Databases

System R

File system

Flash File Systems

Isolation Levels

Transactional Recovery

Practical Byzantine Fault Tolerance

Exokernel

Resource Allocation and Scheduling

Edge Computing

Distributed Storage

MapReduce

Column Stores

Microkernels

Spectre Attack

Unix

Bigtable

End-To-End Arguments in System Design

File System Reliability

Transaction Locking

Concurrency

The Byzantine Generals Problem

Google File System (GFS)

Dynamo

seL4

Virtual Machine (VM)

Peer To Peer Networks

Distributed Consensus

Apache Spark

Security

CryptDB

CS 262a Advanced Topics in Computer Systems UC Berkeley Fall 2021 A graduate survey of systems managing computation and information. Topics include volatile and persistent memory management, system support for networking, security infrastructure, extensible systems, APIs, and large software system performance analysis. Students are expected to engage in quality systems research, culminating in a publishable group project. Graduate survey of systems for managing computation and information, covering a breadth of topics: early systems; volatile memory management, including virtual memory and buffer management; persistent memory systems, including both file systems and transactional storage managers; storage metadata, physical vs. logical naming, schemas, process scheduling, threading and concurrency control; system support for networking, including remote procedure calls, transactional RPC, TCP, and active messages; security infrastructure; extensible systems and APIs; performance analysis and engineering of large software systems. Homework assignments, exam, and term paper or project required.

The main work of this class is to read frequently and deeply, while working toward a group research project of publishable quality.  Each student will be individually responsible for writing up a short summary of every paper. There will be one midterm exam (albeit near the end), and no final exam. Research projects are a critical aspect of the course.  Your goal is to do some quality systems research; that is, to add to our understanding of how to build systems.  Research projects must be written up in a term paper, and will be presented in a poster in a departmental mini-conference.  Suggested project ideas will be provided by the instructors, but you are strongly encouraged to come up with your own project ideas.  Potential projects include implementation or analysis of some piece of an OS, a DBMS, or an Internet service; extending one of these systems with new functionality; or measurement and analysis of existing systems with the goal of better understanding issues in system design.   [CS 162](https://cs162.org/), or equivalent. There is no required textbook, but some of the papers are in [*Readings in Database Systems*](http://redbook.cs.berkeley.edu/). We will read and discuss 2-4 papers per week. Likely all of the papers will be available online.

General information: ISBN-10: 0-262-69314-3, ISBN-13: 978-0-262-69314-1

Link to MIT press site: [Readings in Database Systems, 4th Edition](http://mitpress.mit.edu/catalog/item/default.asp?tid=10480&ttype=2)

CS 262a Advanced Topics in Computer Systems

Computer Systems

Abstraction (computer science)

Loops

For Loop

Environment Diagrams

Dictionaries

Recursion (computer science)

Object-Oriented Programming (OOP)

Mutable Data

Linked list

Tree (data structure)

Generators

Function (computer programming)

List (abstract data type)

Higher-order function (HOF)

Lambda

Abstract Data Type (ADT)

Tree Recursion

Inheritance (object-oriented programming)

Efficiency

Exception handling

Iterators

Programming Paradigms

CS 88: Computational Structures in Data Science UC Berkeley Fall 2022 This course provides an introduction to computer science with an emphasis on functional programming, data abstraction, object-oriented programming, and program complexity. The course teaches foundational programming concepts primarily in Python. CS 88 is a "connector" for Data 8 that is designed for students who would like a more complete introduction to Computer Science. We will cover a variety of topics such as functional programming, data abstraction, object-oriented programming, and program complexity. This course will be taught primarily in Python. However, we are interested in teaching you foundational programming ideas, not just how to use one particular programming language. Once you have learned the essence of programming and the concepts that appear in various forms in programming languages, you will be able to pick up other languages and other programming concepts rapidly.

The material for this course has significant overlap with CS 61A. We do not cover the interpretation section of CS61A. If you are certain that you want to major or minor in Computer Science, CS 61A is the right introductory course. You can take CS 61A for credit after having taken CS 88. However, you cannot take CS 88 for credit after having taken CS 61A. Data 8 and CS 88 together satisfy the knowledge prerequisite for CS 61B.  It is recommended, but not required, that you are currently enrolled in or have taken Data 8. There is no formal programming-related prerequisite for CS 88. You do not need to be familiar with any particular programming language. The online textbook for the course is [Composing Programs](http://composingprograms.com/), which was created specifically for CS61A but is also the best basis for this course. Readings for each lecture appear in the course schedule. We will be jumping around a little due to the data-centric orientation of the course. You should complete the readings before attending lecture.

In addition, the course website and Piazza will contain additional links to guides, handouts, and practice materials available for the course.

CS 88: Computational Structures in Data Science

Computer Programming

Data Structures and Algorithms

Command Line

HTML

Specificity

Layout

Box Model

Flex

JavaScript

Document Object Model (DOM)

Events in JavaScript

JS files

classList

Anonymous functions

`this`

JSDoc

DOM Manipulation

JavaScript Timers

Asynchronous JS

Promises

Async / Await

Timers + Promises

File I/O in Node

APIs

JSON

Fetch

Regex

AJAX

POST

Form Submission and Validation

Server Side

Node.js

SQLite

SQL Joins

CSE 154 Web Programming University of Washington Summer 2022 This course introduces the fundamental concepts of web programming and technologies required for web development. It covers the full spectrum of web development, from HTML, CSS, JavaScript to server-side technologies like Node.js, databases, and SQL. CSE 154 is an introduction to programming for the World Wide Web and the technologies that support it. The course is one part practical: you will learn how to use the tools and technologies to build websites. It's also one part theoretical: you'll learn how and why many of these technologies work. And it's one part creative: you'll get an opportunity to design and explore creative ways of building a website.   

CSE 154 Web Programming

Database

Databases

3 courses cover this concept

CS 262a Advanced Topics in Computer Systems

CS 88: Computational Structures in Data Science

CSE 154 Web Programming