Alloy is a language for describing structures and a tool for exploring them(github.com)
github.com
Alloy is a language for describing structures and a tool for exploring them
https://github.com/AlloyTools/org.alloytools.alloy
6 comments
Discussed on HN the other day: https://news.ycombinator.com/item?id=21200721.
Also a month ago: https://news.ycombinator.com/item?id=20909404
It's an excellent talk. I couldn't stop watching it.
Also a month ago: https://news.ycombinator.com/item?id=20909404
It's an excellent talk. I couldn't stop watching it.
Convincing mathematicians about it is a really old problem. Here's the first paper I saw really describing how mathematics has been done as a social process focused on people's understanding:
https://www.cs.cmu.edu/~pattis/misc/socialproofs.pdf
A 2009 rebuttal to be fair to my side of the debate:
https://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=40...
Here's a recent article about the situation from yet another segment of people trying to bring in automation:
https://www.quantamagazine.org/in-computers-we-trust-2013022...
Unlike article's impression, a lot of how to build trustworthy provers has already been solved. The state-of-the-art is probably Milawa: a prover for ACL2-like logic running on a Lisp verified down to the machine code. It has summaries of various approaches of making computational math/logic trustworthy:
https://www.kookamara.com/jared/2015-jar-milawa.pdf
Note: Like in Common Criteria EAL7 or DO-178C, I'd use a mix of techniques for verification instead of blindly trusting the math. Lots of human review, static analysis, testing, etc.
Far as projects implementing math's foundations, you should especially check out Mizar (most complete) and Metamath (open source):
https://en.wikipedia.org/wiki/Mizar_system
https://en.wikipedia.org/wiki/Metamath
If authors give permission, it might be worthwhile to attempt to create re-writing tools that convert those tools languages into platforms in use by programmers. That's mainly Coq, the HOL's, Why3, and (hardware) ACL2. I don't know how feasible that is. I just think it could be valuable.
https://www.cs.cmu.edu/~pattis/misc/socialproofs.pdf
A 2009 rebuttal to be fair to my side of the debate:
https://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=40...
Here's a recent article about the situation from yet another segment of people trying to bring in automation:
https://www.quantamagazine.org/in-computers-we-trust-2013022...
Unlike article's impression, a lot of how to build trustworthy provers has already been solved. The state-of-the-art is probably Milawa: a prover for ACL2-like logic running on a Lisp verified down to the machine code. It has summaries of various approaches of making computational math/logic trustworthy:
https://www.kookamara.com/jared/2015-jar-milawa.pdf
Note: Like in Common Criteria EAL7 or DO-178C, I'd use a mix of techniques for verification instead of blindly trusting the math. Lots of human review, static analysis, testing, etc.
Far as projects implementing math's foundations, you should especially check out Mizar (most complete) and Metamath (open source):
https://en.wikipedia.org/wiki/Mizar_system
https://en.wikipedia.org/wiki/Metamath
If authors give permission, it might be worthwhile to attempt to create re-writing tools that convert those tools languages into platforms in use by programmers. That's mainly Coq, the HOL's, Why3, and (hardware) ACL2. I don't know how feasible that is. I just think it could be valuable.
Isn't it the same thing that guys at INRIA with COQ are trying to do since ages ?
There was a fantastic talk at strangeloop this year on Alloy: https://www.youtube.com/watch?v=FvNRlE4E9QQ. The speaker used it to find a serious security bug in their live code and a feature interaction bug in their UI that had meant they had been writing broken code for the past _year_.
(full disclosure I'm referenced towards the end)
(full disclosure I'm referenced towards the end)
I watched that earlier this week, and have been making my way through the Software Abstractions book by Jackson. Alloy's still in the "this thing makes me feel stupid" territory, but it does feel learn-able to me. I really like the emphasis on iterative development.
I found Jackson’s book excellent, one of the most readable books with the depth the book had.
Forgive my ignorance, but after looking at the Github readme I'm not really understanding what this does. What kinds of things would Alloy be used for?
Here’s a good intro from strangeloop: https://www.youtube.com/watch?v=FvNRlE4E9QQ
Thanks, this is really helpful.
In what way is this alloy different than the official/original alloy? This the official alloy now?
