Heap (data structure)

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

Computer memory

Shortest paths

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

Java (programming language)

Class (computer programming)

Software testing

References

List (abstract data type)

SLLists

Nested Classes

Debugging

Array (data structure)

Array Resizing

Inheritance (object-oriented programming)

Extends

Higher-order function (HOF)

Exception handling

Object Methods

Red Black Trees

Tree traversal

Multi-Dimensional Data

Prefix Operations and Tries

Reductions and Decomposition

Quick Sort

Algorithmic Bounds

Data structure

Scope

Kolmogorov complexity

Sentinel Nodes

DLLists

ALists

SLists

Implements

Casting

Subtype Polymorphism

Iterators

Asymptotics

B-tree

Priority queue (PQ)

Range Searching

Software Engineering

Radix Sorts

Compression

P=NP

Static

CS 61B: Data Structures UC Berkeley Fall 2022 CS 61B focuses on software efficiency from design and runtime perspectives. It covers object-oriented programming with Java, teaching data structures and various programming concepts. The course promotes hands-on learning with optional assignments. The CS 61 series is an introduction to Computer Science, with particular emphasis on software and machines from a programmer’s point of view. CS 61A covered high-level approaches to problem-solving, providing you with a variety of ways to organize solutions to programming problems as compositions of functions, collections of objects, or sets of rules. In CS 61B, we move to a somewhat more detailed (and to some extent, more basic) level of programming by focusing particularly on the efficiency of writing programs (design) and running programs (runtime).  This class assumes you have taken CS 61A, CS 88, or E 7, or have equivalent background to a student who has taken one of these courses. The course is largely built upon the assumption that you have taken CS 61A. CS 88 and E7 students may find the beginning of the course to be a bit scarier, particularly when it comes to object oriented programming. We assume you are coming in with zero Java experience, but we will move through basic Java syntax very quickly.

We recommend all students to complete the [optional introductory assignment](https://fa22.datastructur.es/materials/hw/hw0/) by the beginning of the semester to get comfortable with Java and practice some of the programming skills expected by this class.

If you already have Java experience, great! We hope that you’ll help out your fellow students in discussion, lab, and on our class forum, particularly in the opening weeks when everyone is catching up on Java. **There is no required textbook for the class.**

There is an online textbook written by myself and a large team of former TAs. It can be found at https://joshhug.gitbooks.io/hug61b. If you find these notes insufficient, you might consider consulting [Paul Hilfinger’s (free) Java Reference](http://www-inst.eecs.berkeley.edu/~cs61b/fa14/book1/java.pdf) or [Head First Java, 2nd Edition by Sierra and Bates (O’Reilly, 2005)](https://www.google.com/search?q=head+first+java). These are not required for the course. The **optional** textbook for the weeks 5-14 of the course is Algorithms, 4th Edition by Wayne and Sedgewick.

The official description of the Java core language is available online in [The Java Language Specification](https://docs.oracle.com/javase/specs/jls/se17/html/index.html) (Java SE 17 Edition) by James Gosling, Bill Joy, Guy Steele, Gilad Bracha, Alex Buckley, Daniel Smith, and Gavin Bierman. It’s extremely thorough and precise, at the expense of being quite dense and technical. You will find the official [Java 17 documentation](ttps://docs.oracle.com/en/java/javase/17/docs/api/index.html) to be useful as well

CS 61B: Data Structures

Rust

C Programming

Function (computer programming)

Modules

Compilation

Makefiles

File I/O

Buffering

POSIX I/O

System Calls

Directories

C++ Programming

Introduction

Const

Constructors

new/delete

Smart pointer

Client-side Networking

HTTP

Templates

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

Bitwise Operations

x86-64

Privacy

C (programming language)

Assembly: Arithmetic and Logic

Trust

C Generics

Assembly: Control Flow

Managing the Heap

Buffer overflow

Data Representation

Function Pointers

Assembly: Function Call

Optimization

Overflow

Reverse Engineering

Caching

CS 107 Computer Organization & Systems Stanford University Autumn 2022 This Stanford University course delves into the depths of computer systems and programming. It continues from the introductory sequence, expanding students' programming experience using the C language, exploring machine-level code, computer arithmetic, memory management, and more. CS107 is the third course in Stanford's introductory programming sequence. The CS106 courses provide you with a solid foundation in programming methodology and abstractions, and CS107 follows on this to build up and expand your breadth and depth of programming experience and techniques. The course will work from the C programming language down to the microprocessor to de-mystify the machine. With a complete understanding of how computer systems execute programs and manipulate data, you will become a more effective programmer, especially in dealing with issues of debugging, performance, memory, and robustness. Topics covered include: the C programming language, data representation, machine-level code, computer arithmetic, elements of code compilation, optimization of memory and runtime performance, and memory organization and management.

### CS107A

CS107A, also called Pathfinders (or ACE), is a supplementary instruction program that meets for a weekly section and holds Pathfinders-specific review sessions. CS107A is application-only; please see the [FAQ](https://web.stanford.edu/class/archive/cs/cs107/cs107.1232/faq.html) page for more information. The goals for CS107 are for students to gain mastery of

- writing C programs with complex use of memory and pointers
- an accurate model of the address space and compile/runtime behavior of C programs

to achieve **competence** in

- translating C to/from assembly
- writing programs that respect the limitations of computer arithmetic
- identifying bottlenecks and improving runtime performance
- working effectively in a Unix development environment
- using ethical frameworks and case studies to inform decision-making

and have **exposure** to

a working understanding of the basics of computer architecture The prerequisite for CS107 is CS106B/X (or equivalent). You should have practical C/C++ skills using recursion, dynamic data structures (pointers, linked lists, trees, graphs), data abstraction, classic data structures (lists, stacks, queues, sets, maps), and standard algorithms (searching, sorting, hashing). You should have an appreciation of the intrinsic value of good engineering and design and you will be expected to produce well-decomposed, readable code. Come talk with us if you need help determining the right placement for you. **Required**: Bryant & O’Hallaron. Computer Systems: A Programmer’s Perspective. 3rd Edition.

The bookstore has a less-expensive custom version of this textbook for our course that includes only the chapters we will cover; you can also use the regular full 3rd edition. You will need the 3rd edition of the textbook, which has substantial updates from IA32 to x86-64. There will be assigned readings from this textbook that are important preparation for lecture and lab. For readings that we assign, you can view a free digital PDF copy of the textbook on Canvas under the "Files" tab.

**Strongly recommended**: We also strongly recommend you have a "C language goto" in whatever form works best for you: textbook, tutorial, reference sheet, website, etc. As one suggestion, The C Programming Language by Kernighan and Ritchie is the classic text and a digital copy is available for checkout via [Open Library](https://openlibrary.org/books/OL2030445M/The_C_Programming_Language) (make a free account to "borrow" it digitally). Another option is Nick Parlante's Essential C reader PDF [available here](http://cslibrary.stanford.edu/101).

There is also a CS107 reader written by Chris Gregg, another CS107 instructor: [https://web.stanford.edu/~cgregg/cgi-bin/107-reader](https://web.stanford.edu/~cgregg/cgi-bin/107-reader), which covers all of the course topics in detail.

Our lecture readings pull from Bryant & O'Halloran, Kernighan & Ritchie, and Essential C.

CS 107 Computer Organization & Systems