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https://github.com/melsman/mlkit

Standard ML Compiler and Toolkit
https://github.com/melsman/mlkit

compiler functional-programming regions standard-ml

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Standard ML Compiler and Toolkit

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README 

        
## MLKit



The [MLKit](http://elsman.com/mlkit) is a compiler toolkit for the

Standard ML language, including **The MLKit with Regions**, which features a native

backend for the x64 architecture, based on region inference, and

**SMLtoJs**, which features a JavaScript backend targeting web browsers. The two

compilers share the same frontend and compilation management scheme.



The MLKit covers all of Standard ML, as defined in the 1997 edition of

[The Definition of Standard ML](https://mitpress.mit.edu/books/definition-standard-ml-revised-edition) and supports most of the [Standard ML

Basis Library](http://elsman.com/mlkit/basis.html).



## Test Statistics and Benchmarking



[![CI](https://github.com/melsman/mlkit/workflows/CI/badge.svg)](https://github.com/melsman/mlkit/actions) [Benchmarking](https://elsman.com/mlkit-bench/)



## Installation



Under macOS, MLKit is available through Homebrew: Just execute `brew

install mlkit`. Under Linux, you may download the latest binary

tgz-distribution of MLKit from

https://github.com/melsman/mlkit/releases/latest



Once downloaded and unpacked, execute `make install` from within the

top-directory of the unpacked distribution. You may install MLKit in a

directory different from `/usr/local/mlkit` by instead typing

`PREFIX=myinstallpath make install`.



## General Features



- **Compiles all of Standard ML**. The MLKit compiles all of Standard ML, [including Modules](http://elsman.com/mlkit/staticinterp.html), as specified by

  the Definition of Standard ML. The MLKit also supports most of the

  [Standard ML Basis Library](http://elsman.com/mlkit/basis.html).



- **Compiles large programs**. The MLKit compiles large programs,

  [including itself](http://elsman.com/mlkit/bootstrap.html), around

  80.000 lines of Standard ML plus the Standard ML Basis Library. The

  support for [ML Basis

  Files](http://elsman.com/mlkit/mlbasisfiles.html) makes it easy to

  compile a program with different Standard ML compilers. Currently,

  both [MLton](http://mlton.org) and the MLKit supports the concept of

  ML Basis Files. The MLKit works well together with

  [smlpkg](https://github.com/diku-dk/smlpkg), a generic package

  manager for Standard ML libraries and programs.



- **Documentation is available**. Man-pages and general documentation

  is available from the [MLKit home

  page](http://melsman.github.io/mlkit).



## MLKit with Regions - The x64 Native Backend



This version of the compiler is based on region inference and has the

following features:



- An x64 native backend (works with Linux and macOS).



- Memory allocation directives (both allocation and deallocation) are

  inferred by the compiler, which uses a number of program analyses

  concerning lifetimes and storage layout. The MLKit compiler is

  unique among ML implementations in this respect.



- A comprehensive guide on [Programming with Regions in the

  MLKit](https://github.com/melsman/mlkit/raw/master/doc/mlkit.pdf) is available,

  which also demonstrates how to create memory profiles of program

  executions using the supplied region profiler and how to interact

  with C programs.



- Region inference may be augmented with reference-tracing garbage

  collection to achieve better memory behavior.



## SMLtoJs - The JavaScript Backend



This version of the compiler generates efficient JavaScript, primarily

for [executing Standard ML code in the

browser](/README_SMLTOJS.md). There is also an [online version of

SMLtoJs](https://diku-dk.github.io/sml-ide/), which makes it possible

to write, compile, and execute Standard ML code in a web browser.



## The Barry Backend



The repository also includes the sources for

[Barry](/README_BARRY.md), a Standard ML source-to-source compiler

that eliminates modules, using static interpretation, and generates

optimised Core-language Standard ML code.



## License and Copyright



The MLKit compiler is distributed under the GNU Public License,

version 2. See the file [MLKit-LICENSE](/doc/license/MLKit-LICENSE)

for details. The runtime system (`/src/Runtime/`) and libraries

(`basis/`) is distributed under the more liberal MIT License.



## Compilation Requirements



To compile, install, and use the MLKit, a Linux box running Ubuntu

Linux, Debian, gentoo, or similar is needed. The MLKit also works on

macOS and has also earlier been reported to run on the FreeBSD/x64

platform, with a little tweaking.



