jumprope-rs
ATS-Postiats
jumprope-rs | ATS-Postiats | |
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8 | 18 | |
129 | 349 | |
- | - | |
4.0 | 0.0 | |
12 months ago | about 1 year ago | |
Rust | ATS | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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jumprope-rs
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Text Showdown: Gap Buffers vs. Ropes
Thanks for all the work in bootstrapping this part of the ecosystem! I opened an issue[1] on the memory issue for jumprope. It seems to really come down to the large size of skiplist nodes relative to the text.
I did some testing with JumpRopeBuf, but ultimately did not include it because I was comparing things from an "interactive editor" perspective where edits are applied immediately instead of a collaborative/CRDT use case where edits are async. But it did perform very well as you said! I feel like JumpRopeBuf feels similar to a piece table, where edits are stored separately and then joined reading.
[1] https://github.com/josephg/jumprope-rs/issues/5
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How to Survive Your Project's First 100k Lines
Every piece of a large program should be tested like this. And if you can, test your whole program like this too. (Doable for most libraries, databases, compilers, etc. This is much harder for graphics engines or UI code.)
I've been doing this for years and I can't remember a single time I set something like this up and didn't find bugs. I'm constantly humbled by how effective fuzzy bois are.
This sounds complex, but code like this will usually be much smaller and easier to maintain than a thorough unit testing suite.
Here's an example from a rope (complex string) library I maintain. The library lets you insert or delete characters in a string at arbitrary locations. The randomizer loop is here[1]. I make Rope and a String, then in a loop make random changes and then call check() to make sure the contents match. And I check and all the expected internal invariants in the rope data structure hold:
[1] https://github.com/josephg/jumprope-rs/blob/ae2a3f3c2bc7fc1f...
When I first ran this test, it found a handful of bugs in my code. I also ran this same code on a few rust rope libraries in cargo, and about half of them fail this test.
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Announcing crop, the fastest UTF-8 text rope for Rust
Jumprope author here. Thanks for the quick test! I just updated the benchmarks in jumprope/rope_benches to include Crop, and it looks to me like jumprope is about 2x faster than crop:
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Google's OSS-Fuzz expands fuzz-reward program to $30000
I’d go further and say that writing most software without fuzz testing is insane. Fuzz testing is one of those things they should teach in school. They’re a super useful technique - up there with TDD and it’s a tragedy they aren’t more wildly used.
Fuzzers are so good because they find so many bugs relative to programmer effort (lines of code). They’re some of the most efficient testing you can do. If I had to choose between a full test suite and a fuzzer, I’d choose the fuzzer.
I use fuzzers whenever I have a self contained “machine” in my code which should have well defined behaviour. For example, a b-tree. I write little custom fuzzers each time. The fuzzing code randomly mutates the data structure and keeps a list of the expected btree content. Then periodically I verify that the list and the btree agree on what should be contained inside the list. In the project I’m working on at the moment, I have about 6 different fuzzers sprinkled throughout my testing code. (Btree fuzzer, rope fuzzer, file serialisation fuzzer, a few crdt fuzzers, and so on).
Writing fuzzers is quite devastating for the ego. Usually the first time I point a fuzzer at my code, even when my code has a lot of tests, the fuzzer throws an assertion failure instantly. “Iteration 2 … the state doesn’t match what was expected”.
Getting a fuzzer running all night without finding any bugs is a balm for the soul.
The code looks like this, if anyone is curious. Here’s a fuzzer for a rope (fancy string) implementation: https://github.com/josephg/jumprope-rs/blob/master/tests/tes...
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The case against an alternative to C
Yep. A few years ago I implemented a skip list based rope library in C[1], and after learning rust I eventually ported it over[2].
The rust implementation was much less code than the C version. It generated a bigger assembly but it ran 20% faster or so. (I don't know why it ran faster than the C version - this was before the noalias analysis was turned on in the compiler).
Its now about 3x faster than C, thanks to some use of clever layered data structures. I could implement those optimizations in C, but I find rust easier to work with.
C has advantages, but performance is a bad reason to choose C over rust. In my experience, the runtime bounds checks it adds are remarkably cheap from a performance perspective. And its more than offset by the extra optimizations the rust compiler can do thanks to the extra knowledge the compiler has about your program. If my experience is anything to go by, naively porting C programs to rust would result in faster code a lot of the time.
And I find it easier to optimize rust code compared to C code, thanks to generics and the (excellent) crates ecosystem. If I was optimizing for runtime speed, I'd pick rust over C every time.