There is literally no mention or prior credit on your site to the original? A lot of unanswered things here.
http://alloy.lcs.mit.edu/
http://alloy.lcs.mit.edu/
I've been wondering about this for a while. This one shows up ranked fairly highly on Google searches for alloy. I was very confused but I suspect it's an identically or confusingly named fork. But when I first discovered it, I spent a while assuming that development had just migrated to GitHub.
Has the original alloy gone unmaintained?
Has the original alloy gone unmaintained?
In any case if it has, in my personal opinion it's quite shady to fork a project and remove all reference to the pre-fork, except the cover of the book, which is just a picture and not even a link to the original MIT site.
Check the "Downloads" page at the MIT site. The "Experimental versions -- latest build" link points back to the Github site in question. (I agree that the Github site should explain the relationship.)
how does this relate to tools like TLA+? coq?
Re TLA+, I'll copying my response from the last time Alloy was linked here:
---
Alloy comes from the Z line of “systems are basically giant relational algebra problems”, while TLA+ comes from the LTL line of “systems are basically giant temporal logic problems”, which leads to a lot of fundamental differences between them. They also had different design philosophies: Jackson wanted a language that was easy to build tooling for, Lamport wanted a language that was easy to express complex logic in.
One consequence of this is that Alloy is a much smaller language: you can fit the entire syntax on a single sheet. It's also much easier in TLA+ to write a spec that you can't model-check, while with Alloy you have to be actively trying. It’s also impossible to write an unbound model in Alloy, so you’re guaranteed that every spec is over a finite state space. Which gets rid of the common TLA+ runtime problem of “is this taking a long time because it’s a big state space or because it’s an infinite state space".
Re tooling: Alloy converts to SAT, which makes model checking much, much faster. Specs that would take minutes to check in TLA+ take less than a second in Alloy. Being able to model-find as well as model-check is really nice, as is the ability to generate multiple counter/examples. The visualizer is really useful, too, especially for showing counterexamples to nontech folk. But the thing I honestly miss most when working in TLA+ is the REPL. It’s not the best REPL, but it’s a hell of a lot better than no REPL.
Okay, so drawbacks: Alloy doesn’t have an inbuilt notion of time. You have to add it in as a sequence sig. This means you can’t study liveness properties or deadlocks or anything like that. It also makes simulating concurrency awkward. This isn’t a huge problem if you have simple interactions or only one structure that’s changing, but the more “timelike” the problem gets, the worse Alloy becomes at handling it.
Less fundamental but still a big problem I keep having: no good iteration or recursion. Transitive closure is pretty nice but it’s not powerful enough. For example:
The biggest problem with Alloy adoption, though, is social: there’s no comprehensive online documentation. If you want to learn it you have to buy _Software Abstractions_. Fantastic book but not something that’s especially convenient, and it doesn't cover newer features. We're working on changing this, but it will be a while before we have comprehensive online documentation available.
Which one is more appropriate to use really depends on your problem. As a very, very, VERY rough rule of thumb: TLA+ is best you're most interested in the dynamics of a system: the algorithms, the concurrency, etc. Alloy is best when you're most interested in the statics of a system: the requirements, the data relationships, the ontology, etc. My standard demos for showcasing TLA+ are concurrent transfers and trading platforms, while my standard demos for Alloy are access policies and itemized billing. You can use each in the other's niche, too (see Zave's work on Chord), so it's not a stark division.
---
(Since writing that post, we're a few steps closer to having online documentation, and in the next couple of weeks or so I'll be running some first drafts past the rest of the team.)
Coq, by contrast, is a full theorem prover. I'm not experienced with it, but from my understanding it's mostly used in programming to prove things at a low level, where you're directly synthesizing code. Alloy is much higher level, relying on you to do the translations to code yourself. The upside is you don't need to know how to write mathematical proofs to use it, you just hit the "check model" button and it takes care of all of that for you.
If you want to see an example of Alloy in practice, I recently wrote a tutorial on using it to formally verify that your database migrations are safe: https://www.hillelwayne.com/post/formally-modeling-migration...
