Course Wrap-up and CS 107 Preview

CS 106B: Programming Abstractions

Fall 2024, Stanford University Computer Science Department

Lecturers: Cynthia Bailey and Chris Gregg, Head CA: Jonathan Coronado

Slide 2

Today's Topics

• Where we have been
• Where you are going
  • Preview of CS107

Slide 3

Where we have been

• Assignment 1: Getting your C++ Legs

• Soundex:

  Digit	represents the letters
  0	A E I O U H W Y
  1	B F P V
  2	C G J K Q S X Z
  3	D T
  4	L
  5	M N
  6	R

• Remember when you didn't know any C++? That wasn't that long ago!
• You've come a long way
• You now know a lot of C++ (but not all of it!)
• You've had plenty of practice with the debugger
  • This can be a lifeline for almost any programming language, from Python to C++ to Javascript to Assembly Language

Slide 4

Where we have been

• Assignment 2: Fun with collections

• Maze:

• Search Engine:

Stand by while building index...
Indexed 50 pages containing 5595 unique terms.

Enter query sentence (RETURN/ENTER to quit): llama
Found 1 matching pages 
{"http://cs106b.stanford.edu/assignments/assign2/searchengine.html"}

Enter query sentence (RETURN/ENTER to quit): suitable +kits
Found 2 matching pages 
{"http://cs106b.stanford.edu/assignments/assign2/searchengine.html", "http://cs106b.stanford.edu/qt/troubleshooting.html"}

• We've learned about a lot of collections this quarter!
  • Vectors and arrays
  • Grids
  • Sets
  • Maps
  • Stacks
  • Queues
  • Heaps and Priority Queues
  • Linked Lists
  • Trees
  • Hash Tables
  • Graphs

Slide 5

Where we have been

• Assignment 3: Recursion
• Sierpinski:

• Recursion was a big part of this class
  • You probably won't use recursion all that often in your own coding, but when you need it, it will come in very handy

Slide 6

Where we have been

• Assignment 4: Backtracking

• Tile Match:

• Banzhaf Power Index:

• Recursion with backtracking can be super powerful for solving all sorts of counting problems, and problems where we need to do a large, coordinated search.

Slide 7

Where we have been

• Assignment 5: Tone Matrix

• You used dynamic memory on the heap to create space for the tone data
• This was also good practice building C++ classes

Slide 8

Where we have been

• Assignment 6: Linked Lists
• You started with a maze (if you did the warmup):

• You moved on to particles:

Slide 9

Where we have been

• Assignment 7: Huffman

• You finished up the quarter with some very cool Huffman coding to compress text.

Slide 10

The Importance of Data Structures

• One reason we care about data structures is, quite simply, time. Let’s say we have a program that does the following (and times the results):
  • Creates five containers for data: unsorted vector, linked list, binary tree, hash table, sorted vector
  • Adds 100,000 elements to each container – specifically, the even integers between 0 and 198,998 (sound familiar?).
  • Searches for 100,000 elements (all integers 0-100,000)
  • Attempts to delete 100,000 elements (integers from 0-100,000)
• What are the results?

Slide 11

The Importance of Data Structures

Computer Science is embarrassed by the computer.
– Alan Perlis

• Results:
• Processor: Apple M1, 3.2GHz (Macbook Air), Compiler: clang++
• Compile options:

  clang++ -Os -std=c++11 -Wall -Wextra ContainerTest.cpp -o ContainerTest
  

Structure         Overall(s)
Unsorted Vector:  1.77514
Linked List:      6.53712
Binary Tree:      0.01465
Hash Table:       0.00400
Sorted Vector:    0.26143

• Difference between unsorted vector and hash table: 444x
• Difference between linked list and hash table: 1600x!
• Note: In general, for this test, we used optimized library data structures (from the "standard template library") where appropriate. The Stanford libraries are not optimized.
• Overall, the Hash Table "won" — but (as we saw!) while this is generally a great data structure, there are trade-offs to using it.

Slide 12

The Importance of Data Structures

Structure         Overall(s)    Insert(s)     Search(s)     Delete(s)
Unsorted Vector:  1.77514       0.00031       1.23618       0.53866
Linked List:      6.53712       0.00179       4.67681       1.85852
Binary Tree:      0.01465       0.01266       0.00133       0.00066
Hash Table:       0.00400       0.00318       0.00035       0.00047
Sorted Vector:    0.26143       0.18440       0.00135       0.07567

• Why are there such discrepancies??
  • Some structures carry more information simply because of their design.
  • Manipulating structures takes time

Slide 13

Where to from here?

• The CS Core:
  • Systems:
    • CS 106B, Programming Abstractions
    • CS 107, Computer Organization and Systems
    • CS 111, Operating Systems Principles
  • Theory:
    • CS 103, Mathematical Foundations of Computing
    • CS 109, Introduction to Probability for Computer Scientists
    • CS 161, Design and Analysis of Algorithms
• Other Courses you might like
  • CS 147, Introduction to Human-Computer Interaction
  • CS 108, Object-Oriented Systems Design
  • CS 193X, Web Programming Fundamentals

Slide 14

CS 103

• CS 103, Mathematical Foundations of Computing is a good course to take early in your CS path
  • Can computers solve all problems?
  • Why are some problems harder than others?
    • We can find in an unsorted array in O(n), and we can sort an unsorted array in O(n log n). Is sorting just inherently harder, or are there better O(n) sorting algorithms to be discovered?
  • How can we be certain??

