Vector (C++)

Abstract Data Structures

Recursion (computer science)

C++ Classes

Memory management

Implementation-level abstractions

Linked data structures

Python

Grids

Set (abstract data type)

Asymptotic Analysis

Backtracking

Pointer (computer programming)

Sorting algorithm

Binary Search Trees

Graphs

String (computer science)

Stack (abstract data type)

Map (higher-order function)

Fractals

Dynamic Memory

Implementing `StackInt`

Linked list

Huffman Coding

Graph Shortest Path Algorithms

Queue (abstract data type)

Big-O notation

Procedural Recursion

Computer memory

Tree (data structure)

Hashing

Heap (data structure)

CS 106B Programming Abstractions Stanford University Winter 2023 This course helps transition from coding to problem-solving using computers. The course explores techniques, tools, and models for problem-solving across disciplines using C++. Prior programming experience is assumed. A nonprofit needs to assign tasks to its volunteers so they get completed as fast as possible. A political scientist wants to determine how to allocate city council seats based on a popular vote. A climatologist wants to estimate how many trees are in a forest. A city planner wants to see whether a proposed development will be underwater as sea levels rise. A physicist wants to know why perturbations to a system cause cascading effects.

How can we use computing power to answer these questions?

This course is about transitioning from “I know how to write programs” to “I know how to solve problems with computers.” Over the course of ten weeks, we’ll explore an array of techniques, tools, and perspectives useful for modeling and solving problems. We’ll explore recursion and see how it can be used both to model the intricacies of nature and to optimally allocate resources. We’ll develop a rich vocabulary of structures that can both capture the position of a dancer in space and compress a data file. And we’ll see how to put these techniques to use in problems drawn from a range of disciplines. By the time you’ve completed this course, you’ll learn how to look at problems in fundamentally different ways and how to use those perspectives to create clean and elegant computational solutions.  CS106B assumes that you have a familiarity with programming at the level of CS106A or the AP Computer Science exam. Check out [our course placement page](https://web.stanford.edu/class/archive/cs/cs106b/cs106b.1234/course_placement) for more information about deciding whether CS106B is right for you. As always, feel free to get in touch with us if you have any questions.

A note: although this class uses C++, this class is primarily designed to teach abstraction, recursion, and algorithmic analysis. If you already know those topics and just want to learn C++, you may want to opt to take CS106L instead of CS106B. The required reading for this course is Eric Roberts' *Programming Abstractions in C++*. You can purchase a copy at the bookstore using this link:

> https://www.bkstr.com/stanfordstore/search/keyword/programming%2520abstractions

You can also use this online version, which is a 2012 draft version of the book.

> https://web.stanford.edu/dept/cs_edu/resources/textbook/

We assume that the majority of you have no prior programming experience in C++, and this textbook is a great resource to use at the start of the quarter as you’re transitioning into the language.

A helpful note from the School of Engineering:

> *“All students should retain receipts for books and other course-related expenses, as these may be qualified educational expenses for tax purposes. If you are an undergraduate receiving financial aid, you may be eligible for additional financial aid for required books and course materials if these expenses exceed the aid amount in your award letter. For more information, review your award letter or visit the [Student Budget website](https://financialaid.stanford.edu/undergrad/budget/index.html).”*

CS 106B Programming Abstractions

Computer Programming

Machine organization

System Programming

Memory allocation

Array (data structure)

struct (C programming language)

Data structure alignment

Collection Summary

Signed number representations

Assembly language

Calling Conventions

Caching

Operating system

Privilege separation

Memory protection

Virtual memory

Page table

Process Control

Process (computing)

Inter-Process Communication (IPC)

Thread (computing)

Race condition

Synchronization (computer science)

Synchronization Patterns

Deadlock

Networking

Scalability

Distributed Scalability

Failures

Consistency (database systems)

Real-world Distributed Systems

CS 131: Fundamentals of Computer Systems Brown University Spring 2020 This course delves deep into the foundational principles behind computer systems, ranging from hardware intricacies to the vast global internet. Students gain insights into systems programming, the architecture of computer systems, concurrency, and the dynamics of distributed systems. Notably, the curriculum includes projects that offer hands-on experience, like building library functions, creating a toy OS, and designing a scalable key-value storage service. It's a stepping stone to advanced courses like Distributed Systems, Databases, and Computer Systems Security. The goal of **CS 131/CSCI 1310** is to teach the fundamentals behind the "magic" of computer systems from the hardware level to the global internet. We'll cover the ideas, principles and abstractions that unify computer systems design – from how your laptop runs multiple programs at the same time, to how companies like Instagram, AirBnB, and Google operate large websites, to how easy it is to exploit security vulnerabilities on badly designed systems. This is a great class for students who are interested in learning **what** systems programming is, **how** systems work, and **why** these systems are so critical to modern technology. We will look at topics arranged in four main blocks during the course, building up your understanding across the whole systems stack:

1. **Computer Systems Basics**: programming in systems programming languages (C and C++); memory; how code executes; and why machine and memory organization mean that some code runs much faster than other code that implements the same algorithm.
    *Project*: you will build your own versions of standard library functions and a vector data structure (strvec), and you will develop your own debugging memory allocator, helping you understand common memory bugs in systems programming languages (DMalloc).
1. **Fundamentals of Operating Systems**: how your computer runs even buggy or incorrect programs without crashing; how it keeps your secrets in one program safe from others; and how an operating system like Windows, Mac OS X, or Linux works.
    *Project*: you will implement memory isolation via virtual memory in your own toy operating system (WeensyOS)!
1. **Concurrency and Parallel Programming**: how your computer can run multiple programs at the same time; how you can share memory even if running programs on multiple processors; why programming with concurrency is very difficult; and how concurrency is behind almost all major web services today.
    *Project*: you will implement the server-side component of a peer payment application called "Vunmo", and make it handle requests from many users.
1. **Distributed Systems**: what happens when you use more than one computer and have computers communicate over networks like the Internet; how hundreds of computer can work together to solve problems far too big for one computer; and how programs running distributedly can survive the failure of participating computers.
    *Project*: you will implement a sharded key-value storage service that can (in principle) scale over hundreds or thousands of machines.

The first block, Computer Systems Basics, begins today. It's about how we represent data and code in terms the computer can understand. But today's lecture is also a teaser lecture, so we'll see the material raise questions that you cannot yet answer (but you will, hopefully, at the end of the course!). CS 131/CSCI 1310 is open to anyone who has completed the introductory sequence (i.e., CS 16, 18, or 19). For students who don't satisfy the registration restrictions on CAB, please request an override code on CAB and include an explanation of your course experience, and we'll review your request. **What does CS 131 count for?** CS 131/CSCI 1310 is a 1000-level course that can count as a related course in the systems pathway of the CS concentration and masters. In addition, CS 131 will satisfy the prerequisites for CSCI 1380 (Distributed Systems), CSCI 1270 (Databases), CSCI 1650 (Software Security and Exploitation), CSCI 1660 (Computer Systems Security), CSCI 1730 (Programming Languages), CSCI 1951-A (Data Science), CSCI 1680 (Computer Networks), and CSCI 2390 (Privacy-Conscious Computer Systems).

CS 131: Fundamentals of Computer Systems

Computer Systems

Vector

Vector (C++)

2 courses cover this concept

CS 106B Programming Abstractions

CS 131: Fundamentals of Computer Systems