CS1010 AY24/25 S1 Lecture 1

# CS1010
## Programming Methodology

# Lecture 1

### 12 August 2024

Admin Matters 
Unit 1: **What is a Program?** 
Unit 2: **Computational Problems & Algorithms**

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### Ooi Wei Tsang

ooiwt@comp.nus.edu.sg

__Office__ : AS6 05-14

__Office Hour__ : Tuesday 1 - 2 PM

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### Eldon Chung

eldon.ch@nus.edu.sg

__Office__ : COM3 03-28

__Office Hour__ : Friday 11 - 12 PM

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### [Teaching Team](https://nus-cs1010.github.io/2425-s1/team.html)

- **2 lecturers + lab tutors**
    - Wei Tsang, Eldon

- **4 tutorial instructors**
    - Eric, Gizem, Malaika, Yunjeong

- **25 UG lab tutors**

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### Please read this:

[CS1010 Course Information and Policy](https://nus-cs1010.github.io/2425-s1/about.html)

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## Important Websites

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### CS1010 Handbook

[`https://nus-cs1010.github.io/2425-s1/`](https://nus-cs1010.github.io/2425-s1/)

lecture notes 
problem sets 
programming exercises 
guides

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### Piazza

[`https://piazza.com/nus.edu.sg/fall2024/cs1010/home`](https://piazza.com/nus.edu.sg/fall2024/cs1010/home)

ask questions

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### GitHub

[`https://www.github.com/`](https://www.github.com)

programming exercise submissions 
programming exercise feedback

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### Canvas

[`https://canvas.nus.edu.sg/courses/62224`](https://canvas.nus.edu.sg/courses/62224)

announcements 
quizzes 
grades 
survey 
etc.

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### RT (Request Ticket)

[`https://mysoc.nus.edu.sg/app/cs1010/`](https://mysoc.nus.edu.sg/app/cs1010/)

request to be excused from tests 
request for regrade 
etc.

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## Assessments

how you will be graded

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### Programming Exercises

- The most important formative component of CS1010.

- 60+ practice questions of various difficulties.

- Complete them to gain the skills and confidence of solving computational problems

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.smaller[
Assessment         | Date                       | Time
:------------------|:-------------------------- |:-------------
Midterm            | Mon, 30 Sep                | 4 - 6 PM
Final              | Fri, 25 Nov                | 1 - 3 PM
Practical Exam 0   | Tue, 1 Oct                 | 6 - 9 PM
Practical Exam 1   | Tue, 22 Oct                | 6 - 9 PM
Practical Exam 2   | Tue, 12 Nov                | 6 - 9 PM
]

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### Open Book Exam

- Bring any (analog) materials you want

- Nothing to memorize

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### Not "bell-curved"

- Your grade is based solely on you

- Not relative to others in the class

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## Expectations

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You are responsible for your own education.

Self-motivated to work hard, learn, and improve.

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The teaching team is here to facilitate and help.

Don't be afraid to ask questions.

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background-image: url(figures/meme/andy-too-afraid-to-ask.png)

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Help each other to learn and succeed.

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background-image: url(figures/not-alone.jpg)

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Read instructions and adhere to [the policies](https://nus-cs1010.github.io/2425-s1/about.html).

Respect deadlines.

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## Words of Advice

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### CS1010 is difficult

but useful

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background-image: url(figures/reddit_cs1010_made_me_cry.png)

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### Work hard consistently

Invest time to learn and practice

Don't fall behind

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### This is a fresh start

It does not matter:

how well you did academically 
how much you know about programming

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### Grade is not everything

Focus on:

learning new things 
level-up your skills 
enriching your experience

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### Take care of yourself

Mental wellness is important.

If you can't cope or is falling behind, talk to us.

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# Lecture 1

### 12 August 2024

Admin Matters 
Unit 1: **What is a Program?** 
Unit 2: **Computational Problems and Algorithms**

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## What is a program?

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### A sequence of step-by-step instructions given to computers to process data in order to perform a certain task.
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### How CPU Executes a Program

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### Machine Code

- Instructions that can be interpreted by a CPU

- Different CPU architecture may use different instruction sets

`1001010001011110100010101010101000101`

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### Assembly Language

- Use mnemonic to represent the instructions such as `incr`, `decr`, `store`, etc. in a more human-readable way.

- Still difficult to write: operation that is conceptually simple still requires multiple instructions to be issued.

