Skip to content


Repository files navigation


Slicer is an interpreter for a simple ML-like language called iTML (imperative Transparent ML). This is companion code for paper "Imperative Functional Programs that Explain their Work" by Wilmer Ricciotti, Jan Stolarek, Roly Perera and James Cheney, published at International Conference on Functional Programming 2017. Upstream source code repository is located at


This software is written in Haskell. To build and install it you will need GHC 8.10 or above (some lower versions might work but were not tested) and a typical Haskell infrastructure (Cabal, access to Hackage).


git clone
cd slicer
cabal build

ICFP 2017 version

To run the exact version published at ICFP 2017 checkout the relevant tag and follow a README there:

git checkout icfp2017-final

Note: you will need GHC 8.0 and legacy Cabal.


After following the above steps the slicer executable will be located at dist-newstyle/build/$ARCH/$GHC-VER/slicer- where $ARCH is your system architecture (e.g. x86_64-linux) and $GHC-VER is your GHC version (e.g. ghc-9.0.1). For ease of use it's best to create a symlink to the executable, e.g.:

ln -s dist-newstyle/build/x86_64-linux/ghc-9.0.1/slicer- slicer

Example TML programs are located in examples sub-directory. You can run them by passing file name on the command line:

$ ./slicer examples/icfp17-example.tml

If all went well you should see the output:

Running examples/icfp17-example.tml
val it = let f = (fun f x =>
         if x == 0
         then y := 6 * !z
         else _) in
  f 0
with _ =>
;; !y : trace(int)

You can pass more than one file name at the same time.


Slicer provides a very simple REPL. Invoke it by passing --repl flag:

$ ./slicer --repl
Welcome to Slicer REPL

You can interact with REPL by providing single-line declarations and expressions:

slicer> data intlist = Nil | Cons int * intlist
slicer> let tail = fun tail (xs : intlist) : intlist => case xs of Nil -> Nil; Cons xs' -> snd xs'
val it = (fun tail xs =>
 case xs of
   Nil -> Nil;
   Cons xs' -> snd xs') : (intlist -> intlist)
slicer> let t = trace (tail (Cons (1, Cons (2, Cons (3, Nil)))))
val it = trace (tail Cons (1, Cons (2, Cons (3, Nil)))) : trace(intlist)
slicer> bwdSlice (t, Cons (2, _:intlist))
val it = tail Cons (_, Cons (2, _)) : trace(intlist)

Running the test suite

All example programs are packaged into a single test suite. Build and run the testsuite with:

cabal build
cabal test

The test suite will run every program in examples directory and compare its output with the expected output stored in a corresponding *.golden file inside tests/golden-templates/.

Note: tests hardcode the executable path, which includes a particular version of GHC. See SlicerTestSuiteUtils.slicerPath - you might have to adjust it on your machine.

Running the benchmarks

You can run benchmarks with:

cabal build
cabal bench

Reproducing examples from the paper

In the paper we have discussed several examples. These are all located as source files inside examples/ directory.

  1. On the first page of the paper we present a following example:

    let f(x) = if (x == 0) then y := 6 * !z else (y := 84 / !z; w := g(!y + 12)) in
    try f 0 with x => y := 42);; !y

    This example can be found in file icfp17-example.tml. Run it with:

    $ ./slicer examples/icfp17-example.tml

    You can tweak initial value of z and the value of argument passed to f to obtain different results. Remember that you must change the slicing criterion to match the obtained result. So for example if you change initial value of z to be 0 rather than 7 you need to change the slicing criterion from 42 to 0. If you remove the try-with exception handler and modify the code to cause division by zero the slicing criterion should be raise "Division by zero".

