MLton has the following features.
Portability
Robustness
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Supports the full SML 97 language as given in The Definition of Standard ML (Revised).
If there is a program that is valid according to the Definition that is rejected by MLton, or a program that is invalid according to the Definition that is accepted by MLton, it is a bug. For a list of known bugs, see UnresolvedBugs.
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A complete implementation of the Basis Library.
MLton’s implementation matches latest Basis Library specification, and includes a complete implementation of all the required modules, as well as many of the optional modules.
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Generates standalone executables.
No additional code or libraries are necessary in order to run an executable, except for the standard shared libraries. MLton can also generate statically linked executables.
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Compiles large programs.
MLton is sufficiently efficient and robust that it can compile large programs, including itself (over 140K lines). The distributed version of MLton was compiled by MLton.
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Support for large amounts of memory (up to 4G on 32-bit systems; more on 64-bit systems).
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Support for large array lengths (up to 231-1 on 32-bit systems; up to 263-1 on 64-bit systems).
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Support for large files, using 64-bit file positions.
Performance
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Executables have excellent running times.
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Generates small executables.
MLton takes advantage of whole-program compilation to perform very aggressive dead-code elimination, which often leads to smaller executables than with other SML compilers.
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Untagged and unboxed native integers, reals, and words.
In MLton, integers and words are 8 bits, 16 bits, 32 bits, and 64 bits and arithmetic does not have any overhead due to tagging or boxing. Also, reals (32-bit and 64-bit) are stored unboxed, avoiding any overhead due to boxing.
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Unboxed native arrays.
In MLton, an array (or vector) of integers, reals, or words uses the natural C-like representation. This is fast and supports easy exchange of data with C. Monomorphic arrays (and vectors) use the same C-like representations as their polymorphic counterparts.
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Multiple garbage collection strategies.
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Fast arbitrary precision arithmetic (IntInf) based on the GnuMP.
For IntInf intensive programs, MLton can be an order of magnitude or more faster than Poly/ML or SML/NJ.
Tools
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Source-level Profiling of both time and allocation.
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MLLex lexer generator
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MLYacc parser generator
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MLNLFFIGen foreign-function-interface generator
Extensions
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A simple and fast C ForeignFunctionInterface that supports calling from SML to C and from C to SML.
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The ML Basis system for programming in the very large, separate delivery of library sources, and more.
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A number of extension libraries that provide useful functionality that cannot be implemented with the Basis Library. See below for an overview and MLtonStructure for details.
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MLton supports continuations via callcc and throw.
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MLton supports finalizable values of arbitrary type.
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MLton supports the functionality of the C setitimer function.
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MLton has functions similar to the C rand and srand functions, as well as support for access to /dev/random and /dev/urandom.
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MLton has functions similar to the C getrlimit and setrlimit functions.
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MLton supports a subset of the functionality of the C getrusage function.
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MLton supports signal handlers written in SML. Signal handlers run in a separate MLton thread, and have access to the thread that was interrupted by the signal. Signal handlers can be used in conjunction with threads to implement preemptive multitasking.
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MLton includes a primitive that returns the size (in bytes) of any object. This can be useful in understanding the space behavior of a program.
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MLton has a complete interface to the C syslog function.
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MLton has support for its own threads, upon which either preemptive or non-preemptive multitasking can be implemented. MLton also has support for Concurrent ML (CML).
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MLton supports weak pointers, which allow the garbage collector to reclaim objects that it would otherwise be forced to keep. Weak pointers are also used to provide finalization.
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MLton has a facility for saving the entire state of a computation to a file and restarting it later. This facility can be used for staging and for checkpointing computations. It can even be used from within signal handlers, allowing interrupt driven checkpointing.
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