Slide 15

CS 107

• CS 107 is a typical follow-on course to CS 106B
  • It is a classics systems class that covers many low-level topics
  • How do we encode text, numbers, programs, etc., using just 0s an 1s?
  • How are integers and doubles represented in memory?
  • How do we manage the memory our programs use? What is the difference between the stack and the heap?
  • What is assembly language and how does it work?
• CS 107 is not a litmus test for whether you can be a computer scientist
  • You can be a great computer scientist wihout enjoying low-level systems programming (though some understanding can be helpful)
• CS 107 is not indicitive of what programming is "really like."
  • CS 107 covers a lot of low-level programming. Most computer scientists don't regularly do low-level programming

Slide 16

How to Prepare for CS107

• You are prepared! CS106B is a great preparation!
• However, you might want to learn a few things before class
  • The terminal
  • You can log in to the myth machines right now with the terminal program (Mac/Linux) or on Windows with either the Windows subsystem for Linux, or with a downloadable terminal.

    /afs/ir/users/c/g/cgregg/cowsay/bin/cowsay Moooo
    
    ls /afs/ir/users/c/g/cgregg/cowsay/share/cows
    
    /afs/ir/users/c/g/cgregg/cowsay/bin/cowsay -f stegosaurus rowr  
    

Slide 17

How to log into the myth machines

• Open Terminal. Then:
• You only need to answer the question about whether you want to continue connecting once:
• You type your SUNet password, but it doesn't show up for security reasons:
• The ls command lists the files:
• There are other commands, such as whoami and who that shows your SUNet and then everyone else logged into that particular machine.

• Your first C program!

• But, you probably want a real editor!

Slide 18

Editor Choices

• There are lots of choices for a terminal editor
  • vi / vim
  • emacs
  • nano
  • Sublime Text / Atom / VS Code from your own computer (slower, but you edit everything on your own computer)
• Choosing an editor can be a big choice…
• If you want to learn how to use the vim editor, you can play Vim Adventures, which is a fun way to get up to speed.

Slide 19

How to prepare for CS107: Pointers

• Although we covered pointers in CS106B, you will really get to know them well in CS107. This is a good tutorial if you want to brush up.
• Pointer example – if you can understand this, you're in a good starting shape:

  #include <stdio.h>
   
  int main () {
     int   var;
     int*  ptr;
     int** pptr;
    
     var = 3000;
    
     /* take the address of var */
     ptr = &var;
    
     /* take the address of ptr using address of operator & */
     pptr = &ptr;
    
     /* take the value using pptr */
     printf("Value of var:\t%d\n", var );
     printf("Value of ptr:\t%p\n", ptr);
     printf("Value of *ptr:\t%d\n", *ptr );
     printf("Value of pptr:\t%p\n", pptr);
     printf("Value of *pptr:\t%p\n", *pptr);
     printf("Value of **pptr:\t%d\n", **pptr);
    
     return 0;
  }
  

• output:

  Value of var:	3000
  Value of ptr:	0x7ffee662f728
  Value of *ptr:	3000
  Value of pptr:	0x7ffee662f720
  Value of *pptr:	0x7ffee662f728
  Value of **pptr:	3000
  

Slide 20

C / C++ Differences

• What is this printf business from the last slide?
  • printf() is the way we print to the terminal in C. It is similar in function to C++'s cout but it is a more standard function.
• Let's talk about some C / C++ differences:
  • You will find C to be similar in feel to C++ (C++ is based on C, after all)
  • Things that are the same:
    • built-in data types: int, char, float, double, long, unsigned int
    • array indexing (using brackets, e.g., v[4])
    • function declarations
    • modularity between .h and .c files
    • control flow: while, if, for, etc.
  • Things that are different:
    • There isn’t a string type. Strings are NULL terminated arrays of chars.
    • There are no classes, no objects, and no constructors/destructors.
    • Memory management is more involved than in C++
      • To allocate memory, C uses malloc() (so can C++, but normally we use new())

Slide 21

Going from C++ to C

• Things that are the same but that you might not have learned about yet:
  • There are entities called “void pointers” which can point to any type
  • You often need to cast variables to different types
  • Pointer arithmetic is often used instead of bracket notation

Slide 22

From C++ to C

• C Strings are NULL terminated char arrays
• There is no string class in C. Let me repeat: there is no string class in C.
• Strings are simply arrays of characters, with the final character of the array set aside for the NULL character, which is 0.
• You must be careful to avoid buffer overflows when dealing with char strings.

