Computer memory

Abstract Data Type (ADT)

Stack (abstract data type)

Queue (abstract data type)

Map (higher-order function)

Algorithmic Analysis

Case Analysis

Algorithm Analysis

Asymptotic Analysis

Recursive Algorithm Analysis

Binary Search Tree (BST)

Hashing

AVL Trees

Tree (data structure)

Graphs

Breadth-first search (BFS)

Depth-first search (DFS)

Topological sorting

Graph traversal

Minimum Spanning Tree (MST)

Disjoint Sets

Dynamic programming

Graph Modelling

Sorting algorithm

P/NP

Shortest paths

Heap (data structure)

CSE 373 Data Structures and Algorithms University of Washington Summer 2022 This course focuses on common data structures and algorithms. It integrates theoretical understanding with practical exercises, preparing students for software-related roles and industry technical interviews. Programming projects, unit testing, and source control techniques are emphasized.  In this course, you will gain a strong theoretical and conceptual understanding of common data structures and algorithms, as well as how to apply them within larger programming projects.

Specific topics we will cover include:

- **Data structures and ADTs**: lists, stacks, queues, sets, dictionaries, linked lists, arrays, trees, balanced trees, AVL trees, hash tables, priority queues, binary heaps, and disjoint sets.
- **Graphs and graph algorithms**: graph search, shortest path, and minimum spanning trees.
- **Algorithm analysis**: asymptotic analysis, and P and NP complexity classes.
- **Sorting** and divide-and-conquer.

This course is designed to have a practical component to help you gain basic familiarity with techniques used within industry. In particular, you’ll be asked to:

- Work on **programming projects** and integrate your work in an existing codebase.
- Learn how to use an **industrial-strength IDE**.
- Learn techniques for **checking correctness**: writing unit tests with JUnit, designing and checking invariants, etc.
- Learn how to collaborate on a single code base using **source control** repositories.

Finally, this course emphasizes the importance of making and justifying design decisions. Taken together, all of the above skills are chosen to set you up for success in a software-related role. In fact, this course is typically regarded as useful preparation for industry and technical interviews. [CSE 143](https://courses.cs.washington.edu/courses/cse143/), or similar Java programming experience. 

CSE 373 Data Structures and Algorithms

Data Structures and Algorithms

Assembly

Heap Allocator Work Time

Unix

Binary Representation

C Strings

Integers

Bitwise Operators

String (computer science)

Generics

Explicit List

CS 107A: Problem-solving Lab for CS 107 Stanford University Autumn 2022 This supplementary section provides extra support for CS 107 students. It offers an opportunity to review and practice course material in a small group setting, boosting understanding of CS 107 content. It uses a Satisfactory/No Credit grading scheme and is based on effort and participation. ### Welcome to 107A!

🌽 **CS 107A** is the [ACE](https://engineering.stanford.edu/students-academics/equity-and-inclusion-initiatives/undergraduate-programs/additional-calculus) section for [CS 107](https://cs107.stanford.edu), meeting two hours a week to give students an opportunity to review and practice course material in a smaller group setting. We also have CS 107A-specific office hours and support such as exam review sessions to help you do your best in CS 107.

### What is CS107A?

CS 107A is the ACE course for CS107. We spend two hours a week reviewing and practicing CS 107 material in a small-group environment. CS 107A also offers CS 107A-specific office hours and exam review sessions. CS 107A is worth 1 unit and uses a Satisfactory/No Credit grading scheme. Grading is based on effort and participation. If you feel like you would benefit from extra support as you take CS 107, Consider applying to take the course. If your application is accepted, you will be given a permission number in advance of the Add/Drop deadline to enroll in CS 107A on Axess, but you should attend class in the meantime anyway. - To provide students with extra opportunities to review and practice CS 107 material
- To provide an environment where students feel supported and part of a community as they take CS 107  About Ace
### About Ace

Additional Calculus for Engineers (ACE) is designed to provide the skills and solid foundation in mathematics, computational math in engineering, and computer science to undergraduate students interested in pursuing an engineering degree.