  2. On the third page of the paper we present a more elaborate example containing a usage of map. This example can be found in icfp17-example2.tml source file. Run it with:

    $ ./slicer examples/icfp17-example2.tml
  3. In section 6 we discuss an iTML program that solves a system of linear equations by using simple Gaussian elimination without pivoting. This program can be found in gauss.tml source file (its pretty-printed version can be found in Appendix C in the extended version of the paper). Run it with:

    $ ./slicer examples/gauss.tml

    In this program we define two systems of equations. System defined by arrays as and bs is solved correctly. System defined by arrays as' and bs' causes a division by zero. We then map gauss function over a list containing arrays defining both systems. This allows us to demonstrate that our method works in a higher-order setting even for complex functions. Note that we slice the program w.r.t. "Division by zero" exception. That is because we know our program divides by zero and we want to understand why. After running the program observe the results:

    • all elements of arrays as and bs are replaced with holes. This means that neither of them contributed to raising the exception.

    • some elements of as' are replaced with holes and some are not. This means that some elements of that array contributed to raising the exception. The last of the elements that was not replaced with a hole is located at row 2, column 1 (0-based indexing). Knowing the nature of Gaussian elimination leads us to conclusion that this is where the division by zero must have taken place.

    • in the definition of gauss method code responsible for zeroing elements above the diagonal has been replaced by a hole. This means that this code did not contribute to the result and so the exception was raised when zeroing elements below the diagonal.

Learning iTML

Syntax of iTML is based on ML. Here are some basic information that should get you started:

  • built-in primitive types are: int, double, bool, string and unit.

  • iTML does not support polymorphic types

  • you can define your own ADTs but iTML only allows them to have two constructors. Moreover, constructors can only be nullary or unary. So a list of integers would be defined as:

    data intlist = Nil | Cons (int * intlist)

    A standard map function defined over a list of integers (no polymorphism - remember!) looks like this:

    let map = fun map (f : int -> int) (xs : intlist) : intlist =>
       case xs of
          Nil -> Nil;
          Cons y -> Cons (f (fst y), map f (snd y))

    Note the calls to fst and snd - these are a consequence of storing head and tail of a list inside a tuple (Cons can be at most unary).

  • all data declarations should be placed before the program code

  • iTML does not support top-level bindings at the moment. In other words, once you define data types the remaining program is just a single expression.

  • parser currently binds operators tighter than function application. So for example fst (raise "foo") + 2 is parsed as fst ((raise "foo") + 2) rather than (fst (raise "foo")) + 2. Use parentheses to disambiguate.

  • enclose code inside a trace primitive to trace that code. Use bwdSlice for backward slicing:

    let t = trace ( (* YOUR CODE HERE *) ) in
    bwdSlice (t, (* SLICING CRITERION HERE *) )

With all that in mind we recommend that you look at programs in examples/ directory.

Source code tour

Source code is divided into a library and an executable that depends on the library. The library is located in lib directory. Under lib/Language/Slicer/ you will find these modules:

  • Absyn: abstract syntax for TML language. This is what the parser produces (Parser module).

  • Core: abstract syntax tree for the core language. Produced from TML abstract syntax tree (Absyn module) during desugaring (Desugar module). Contains also built-in operators and functions for working with the store abstraction.

  • Desugar - translates TML abstract syntax tree (Absyn module) into core language (Core module).

  • Env - definitions of variable and type environments + helper functions.

  • Error - data type for handling compilation errors.

  • Eval - evaluation of core programs

  • Monad module and Monad/ sub-directory - monads for running various stages of the interpreter pipeline.

  • Parser - well, the parser.

  • Primitives - built-in language primitives

  • Resugar - translate core programs into surface-like syntax. Used for pretty-printing.

  • Run - entry points to the interpreter

  • Slice - implementation of slicing

  • UpperSemiLattice - lattice definition

Executable is located inside src directory. src/Language/Slicer/ contains:

  • Main - executable logic (parsing command line options, invoking the library, etc.)

  • Monad/ - REPL monad

  • Repl - REPL logic


This is experimental research software. It comes as-is without any guarantees.


Companion code for paper "Imperative Functional Programs that Explain their Work", Wilmer Ricciotti, Jan Stolarek, Roly Perera and James Cheney, ICFP 2017, Oxford, UK







No packages published