---
Alloy comes from the Z line of “systems are basically giant relational algebra problems”, while TLA+ comes from the LTL line of “systems are basically giant temporal logic problems”, which leads to a lot of fundamental differences between them. They also had different design philosophies: Jackson wanted a language that was easy to build tooling for, Lamport wanted a language that was easy to express complex logic in.
One consequence of this is that Alloy is a much smaller language: you can fit the entire syntax on a single sheet. It's also much easier in TLA+ to write a spec that you can't model-check, while with Alloy you have to be actively trying. It’s also impossible to write an unbound model in Alloy, so you’re guaranteed that every spec is over a finite state space. Which gets rid of the common TLA+ runtime problem of “is this taking a long time because it’s a big state space or because it’s an infinite state space".
Re tooling: Alloy converts to SAT, which makes model checking much, much faster. Specs that would take minutes to check in TLA+ take less than a second in Alloy. Being able to model-find as well as model-check is really nice, as is the ability to generate multiple counter/examples. The visualizer is really useful, too, especially for showing counterexamples to nontech folk. But the thing I honestly miss most when working in TLA+ is the REPL. It’s not the best REPL, but it’s a hell of a lot better than no REPL.
Okay, so drawbacks: Alloy doesn’t have an inbuilt notion of time. You have to add it in as a sequence sig. This means you can’t study liveness properties or deadlocks or anything like that. It also makes simulating concurrency awkward. This isn’t a huge problem if you have simple interactions or only one structure that’s changing, but the more “timelike” the problem gets, the worse Alloy becomes at handling it.
Less fundamental but still a big problem I keep having: no good iteration or recursion. Transitive closure is pretty nice but it’s not powerful enough. For example:
sig node {edge: set Node}
The biggest problem with Alloy adoption, though, is social: there’s no comprehensive online documentation. If you want to learn it you have to buy _Software Abstractions_. Fantastic book but not something that’s especially convenient, and it doesn't cover newer features. We're working on changing this, but it will be a while before we have comprehensive online documentation available.
Which one is more appropriate to use really depends on your problem. As a very, very, VERY rough rule of thumb: TLA+ is best you're most interested in the dynamics of a system: the algorithms, the concurrency, etc. Alloy is best when you're most interested in the statics of a system: the requirements, the data relationships, the ontology, etc. My standard demos for showcasing TLA+ are concurrent transfers and trading platforms, while my standard demos for Alloy are access policies and itemized billing. You can use each in the other's niche, too (see Zave's work on Chord), so it's not a stark division.
---
(Since writing that post, we're a few steps closer to having online documentation, and in the next couple of weeks or so I'll be running some first drafts past the rest of the team.)
Coq, by contrast, is a full theorem prover. I'm not experienced with it, but from my understanding it's mostly used in programming to prove things at a low level, where you're directly synthesizing code. Alloy is much higher level, relying on you to do the translations to code yourself. The upside is you don't need to know how to write mathematical proofs to use it, you just hit the "check model" button and it takes care of all of that for you.
If you want to see an example of Alloy in practice, I recently wrote a tutorial on using it to formally verify that your database migrations are safe: https://www.hillelwayne.com/post/formally-modeling-migration...
My undergraduate degree in CS covered Alloy, it was good fun to learn and solve problems with but I have to agree that the biggest pain point was definitely the limited documentation (even with access to the university's own resources). It's great to see improvements are on the horizon in this area!
Edit: one of the other things I disliked about it was the GUI (it's Swing, IIRC). http://alloytools.org/workshop/slides/cunha-alloy.pdf looks pretty cool and should probably be the future interface for the tool.
Edit: one of the other things I disliked about it was the GUI (it's Swing, IIRC). http://alloytools.org/workshop/slides/cunha-alloy.pdf looks pretty cool and should probably be the future interface for the tool.
If you happen to remember some of the pain points, please let me know! I keep a list of the common pitfalls that I need to address in the docs.
Re: coq, Alloy and TLA+ (to an extent) are built around model checking and SAT solvers, which are better at finding problems in specifications.
Coq is a proof assistant (and dependently typed programming language); more aimed at theorems.
Coq is a proof assistant (and dependently typed programming language); more aimed at theorems.
I think Alloy was mentioned at the end, but not really compared to LEAN.
[1]: https://youtu.be/Dp-mQ3HxgDE
[2]: https://leanprover.github.io/