inc VS Essentials-of-Compilatio

I also took a look at this repo namin/inc for some inspiration (this repo uses Scheme, not Common Lisp).

The tutorial, source, and tests can be found in the GitHub repo below as well:

https://github.com/namin/inc

(Not the author’s repo, just consolidates some of the material)

You can try this book if you want something that came out this year https://github.com/IUCompilerCourse/Essentials-of-Compilatio.... Go to the releases to either get the racket version or python version. But I mean cmu uses the dragon book second edition for a graduate level compiler optimization class.

This paper is my favorite introduction to compilers, it's short and hands-on: http://scheme2006.cs.uchicago.edu/11-ghuloum.pdf

There is a book-length expansion of this paper that goes into more detail: https://github.com/IUCompilerCourse/Essentials-of-Compilatio...

Introduction to Computing"

https://dcic-world.org/

# Programming Language Theory:

"Programming Languages: Application and Interpretation"

https://www.plai.org/

# Compilation:

"Essentials of Compilation: An Incremental Approach in Python"

https://github.com/IUCompilerCourse/Essentials-of-Compilatio...

# Database Systems:

"CMU: Intro to Database Systems"

https://15445.courses.cs.cmu.edu/

"CMU: Advanced Database Systems"

https://15721.courses.cs.cmu.edu/

# Calculus I/II & Real Analysis

"A Course in Calculus and Real Analysis"

https://link.springer.com/book/10.1007/978-3-030-01400-1

"A Course in Multivariable Calculus and Analysis"

https://link.springer.com/book/10.1007/978-1-4419-1621-1

# Linear Algebra & ML:

* A Series of books by prof. Joe Suzuki without using any external library for the implementations *

"Statistical Learning with Math and Python"

https://link.springer.com/book/10.1007/978-981-15-7877-9

"Sparse Estimation with Math and Python"

https://link.springer.com/book/10.1007/978-981-16-1438-5

"Kernel Methods for Machine Learning with Math and Python"

https://link.springer.com/book/10.1007/978-981-19-0401-1

# Discrete Mathematics:

"CMU 21-228 Discrete Mathematics (prof. Poh-Shen Loh"

https://www.math.cmu.edu/~ploh/2021-228.shtml

# Cryptography:

"Serious Cryptography: A Practical Introduction to Modern Encryption"

https://nostarch.com/seriouscrypto

# Problem Solving:

"Math 235: Mathematical Problem Solving"

https://www.cip.ifi.lmu.de/~grinberg/t/20f/

https://github.com/IUCompilerCourse/Essentials-of-Compilatio...

You can find a PDF and the associated course with a very minimal amount of following links.

If you are thinking of making your own language, it's also good to learn something about programming language theory, if you don't already. Many languages make mistakes that have been solved 25+ years ago. PLAI is good for that: https://www.plai.org/

I presume that's this, run in \racket mode? https://github.com/IUCompilerCourse/Essentials-of-Compilatio...

I ask because there seems to be a \python mode, too, that folks may find valuable: https://github.com/IUCompilerCourse/Essentials-of-Compilatio...

I also don't know why the ci.yml only ran for a few seconds: https://github.com/IUCompilerCourse/Essentials-of-Compilatio...

I took the IU compilers course as an undergrad and can easily say it was my favorite course. If anyone is interested, here is a link to the textbook which will cover this papers content in much finer detail:

https://github.com/IUCompilerCourse/Essentials-of-Compilatio...