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### Higher-Level Language

- Allow programmers to express an operation closer to their intention

- E.g., $x = x + y$ if $y < 0$

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### Higher-Level Languages

- FORTRAN (first popular programming language from 1950s)

- C (1972, still influential today)

- [Many many others](https://en.wikipedia.org/wiki/List_of_programming_languages)

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### Why C?

- It lets you have more control over how you use memory.  
- It forces students to think and understand how machine works.
- It is fast.

Important for InfoSec and CEG students.

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### Compilation

A compiler _compiles_ a program written in high-level language to machine code.

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## What will you learn in CS1010?

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### How a C program behaves

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### How to write C programs
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### Tools and techniques to write good and correct C programs
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### How to use C to solve computational problems
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### *Easy*: Write a program that does what you want

### *Harder*: Knowing what your program should do

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## What is a computational problem?

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### Computational problems

- are problems that can be solved _step-by-step_ by a computer

- have _well-defined_ inputs, outputs, and constraints

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### Example: Testing if integer is odd

![:scale 75%](../notes/figures/lec01/oddness.png)

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### Example: Is the input number a prime?

![:scale 75%](../notes/figures/lec01/primality.png)

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#### Example: Output the triangle in a network.

![:scale 75%](../notes/figures/lec01/triangle.png)

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### What is the meaning of life?

![:scale 75%](../notes/figures/lec01/notwelldefined.png)

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### Do I look good in this outfit?

![:scale 75%](../notes/figures/lec01/notwelldefined.png)

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### Types of Computational Problems:

1. Decision problems (e.g. Is there a path from point A to point B on a map?)

2. Search problems (e.g. Output a path from point A to point B if it exists.)

3. Optimization problems (e.g. Output the _shortest_ path from point A to point B if it exists.)

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### The Point:

#### In this course, we are in the business of writing programs to solve computational problems.

### The Point:

#### In this course, we are in the business of writing programs to solve computational problems.

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### Let's start with an experiment:
What I need you to do:
--

Pay special attention to your methods and strategy on how you solve the given problem.

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#### Find the maximum among this list of numbers:

```
5  9  8
1  3  2
```
--
So what was your strategy?

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### How about now? What's the maximum number here?

.tiny[
```
12  20  11  20  14  2   24  36  43  16  27  6   11  7 
10  15  38  10  22  7   16  26  32  30  11  9   30  6 
20  6   27  19  26  10  27  6   19  34  5   9   3   22
10  4   13  1   10  22  43  36  39  29  41  12  13  25
17  8   30  31  29  38  2   42  7   45  24  33  9   40
34  29  37  2   26  17  19  34  6   7   34  22  21  41
38  5   15  13  9   1   42  39  5   29  38  4   22  29
41  10  26  32  30  26  16  16  18  22  32  34  14  10
5   17  25  16  19  6   31  16  3   13  8   42  41  0 
13  30  44  1   41  14  5   39  40  38  6   37  38  9 
.

```
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What was your strategy this time?

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### How close does this match what you tried?

1. Scan the integers one-by-one

2. Keep track of the "max so far"

3. When we are done scanning, the "max so far" will be the answer.

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### Did you do any of the following:

1. Use an arbitrary/random sequence to go through the numbers?

2. Look at groups of numbers at a go?

3. Double back to look at the same numbers you already did?

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### Computational Thinking:

The thing is, computers aren't exactly like humans. 
They don't look at the list like this:

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### Computational Thinking:
It's easier for them to process singular values one by one:

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### Computational Thinking:
It's easier for them to process singular values one by one:

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### Computational Thinking:
It's easier for them to process singular values one by one:

### Computational Thinking:
It's easier for them to process singular values one by one:

### Computational Thinking:
It's easier for them to process singular values one by one:

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### Computational Thinking:
Also, they are very good at following precise instructions. 
So we will try to get them to read the list in a _fixed sequence_.
E.g. From first number to last number.

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### Computational Thinking:
Lastly, computers are really good at remembering things. 
So unlike us humans, they don't need to "double back" to re-check their results.

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### Computational Thinking:
Let's try to be less human 🤖 and try to get a computer 
to follow the same strategy.

To do this, we need to do a few things:

--
1. A problem formulation. (So that we know what the computer is given as input.)

--
2. A fixed set of instructions. (This describes the strategy to implement.)

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### Step 1: General Problem Formulation

- Input: $L$ = $\langle l\_0,...,l\_{k-1\} \rangle$

- Output: $m$

- Constraint $m$ should be from the input list $L$ and $m$ is the largest value 
among all of the values in $L$.

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### Step 2: Designing an implementable strategy.

But wait! We haven't told what kind of steps computers can make. And this is tricky

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