Asymptotic Analysis

Abstract Data Type (ADT)

Stack (abstract data type)

Queue (abstract data type)

Map (higher-order function)

Algorithmic Analysis

Case Analysis

Algorithm 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

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

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

String (computer science)

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