The goal of ACE is to increase confidence and increase content knowledge through small group interactive sessions and the academic resources provided to students enrolled in the program.

CS 107A: Problem-solving Lab for CS 107

Computer Systems

Abstract Data Structures

Recursion (computer science)

C++ Classes

Memory management

Implementation-level abstractions

Linked data structures

Python

Grids

Set (abstract data type)

Backtracking

Pointer (computer programming)

Binary Search Trees

Fractals

Dynamic Memory

Implementing `StackInt`

Linked list

Huffman Coding

Graph Shortest Path Algorithms

Big-O notation

Procedural Recursion

Vector (C++)

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

Rust

C Programming

Function (computer programming)

Array (data structure)

Data structure

Modules

Compilation

Debugging

Makefiles

File I/O

Buffering

POSIX I/O

System Calls

Directories

C++ Programming

Introduction

References

Const

Constructors

Class (computer programming)

new/delete

Smart pointer

Casting

Client-side Networking

HTTP

Templates

Inheritance (object-oriented programming)

Networks

Server-side Networking

Standard Template Library (STL)

vtables

IP (Internet Protocol)

DNS (Domain Name System)

CSE 333 Systems Programming University of Washington Summer 2022 This course provides an understanding of systems in computing, focusing on operating systems, networking, and C/C++ languages. Students learn about low-level data representation, memory management, system interactions, and efficient programming workflows. It delves into C++ idioms, network protocols, and concurrency. Prior knowledge of C programming and Linux tools is required. Systems Programming is the exploration of the composition and interface of systems in computing looking through the lens of operating systems, networking, and C/C++ languages. Through peeling levels of abstraction, students will view practices of low-level data representation (e.g. C, C++); explicit memory management; interacting with operating-system services; and cache-aware programming. Course Learning objectives are the goals that are set out for you to accomplish in this course:

- Understand system theory of how a system interacts with its environment and controlling its input and output (feedback loops, input and output, deterioration, computation)
- Unravel layers of abstraction found within systems
- Describe multiple systems throughout the computing space (e.g. HTTP, Operating Systems, Threading, and Makefiles)
- Interpret and build an efficient workflow for programming in larger sized code bases
- Debug substantial C/C++ programs using debugging tools (GDB and Valgrind) - [CSE351 (The Hardware/Software Interface)](http://www.cs.washington.edu/education/courses/cse351): CSE 351 provides students with rudimentary knowledge of C programming; the ability to write, run, and debug programs; familiarity with Linux and the use of Linux compilation, editing, and debugging tools; a solid mental model of the relationship between high-level code (C) and assembly-level compiled code.
- [CSE 143 (Intro Programming II)](http://www.cs.washington.edu/education/courses/cse143): CSE 143 is not a direct prerequisite (CSE 351 prerequisite), but some of its topics are beneficial to review for CSE 333. This includes classes, inheritance, good style practices, and simple data structures such as linked lists, trees, hash tables, and queues. Further knowledge of Java and these data structures is not required, but could be helpful! ### Textbooks

There are no strictly required texts for this course. Most people will find it useful to have both a C and a C++ reference; suggestions are given below. The C++ Primer is strongly recommended as C++ is a big, complex language and it is hard to understand how it all fits together from just Google and Stack Overflow snippets and folklore.

#### Strongly Recommended:

C++ Primer (5th Edition), Lippman, Lajoie & Moo. ISBN 0-321-71411-3.

