Boolean

Function (computer programming)

Lambda

Regular Expressions

Intermediate Representations

Register Allocation

Garbage Collection

Type Checking

Pattern Matching

Unary Operations

Binary Operations

Function Pointers

OCaml

S-Expression

Conditional (computer programming)

Handling Errors

First-Class Functions

Constant Folding

Compiler

Types

Correctness and Testing

Naming Expressions

Tail Call Optimization

Functional Programming (FP)

Custom Types

Pairs

Parsing

Optimization

CS 164: Programming Languages and Compilers UC Berkeley Fall 2022 Explores how compilers translate high-level languages into machine-understandable code, offering practical experience with developing compilers for various languages. Also covers reasoning about compiler correctness and understanding runtime errors.  Have you ever wondered why C programs seem to run faster than Python programs? Have you ever been confused by an error message and wondered why Java couldn’t understand your program? In CS 164, we’ll learn how compilers take in code in one language and produce code in another; in particular, we’ll learn how to translate high-level languages into code that your computer’s processor can understand. We’ll get hands-on practice developing compilers for a series of increasingly complex languages. Along the way, we’ll learn some general best practices for developing and testing complex software systems. After completing this course, students will be able to:

- Develop programs to translate between different programming languages
- More broadly, develop programs that operate on programs
- Explain the relationship between compilers and interpreters, and the differences between them
- Understand the tools they use to run programs—and the errors those tools produce
- Assign meaning to high-level language constructs
- Implement high-level language constructs
- Reason about what it means for a compiler to be correct
- Reason about undefined behavior
- Read and write assembly language
- Write a parser - [CS 61B. Data Structures](https://www2.eecs.berkeley.edu/Courses/CS61B/)
- [CS 61C. Machine Structures](https://www2.eecs.berkeley.edu/Courses/CS61C/)

### Course Culture

Students taking CS 164 come from a wide range of backgrounds. We hope to foster an inclusive and safe learning environment based on curiosity rather than competition. All members of the course community—the instructor, students, and GSIs—are expected to treat each other with courtesy and respect. Some of the responsibility for that lies with the staff, but a lot of it ultimately rests with you, the students. There is no textbook for the course; all readings will be provided digitally.

CS 164: Programming Languages and Compilers

Compilers

Programming Languages

Tkinter

Python

Arithmetic Expressions

Variable (computer science)

String (computer science)

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)

API (Application Programming Interface)

Web API

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

Java (programming language)

Functional Decomposition

Control Structures

Data Abstraction

Documentation and Readability

Static methods

`print` statements

Scanners

Array (data structure)

ArrayList

Java

Expressions

Scope

Parameters

`Math` class

Information flow

Pseudorandomness

Line-based file input

reference semantics

Constructors

Polymorphism (computer science)

Escape sequences

`for` loops

Class constants

Return values

Chaining

Sentinel loops

Token-based file input

Array Traversals

Fields

`println`

Variable (computer_science)

Nested `for` loops

Cumulative algorithm

Fencepost problems

File output

Array Shifting

Instance Methods

Critters

CSE 142 Computer Programming I University of Washington Summer 2022 This introductory course teaches programming using Java. Students learn computational problem-solving techniques, functional decomposition, control structures, data abstraction, and code documentation. No prior programming experience is required. This course provides an introduction to programming using the Java programming language. We will explore common computational problem-solving techniques useful to computer scientists, but also to anyone who has large data sets, repetitive processes or other needs for computation. No prior programming experience is assumed, although students should know the basics of using a computer (e.g., using a web browser and a text editor) and should be comfortable with math through Algebra 1. Students with significant prior programming experience should consider skipping CSE 142 and taking [CSE 143](https://cs.washington.edu/143). CSE 142 is organized around five key learning objectives. At the end of the course, students will be able to do the following:

1. Functionality/Behavior: Write functionally correct Java programs that meet a provided specification and/or solve a specified problem
1. Functional Decomposition: Break down problems into subproblems that are modular and reusable, and define methods to represent those subproblems
1. Control Structures: Select and apply control structures (e.g. methods, loops, conditionals) to manage the flow of control and information in programs
1. Data Abstraction: Select and apply basic data abstractions (e.g. variables, parameters, arrays, classes) to manage and manipulate data in programs
1. Documentation and Readability: Define programs that are well-written, readable, maintainable, and conform to established standards  Recommended textbook: [*Building Java Programs* by Reges and Stepp (5th edition)](https://courses.cs.washington.edu/courses/cse142/22su/textbook.html)

CSE 142 Computer Programming I

Boolean

3 courses cover this concept

CS 164: Programming Languages and Compilers

CICS 110: Foundations of Programming

CSE 142 Computer Programming I