Mnemonics Summary

OSI 7 Layers (Top→Bottom)

"All People Seem To Need Data Processing"

Application · Presentation · Session · Transport · Network · Data Link · Physical

Memory Units

"Kids Might Get Tired Playing"

Kilo · Mega · Giga · Tera · Peta

CPU Registers

"Please Immediately Make My Assignment"

PC · IR · MAR · MDR · Accumulator

Network Types (Small→Large)

"People Love Making Wide networks"

PAN · LAN · MAN · WAN

Big Data 5 Vs

"Very Very Valuable Vast Varied"

Volume · Velocity · Veracity · Value · Variety

SQL Command Types

"DDL Defines · DML Manipulates · DCL Controls"

DDL=Structure · DML=Data · DCL=Access · TCL=Transactions

Stack vs Queue

Stack = Plates · Queue = People in line

Stack LIFO (top only) · Queue FIFO (join back, leave front)

Cache Levels

L1 Smallest-Fastest → L2 → L3 Largest-Slowest

All are faster than RAM!

⭐ Last-Day Study Strategy

📝 Write Definitions

Write each keyword 3× — active recall beats passive reading

💻 Code Python

Practice sorting, file handling, exception handling in Python

🗃️ SQL Queries

Write SELECT, WHERE, GROUP BY, HAVING, JOIN queries by hand

🌐 Network Diagrams

Draw Star, Bus, Ring, Mesh topologies and label the devices

⚡ Truth Tables

Practice NAND, NOR, XOR truth tables — exam favourites!

🧠 Understand WHY

Focus on why each concept exists — easier to reconstruct than memorise

Prepared by ExamPill · Computer Science Revision · TGT/PGT

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