| XZ Backdoor symbol deobfuscation. Updated as i make progress |
This is a living document. Everything in this document is made in good faith of being accurate, but like I just said; we don't yet know everything about what's going on.
On March 29th, 2024, a backdoor was discovered in xz-utils, a suite of software that
| /* | |
| the twitter api is stupid. it is stupid and bad and expensive. hence, this. | |
| Literally just paste this in the JS console on the bookmarks tab and the script will automatically scroll to the bottom of your bookmarks and keep a track of them as it goes. | |
| When finished, it downloads a JSON file containing the raw text content of every bookmark. | |
| for now it stores just the text inside the tweet itself, but if you're reading this why don't you go ahead and try to also store other information (author, tweetLink, pictures, everything). come on. do it. please? | |
| */ |
FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.
Copyright © 2016-2018 Fantasyland Institute of Learning. All rights reserved.
A function is a mapping from one set, called a domain, to another set, called the codomain. A function associates every element in the domain with exactly one element in the codomain. In Scala, both domain and codomain are types.
val square : Int => Int = x => x * x
| import java.util.Optional; | |
| import java.util.function.Function; | |
| class Main { | |
| public static void main(String[] args) { | |
| Optional<String> o = Optional.of("foo"); | |
| Function<String, String> f = s -> null; | |
| Function<String, String> g = String::valueOf; | |
| //lawless lolz |
| Write a program that does what it’s supposed to do | |
| Write idiomatic code | |
| Debug a program that you wrote | |
| Debug a program someone else wrote | |
| Debug the interaction between a system you wrote and one you didn’t | |
| File a good bug report | |
| Modify a program you didn’t write | |
| Test a program you wrote | |
| Test a program you didn’t write | |
| Learn a new programming language |
Every application ever written can be viewed as some sort of transformation on data. Data can come from different sources, such as a network or a file or user input or the Large Hadron Collider. It can come from many sources all at once to be merged and aggregated in interesting ways, and it can be produced into many different output sinks, such as a network or files or graphical user interfaces. You might produce your output all at once, as a big data dump at the end of the world (right before your program shuts down), or you might produce it more incrementally. Every application fits into this model.
The scalaz-stream project is an attempt to make it easy to construct, test and scale programs that fit within this model (which is to say, everything). It does this by providing an abstraction around a "stream" of data, which is really just this notion of some number of data being sequentially pulled out of some unspecified data source. On top of this abstraction, sca
| package dep | |
| import scala.language._ | |
| object Dep extends App { | |
| sealed trait Nat { | |
| type Plus[M <: Nat] <: Nat | |
| def plus[M <: Nat](m: M): Plus[M] | |
| } |
This is material to go along with a 2014 Boston Haskell talk.
We are going to look at a series of type signatures in Haskell and explore how parametricity (or lack thereof) lets us constrain what a function is allowed to do.
Let's start with a decidedly non-generic function signature. What are the possible implementations of this function which typecheck?
wrangle :: Int -> Int