To compile the MLKit, a Standard ML compiler is needed, which needs to

be one of the following:



__[MLton](http://mlton.org) >= 20051202:__

```bash

$ mlton

MLton 20051202 (built Sat Dec 03 04:20:11 2005 on pavilion)

```



If a version prior to 20201023 is used, you may need to adjust the

`mlton`-flags setup in the file `Makefiledefault`.



__A working MLKit compiler >= 4.3.0:__

```bash

$ mlkit -V

MLKit version 4.3.0, Jan 25, 2006 [X86 Backend]

```



Moreover, `gcc` is needed for compiling the runtime system and related

tools.



## Compilation



After having checked out the sources from Github, execute the command:

```bash

$ ./autobuild

```



Now, `cd` to the toplevel directory of the repository and execute the

appropriate set of commands:



__Compile with MLton alone (Tested with 3Gb RAM):__

```bash

$ ./configure

$ make mlkit

```



__Compile with existing MLKit (Tested with 1Gb RAM):__

```bash

$ ./configure --with-compiler=mlkit

$ make mlkit

```



If you later want to install the MLKit in your own home directory, you

should also pass the option `--prefix=$HOME/mlkit` to `./configure` above.



For binary packages, we use

```bash

$ ./configure --sysconfdir=/etc --prefix=/usr

```



## Pre-compile Basis Library and Kit-Library



Execute the following command:

```bash

$ make mlkit_libs

```



## Bootstrapping (optional - works with 1Gb RAM)



This step is optional. If you want the resulting executable compiler

to be bootstrapped (compiled with itself), execute the command:

```bash

$ make bootstrap && make mlkit_libs

```



Be aware that this step takes some time.



## Installation after Compilation



For a system-wide installation of the MLKit, including installation of

man-pages and tools, execute the command:

```bash

$ sudo make install

```



For a personal installation, with `--prefix=$HOME/mlkit` given to

`./configure`, execute the following command:

```bash

$ make install

```



## Making a Binary Package



To build a binary package, execute the command

```bash

$ make mlkit_x64_tgz

```



This command leaves a package `mlkit-X.Y.Z-x64.tgz` in the `dist/`

directory. For building a binary package, the installation step above

is not needed and the bootstrapping step is optional. The binary package includes both the MLKit with Regions compiler (i.e., the `mlkit` executable) and [SMLtoJs](/README_SMLTOJS.md) (i.e., an executables named `smltojs`).



## Try It



To test the installation, copy the directory `/usr/share/mlkit/kitdemo` to

somewhere in your own directory, say `$HOME/kitdemo`:

```bash

$ cp -a /usr/share/mlkit/kitdemo $HOME/kitdemo

$ cd $HOME/kitdemo

$ mlkit helloworld.sml

```



The MLKit should produce an executable file `run`:

```bash

$ ./run

hello world

```



## Trying Without Installing



You can run `mlkit` without installing it, but you should then point

the environment variable `SML_LIB` at the build directory (which

contains the `basis` and the `lib` directories) whenever you run

`mlkit`.  E.g:



```bash

$ SML_LIB=$PWD bin/mlkit

```



## More Information



See the [MLKit home page](http://melsman.github.io/mlkit) for information about related papers, etc.



General documentation for the MLKit is located in the directories `doc/mlkit`

and `man/man1`. License information is located in the file

`doc/license/MLKit-LICENSE`.



## Comments and Bug Reports



The MLKit has a number of [known bugs and limitations](http://elsman.com/mlkit/bugs.html). To file a bug-report, create an issue at the Github page.



## Appendix A: Directory Structure of the Sources



    kit/

       README

       configure

       Makefile.in

       src/

       basis/

       doc/mlkit.pdf

          /license/MLKit-LICENSE

       man/man1/rp2ps.1

       kitdemo/

       test/



## Appendix B: Quick Compilation and Installation Guide



We assume that MLton >= 20051202 is installed on the system as

described above.



After having checked out the sources from Github, execute the command:

```bash

$ ./autobuild

```



To compile the MLKit, execute the following commands:

```bash

$ ./configure

$ make mlkit

$ make bootstrap

$ make mlkit_libs

```



The `make bootstrap` command is optional.



To install the MLKit and related tools, execute:

```bash

$ sudo make install

```



See the section "Try It" above to test the installation.



## Appendix C: Displaying Region Flow Graphs with VCG



The [VCG tool](http://www.cs.uni-sb.de/RW/users/sander/html/gsvcg1.html) can be used to show region flow graphs.