API (Application Programming Interface)

System Calls

Multiprocessing

execvp

Interprocess Communication

Virtual memory

Thread (computing)

Mutexes (Mutual exclusion)

Semaphores

Thread Pools

Parallel Compilation

Clients

Networking

MapReduce

Filesystems

File Descriptors

waitpid

Pipeline (Unix)

Signals

Multithreading

Race condition

Condition variables

Multithreading Patterns

Read-Write Locks

Networks

Servers

HTTP

Networking Functions

CS 110: Principles of Computer Systems Stanford University Winter 2022 CS 110 delves into advanced computer systems and program construction, focusing on designing large systems, software that spans multiple machines, and parallel computing. This course builds upon CS107 and requires good knowledge of C, C++, Unix, GDB, Valgrind, and Make. It covers Linux filesystems, multiprocessing, threading, networking, and more. CS107 took you behind the scenes:

- how things work inside C++/Python/Java, and how your programs map onto the components of computer systems
- understanding of program behavior and execution
 
CS110 uses this as a foundation to build complex programs that maximally take advantage of the hardware and operating system software available to us:

- How can we understand the designs and tradeoffs of large systems?
- How can we write software that spans multiple machines?
- How can we write software that runs tasks in parallel on a single machine? ### Course Topics Overview

1. **Overview of Linux Filesystems** - How can we design filesystems to store and manipulate files on disk?
1. **Multiprocessing and Exceptional Control Flow** - How can our program create and interact with other programs?
1. **Threading and Concurrency** - How can a single instance of our program perform multiple coordinated tasks at the same time?
1. **Networking and Distributed Computing** - How can we write programs that communicate over a network with other programs, and tackle large tasks using many machines?
1. **Additional Topics**: MapReduce, Caching, and Non-Blocking I/O **CS107 or equivalent -**

- Each of you should know C and C++ reasonably well so that you can...
    - write moderately complex programs (e.g. pointers, **malloc/realloc/free**, C strings, C++ classes, methods, references, templates, **new/delete**)
    - read and understand portions of large code bases
    - trace memory diagrams and always win!
- Each of you should be ﬂuent with **Unix, GDB, Valgrind**, and **Make** to the extent they're covered in CS107 or its equivalent.

The first assignment is meant to give you a sense of the scope of CS110 programs and refresh your memory on relevant prerequisites.  If you feel ok about it, you're all set! Second half of CS107 Textbook: *Computer Systems: A Programmer's Perspective by Bryant & O'Hallaron, 3rd Edition*

- Can purchase full copy, or Stanford Bookstore custom edition with just CS110 chapters
 
*Principles of Computer System Design: An Introduction* by Jerome H. Saltzer and M. Frans Kaashoek

- Free Stanford online access [here](https://www.sciencedirect.com/book/9780123749574/principles-of-computer-system-design)​ (also linked on course homepage)
- Fewer readings from this book vs. first one
- You're welcome to buy a physical copy if you'd like

CS 110: Principles of Computer Systems

Computer Systems

Tkinter

Python

Arithmetic Expressions

Variable (computer science)

Function (computer programming)

String (computer science)

Boolean

List (abstract data type)

Tuple

Array slicing

Control flow

Debugging

For loop

Dictionary (data structure)

Set (abstract data type)

Modular programming

Exception handling

File system

Recursion (computer science)

Object-Oriented Programming (OOP)

Class (computer programming)

Inheritance (object-oriented programming)

While loop

Assertion (software development)

Web API

Lambda

Filter (higher-order function)

Event loop

Graphical User Interface (GUI)

CICS 110: Foundations of Programming  The University of Massachusetts Amherst Spring 2023 This course introduces computer programming and problem-solving. Students learn using a modern language, covering variables, data types, branching, functions, classes, and methods. Emphasis is on real-world problem translation, computational understanding, and debugging. An introduction to computer programming and problem solving using computers. This course teaches you how real-world problems can be solved computationally using programming constructs and data abstractions of a modern programming language. Concepts and techniques covered include variables, expressions, data types, objects, branching, iteration, functions, classes, and methods. We will also cover how to translate problems into a sequence of instructions, investigate the fundamental operation of a computational system and trace program execution and memory, and learn how to test and debug programs. No previous programming experience required. The objective of this course is to introduce the fundamentals of computing and programming using a general-purpose programming language from a modern perspective. This includes understanding the operation of a machine from a programming language perspective and what it means to execute a whole program as well as its individual parts, how to solve problems using constructs that a programming language provides such as variables, data types, objects, branching, iteration, functions, and classes, and how to write programs that receive data from various sources, process that data, and produce output in various forms.

## Learning Outcomes

At the completion of this course you will be able to:

- Read and write programs to solve non-trivial programs using the Python programming language.
- Describe fundamental units of computation and program structure.
- Translate real-world problems into computational solutions.
- Solve problems using a general-purpose programming language and the tools it provides such as variables, data types, objects, branching, iteration, functions/methods, and classes.
- Design and implement whole programs and functions to solve computational problems using top-down and bottom-up techniques.
- Describe application programming interfaces (API) and use APIs available from existing objects and libraries to solve problems.
- Translate data from and into various formats that are in computer memory, a graphical interface, a file, from a remote API on the web, or other data resources.
- Use console-based or graphical interfaces to learn about input/output to move data into and out of a program.
- Use modules and classes to organize data and functions.
- Explain the notion of a machine and how it relates to the execution of a general-purpose programming language.
- Explain how programs and their data are represented in a computer and build mental models and use diagrams of program and function execution and data stored in memory.
- Use basic debugging techniques such as “print debugging” and assert statements to determine the cause of logical programming errors and show the correctness of a program and its implementation.
- Describe programs using proper documentation techniques to communicate implementation details at various levels of granularity. R1 (or a score of 20 or higher on the math placement test Part A), or one of the following courses: MATH 101&102 or MATH 104 or MATH 127 or MATH 128 or MATH 131 or MATH 132. ## Textbook

The following textbook is required:

- Programming in Python 3, an interactive textbook from [zyBooks](https://learn.zybooks.com/) designed specifically for this course.

The information you need to subscribe to this book can be found on the course LMS (e.g., Moodle).

Here are some additional textbook recommendations freely available online. You may consider looking at these as supplemental material:

- Automate the Boring Stuff with Python, Al Sweigert, https://automatetheboringstuff.com
- A Byte of Python, https://www.gitbook.com/book/swaroopch/byte-of-python/details
- Dive into Python, Mark Pilgrim, http://getpython3.com/diveintopython3
- Learn python the hard way, Zed Shaw, http://learnpythonthehardway.org/book
- Python Practice Book, Anad Chitpothu, http://anandology.com/python-practice-book

CICS 110: Foundations of Programming 

Computer Programming

API (Application Programming Interface)

2 courses cover this concept

CS 110: Principles of Computer Systems

CICS 110: Foundations of Programming