Slide 23

From C++ to C

malloc() and free(), and sizeof(): used for memory management instead of new and delete

malloc() is used to reserve memory from the heap. You must pass it the size in bytes of the amount of memory you want. How do you know the size in bytes? You use sizeof():

• sizeof(int) returns the size of an integer. On our machines, this is 4 bytes, or 32-bits.
• malloc() returns a pointer to memory, e.g.,

  /* an array of 10 ints from the heap */
  int *int_ptr;
  int_ptr = malloc(sizeof(int)*10);
  

• malloc() returns NULL if the system runs out of memory.
• free() simply frees the previously allocated memory:

  /* an array of 10 ints from the heap */
  int *int_ptr;
  int_ptr = malloc(sizeof(int)*10);
  free(int_ptr);
  

Slide 24

Pointer arithmetic

• Here is an example that uses pointer arithmetic:

  #include<stdio.h>
  #include<stdlib.h>
  
  int main() {
    /* an array of 10 ints */
    int *int_ptr;
    int_ptr = (int *)malloc(sizeof(int) * 10);
  
    int i;
    for (i = 0; i < 10; i++) {
        *(int_ptr + i) = i * 10;
    }
    for (i = 0; i < 5; i++) {
        printf("%d\n", *(int_ptr + i * 2)); // what will print out? We'd better look at printf
    }
    free(int_ptr);
    return 0;
  }
  

Slide 25

printf

• printf is the way we print to standard out (stdout) in C
• printf() writes a formatted string to the standard output. The format can include format specifiers that begin with % and additional arguments are inserted into the string, replacing their formatters.
• Example: print the int variable, i:

  int i = 22;
  printf("This is i: %d\n", i);
  

• Output:

  This is i: 22
  

• printf has lots of format specifiers (you will only use a few in CS 107):

Slide 26

More printf examples

#include <stdio.h>
int main()
{
   printf ("Characters: %c %c \n", 'a', 65);
   printf ("Decimals: %d %ld\n", 1977, 650000L);
   printf ("Preceding with blanks: %10d \n", 1977);
   printf ("Preceding with zeros: %010d \n", 1977);
   printf ("Radices: %d %x %o %#x %#o \n", 100, 100, 100, 100, 100);
   printf ("floats: %4.2f %+.0e %E \n", 3.1416, 3.1416, 3.1416);
   printf ("Width trick: %*d \n", 5, 10);
   printf ("%s \n", "A string");
   return 0;
}

Output:

Characters: a A
Decimals: 1977 650000
Preceding with blanks:       1977
Preceding with zeros: 0000001977
Radices: 100 64 144 0x64 0144
floats: 3.14 +3e+000 3.141600E+000
Width trick:    10
A string

Slide 27

Going from C++ to C (example from before)

• What does the following print out?

  int main() {
      /* an array of 10 ints */
      int *int_ptr;
      int_ptr = (int *)malloc(sizeof(int)*10);
  
      int i;
      for(i=0;i<10;i++) {
          *(int_ptr+i)=i*10;
      }
      for(i=0;i<5;i++) {
          printf("%d\n",*(int_ptr+i*2)); // what will print out? We'd better look at printf
      }
      free(int_ptr);
      return 0;
  }
  

• Output:

  0
  20
  40
  60
  80
  

Slide 28

Other courses to consider taking: CS107e

• CS107e is an alternative to CS107, and it fulfills the requirements in the CS curriculum
• The class is a hands on version of the course, using bare metal (i.e., no operating system) Raspberry Pi computers.
• There is a lot of wiring, blinking lights, and a great final project that pushes you to build something unique and interesting.

Slide 29

Other courses to consider taking: CS109

• CS 109 is a probability class geared towards comptuer science majors
• It is narrative-driven, and also provides an introduction to machine learning.

Slide 30

Computer Science Affects Every Field

• It is virtually impossible to name a field that hasn't benefitted from computer science in some way.
• Examples in the image above:
  • Medicine
  • Space
  • Animation
  • Self-driving technology
  • Biomedical technology

Slide 31

Courses aren't necessary to continue your learning!

• Things to learn on your own:
  • A new programming language. Good candidates:
    • Javascript: the de facto standard on the World Wide Web
    • Haskell – a great functional programming language. Functional programming is very different than procedural programming (which we have been learning), and it is eye-opening to code in a functional language. The best online resource: Learn You a Haskell for Great Good
    • Swift – if you want to program for a Mac or iPhone
    • Java – if you want o learn to program an Android phone (also, Kotlin, a newer language for Android phones)
    • Python – if you didn't take CS 106A in Python, you should go learn Python right now. It is everywhere, and growing.
  • iOS / Android Programming: learn to program your phone!
    • Best iOS resource: https://www.raywenderlich.com
    • Good tutorials link: http://equallysimple.com/best-android-development-video-tutorials/
    • Want to code for all phones (and the web, and the desktop?) Check out React Native: https://facebook.github.io/react-native/
  • Hardware: Raspberry Pi, Arduino, FPGA: Hardware is awesome!
    • Raspberry Pi resources
    • Arduino Resources
    • FPGA resources
  • GPU and Multicore Programming: hard, but your code can fly
    • Your GPU might have hundreds of individual processors. Resources

Slide 32

It is the time and place for computer science

Source

Slide 33

Thank you!

• From all of the course staff: thank you for your hard work during this challenging
• Congratulations!