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Schism: A Self-Hosting Scheme to WebAssembly Compiler

The backend passes through several intermediate languages as this diagram illustrates and performs some optimisations. Compiler frontend 1. There are two frontends to the compiler. The first one is a proof-producing synthesis tool called the translator. Compiler frontend 2. The second compiler frontend consists of a traditional parser followed by a type inferencer. Both of these have been proved sound and complete with respect to declarative specifications. For the parser, this means that our PEG parser implementation finds a correct parse tree if there exists one according to a traditional grammar for CakeML concrete syntax SML.

Soundness and completeness of the type inferencer means that, if the program can be typed, then the inferencer will find a type which is the most general type. Compiler bootstrapping. By bootstrapped we mean that the compiler has compiled itself. This was achieved by noticing that frontend 2 combined with the backend is a HOL function which we can feed into the tool-chain consisting of frontend 1 and the backend.

The result is a verified binary that provably implements the compiler itself with frontend 2. The latest bootstrapped binary is on our downloads page. The bootstrapping is described here and here. Post-hoc verification of CakeML programs.


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Usually, we recommend that verified CakeML code is produced via synthesis using frontend 1. However, in some cases it is more convenient to do Hoare-style reasoning in the separation logic of CFML. Verified applications built using CakeML. The CakeML tools are geared towards production of verified applications using proof-producing synthesis frontend 1 and compilation inside HOL in-logic evaluation of the compiler backend.

To date, the largest case study is the bootstrapped CakeML compiler. Other end-to-end verified applications that have been produced using the CakeML tools are:. This website provides further details of the CakeML project, links to papers, courseware, auxiliary tools and suggestions for masters and doctoral level projects. The CakeML team at Chalmers has an open postdoc position.

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Application deadline: 28 Feb Application deadline: 21 May There is a two-year postdoc position open at Chalmers on topics related to CakeML. Application deadline: 18 May Data61 is hiring proof engineers again in Sydney, Australia. Application deadline: 15 April Data61 is hiring proof engineers and a research scientist in Sydney, Australia. Application deadline: November 21 The result of bootstrapping in the logic is available as it is for x also.

Habit: a new functional programming language

Ramana Kumar received the John C. These tutorials will let participants try out the tools of the CakeML ecosystem and use them to produce end-to-end verified binaries. The tutorials are a good way to get involved in CakeML. Application deadline: 25 April CPP'17 has accepted our paper preprint on the target-specific aspects of compiling and assembling CakeML to real machine code. The final publication is available here. A diagram of the new compiler can be seen on the right. Our ESOP'16 paper preprint describes and advocates the use of functional big-step semantics for both reasoning about programming languages and compiler verification.

Shared State

The final publication is available at link. Our ITP'15 paper on reflection precedes and supports the work on this project. See the slides for Week 10, , or Week 12, A beta version of the verified CakeML implementation version 1 is available here. The top block is written using React and just says "we want a counter on the page. The bottom block is using vanilla JS. It explicitly finds a DOM node and updates it.

While this is fine for such a simple example this won't scale well. What happens when we want multiple counters in multiple locations? React is ready for that, with vanilla JS we have a lot of work to do. Now it's worth noting that declarative code will always end up either compiling down to or being processed by something imperative. What do I mean by that? Well something has to do the DOM mutation. In this case that's React. Even with functional languages like Lisp or Haskell they eventually get compiled to imperative machine code.

Now these two functions achieve the exact same thing. They take a list of files and return a dictionary of files where the key is file. But the imperative one is sloppier. It's 8 lines of code instead of 3. It also leaves a lot of room for error. What happens if a file doesn't have an id?

Functional programming - Wikipedia

What happens if we get our exit clause wrong? And fun fact, there are faster ways to do for loops they're ugly , but we can trust lodash to do those under the hood. It's now time to move onto functional concepts. Let's take these in pairs, the first two separation and composition.

I pulled these quotes from an article called The Dao of Immutability. What we're saying here is we want small functions that easily chain together to make larger ones. Let's take a look at an example:. These three functions are all super simple. They take one argument and do a transformation on that argument.

Implementing functional languages: a tutorial

The first function sorts the list of files. The second function is a filter. So this code returning an array of files who's extensions are PDFs. The last function is just a map. In this case we're looping over the list of files and returning the key name from each of them.

Now both of these functions are equivalent. They take a list of files, filter for pdfs, get their names, and return a sorted list of file names. Do whatever you think is best. These pair really nicely. Immutability says we're never gonna mutate an argument only return a new one, and memoization allows us to remember outputs. Let's look at an example combining them. What's going on here?

Well we have a function called killSibling dark I know , that takes a wizard.

It copies over the wizard and decrements the number of siblings that wizard has. Please ignore any glaring bugs here, I wanted to keep this simple. We then pass killSibling to lodash. Now when we call killSiblingMemoized on ron , it returns a brand new object. If we do a strict equality check it returns false.