[1] https://github.com/josephg/librope
[2] https://github.com/josephg/jumprope-rs
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Linked lists and Rust
Linked lists are also the basis for skip lists - which are awesome. One of the only data structures I know of which needs a random number generator to work correctly. I have a rope implementation that I tidied up over the last few days which uses a skip list. Its several times faster than the next fastest library I know of (ropey). They're both O(log n), but for some reason jumprope (with skip lists) still ended up several times faster than ropey's b-trees.
ATS-Postiats
- What is the most feature-rich programming language
- Evolutie limbaje in industrie
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The Little Typer – The Beauty of Dependent Type Systems, One Step at a Time
This is one of my two favorite books in The Little ...er series. The other is The Rational Schemer. These are two of the most advanced books in the series.
The Little Typer provides an introduction to dependent types. These can by used to guarantee things like "applying 'concat' to a list of length X and list of length Y returns a list of X+Y". It is also possible, to some extent, to use dependent types to replace proof tools like Coq. Two interesting languages using dependent types are:
- Idris. This is basically "strict Haskell plus dependent types": https://www.idris-lang.org/)
- ATS. This is a complex systems-level language with dependent types: http://www.ats-lang.org/
The Rational Schemer shows how to build a Prolog-like logic language as a Scheme library. This is a very good introduction to logic programming and the implementation of backtracking and unification is fascinating.
This is an excellent series overall, but these two books are especially good for people who are interested in unusual programming language designs. I don't expect dependent types or logic programming to become widely-used in the next couple generations of mainstream languages, but they're still fascinating.
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Does Rust have any design mistakes?
Not being ATS
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The case against an alternative to C
> any safety checks put into the competing language will have a runtime cost, which often is unacceptable
This is completely wrong. The best counterexample is probably ATS http://www.ats-lang.org which is compatible with C, yet also features dependent types (allowing us to prove arbitrary statements about our programs, and check them at compile time) and linear type (allowing us to precisely track resource usage; similar to Rust)
A good example is http://ats-lang.sourceforge.net/DOCUMENT/ATS2CAIRO/HTML/c36.... which uses the Cairo graphics library, and ends with the following:
> It may seem that using cairo functions in ATS is nearly identical to using them in C (modulo syntatical difference). However, what happens at the level of typechecking in ATS is far more sophisticated than in C. In particular, linear types are assigned to cairo objects (such as contexts, surfaces, patterns, font faces, etc.) in ATS to allow them to be tracked statically, that is, at compile-time, preventing potential mismanagement of such objects. For instance, if the following line:
val () = cairo_surface_destroy (sf) // a type error if omitted
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Security advisory: malicious crate rustdecimal | Rust Blog
For a low level language in which you actually need to prove that your code doesn't cause UB, see http://www.ats-lang.org/
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Why is ATS not considered in the design of modern system languages?
Here's the homepage fo the language: http://www.ats-lang.org/. The trick to finding results about with google is to search "ATS programming language".
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ESPOL, NEWP, Mesa, Cedar, Modula-2, Modula-2+, Modula-3, Oberon, Oberon-2, Component Pascal, Active Oberon, D, C#, F#, VB, Ada, Go, Swift, just a few examples.
In SPARK's case, you have to state your invariants in even greater precision than in Rust, and naturally it has worse inference. That's okay, the same happens in a certain language with Atrocious Type Syntax.
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What are all the situations you can't do compile time type-checking when building a programming language?
Yes, things like mentioned in the post can be expressed and checked statically, as demonstrated by languages like Idris and ATS. ATS might be even more relevant as it's an imperative language too, it can get rather low-level (like talking about properties of C runtime functions) while proving required properties statically, and it includes a solver for certain amount of arithmetics so that you don't need to prove obvious mathematical identities to the compiler. http://www.ats-lang.org/
- Is it possible to make a functional programming language that is equivalent of Rust in terms of performance and resource efficiency?
What are some alternatives?
crop - 🌾 A pretty fast text rope
lean4 - Lean 4 programming language and theorem prover
librope - UTF-8 rope library for C
chapel - a Productive Parallel Programming Language
Odin - Odin Programming Language
cicada - An old-school bash-like Unix shell written in Rust
EmeraldC - The Ultimate C Preprocessor
c3c - Compiler for the C3 language
WebKit - Home of the WebKit project, the browser engine used by Safari, Mail, App Store and many other applications on macOS, iOS and Linux.
virgil - A fast and lightweight native programming language
buffet - All-inclusive Buffer for C
HVM - A massively parallel, optimal functional runtime in Rust