#### Suggested:

- [*C Programming Language (2nd Edition)*](http://www.amazon.com/Programming-Language-2nd-Brian-Kernighan/dp/0131103628/), Kernighan & Ritchie. ISBN 0-13-110362-8.
    - The definitive book on C from the people who created it. You will want to use an online reference for information about the latest libraries, but every serious programmer should study this book.
- [*Computer Systems: A Programmer's Perspective (3rd Edition)*](http://csapp.cs.cmu.edu/3e/home.html), Bryant & O'Hallaron, ISBN 0-13-409266-X.
    - Useful review of CSE 351 and background for many additional topics covered more extensively in CSE333.
- [*Effective C++: 55 Specific Ways to Improve Your Programs and Designs (3rd Edition)*](http://www.amazon.com/Effective-Specific-Improve-Programs-Designs/dp/tags-on-product/0321334876), Scott Meyers. ISBN 0321334879.
- [*Effective Modern C++: 42 Specific Ways to Improve Your Use of C++11 and C++14*](http://www.amazon.com/Effective-Modern-Specific-Ways-Improve/dp/1491903996), Scott Meyers. ISBN 1491903996.


### Proposed Topic List

- C Programming and idioms (Memory Management, cstdio, error handling, and structs)
- System Management Tools (Makefiles, Header Guards, GDB, and Valgrind)
- System Interfacing with Operating Systems (POSIX)
- C++ Programming and idioms (namespaces, templates, STL, smart pointers)
- C++ Classes and Inheritance (Classes, operator overloading, OOP)
- Network Programming and Protocols (POSIX, HTTP)
- Concurrency (pthreads)

CSE 333 Systems Programming

Operating Systems

Software testing

List (abstract data type)

Machine learning

Hash table

Object (computer science)

Polymorphism (computer science)

Exception handling

Debugger

Object-Oriented Programming (OOP)

Web scraping

Binary tree

Web API

Merge sort

Random testing

Binary expression tree

CSCI 0112 - Computing Foundations: Program Organization Brown University Fall 2022 CSCI 0112 progresses from CSCI 0111, focusing on structuring programs for solving isolated subproblems. It delves into various algorithms, implementations from abstract descriptions, data organization methods, and program efficiency. Ethical considerations in software development are underscored. Topics include data structures, OOP, web APIs, machine learning, and more. CSCI 0112 builds on the data-focused programming introduced in CSCI 0111. Students will learn how to structure their programs so that subproblems can be solved in isolation. We will discuss several algorithms–abstract descriptions of computations–and students will get practice implementing working programs from these abstract descriptions. We will continue our study of data organization, covering several new ways of storing and accessing information. We will also continue to discuss program efficiency; students will learn how to reason about the performance of their programs. Finally, like CSCI 0111, CSCI 0112 will foreground the ethical considerations programmers must think about when developing software.   

CSCI 0112 - Computing Foundations: Program Organization

Control flow

Expressions

Images

Dictionaries

Search algorithm

Decomposition

Python Control Flow

Graphics

List of Lists

Computer file

Data Science

Internet

Python Variables

Graphical Animation

Nested Structures

Function Variables

CS 106A: Programming Methodologies Stanford University Spring 2023 This is an introductory course offering step-by-step instruction on key programming concepts with Python, including control flow, decomposition, data science, and more. Students are guided through exercises to learn by doing. ### How Does This Class Work?

- Start the very beginning
- Careful to go step by step, little exercises every day
- Like swimming, you can't just read about it
- Learn by doing
- "reps" - Nick's favorite word
- Technology to practice ideas right away
- In just a couple weeks .. amazed at what you can do
- Partly because computers are powerful
- Partly because coding is easier than you think  No prior programming experience required. There is one required text for this class, entitled Karel the Robot Learns Python. It's a short interactive tutorial that introduces the major concepts in programming in the context of an extremely simple robot world. This text is available for free on the class website. In addition to this text, we will also have reference material on Python available via the class webpage.

CS 106A: Programming Methodologies

Address Space

Atomic instructions

Monitors

Starvation

Address translation

Page table

TLB (Translation Lookaside Buffer)

General I/O

Queueing Theory

Reliability

Distributed Decision Making

Remote Procedure Call (RPC)

Key-Value Stores

Quantum Computing

Threads & Processes

Fork

Sockets

Synchronization (computer science)

Lock Implementation

Semaphores

Scheduling (computing)

Segments

Caching

Demand Paging Policies

Performance

End-to-End Arguments

TCP/IP

NFS & AFS

DataCapsules

Device Drivers

Concurrency

Mutual Exclusion

Lock (computer science)

Readers/Writers

Deadlock

Virtual memory

Paging

Demand Paging

Storage Devices

Filesystem Design

Transactions

Networking

Distributed Storage

Chord

Inter-Process Communication (IPC)

Input/output

CS 162: Operating Systems and Systems Programming UC Berkeley Fall 2022 This course introduces operating systems design and related concepts. It covers topics like memory allocation, file systems, basic networking, transactions, and security. The course requires foundational knowledge in data structures, assembly language, C programming, and debugging. It aims to improve students' skills in debugging large programs and computational problem solving. The purpose of this course is to teach the design of operating systems and operating systems concepts that appear in other computer systems. Topics we will cover include concepts of operating systems, systems programming, networked and distributed systems, and storage systems, including multiple-program systems (processes, interprocess communication, and synchronization), memory allocation (segmentation, paging), resource allocation and scheduling, file systems, basic networking (sockets, layering, APIs, reliability), transactions, security, and privacy.  CS 61A, CS 61B, CS 61C, and CS 70, or equivalent courses. This means that you understand:

- Data structures: arrays, linked lists, binary trees, and hashing
- Assembly language programming
- The C programming language
- Debugging C using GDB
- CPU caches and memory hierarchy
- Virtual memory as covered in CS 61C
- CPU pipelines and basic digital logic design
- Basic knowledge of random variables and probability distributions as covered in CS 70


The TAs will spend a small amount of time reviewing some of the material you are less likely to remember. We will assume that you either know the material that is supposed to be covered in those courses, or that you are willing to learn the material as necessary. We will not spend time in lecture covering any of this material. **Perhaps more important than formal prequisites, however, is experience and maturity with debugging large programs, designing and implementing useful abstractions, and computational problem solving in general. This class will exercise your skills in these areas.**

If you feel that you would benefit from additional review of these prerequisites, we recommend using the following resources:

1. For a good review of probability as you’ll need it in this class, read through CS 70 Lecture Notes [15](https://inst.eecs.berkeley.edu/~cs70/sp14/notes/n15.pdf), [16](https://inst.eecs.berkeley.edu/~cs70/sp14/notes/n16.pdf), [17](https://inst.eecs.berkeley.edu/~cs70/sp14/notes/n17.pdf), [18](https://inst.eecs.berkeley.edu/~cs70/sp14/notes/n18.pdf), and [19](https://inst.eecs.berkeley.edu/~cs70/sp14/notes/n19.pdf).

1. Hennessy, John L. and Patterson, David A. *Computer Architecture: A Quantitative Approach*. 5th edition. **Although the main content of this book goes far more in-depth into computer architecture than you are expected to know for this class, the appendices provide an excellent overview of some of the prerequisites. Focus specifically on the sections below:**

- 2.1 and B.1 - B.4 (you can skip the sixth optimization in B.3) review caching, virtual memory, and memory hierarchies.
- C.1 - C.2 review CPU pipelines at the level of CS 61C. We are using the textbook “Operating Systems: Principles and Practice” by Anderson and Dahlin (A&D). The reading from this textbook is **strongly recommended**. There will be some additional readings that are not from this textbook that are freely available online. These will be linked on the course website in the "Readings" column for your viewing.

#### Strongly Recommended
[Operating Systems: Principles and Practice (2nd Edition)](http://ospp.cs.washington.edu/)
#### Recommended
[Operating Systems: Three Easy Pieces](http://pages.cs.wisc.edu/~remzi/OSTEP/)
#### Supplemental
[Linux Kernel Development (3rd Edition)](http://www.amazon.com/Linux-Kernel-Development-3rd-Edition/dp/0672329468)

CS 162: Operating Systems and Systems Programming