Hacking guide

Using VSCode remote containers

We recommend using VSCode Remote Containers to reproduce the very same dev environment used by our core team members. The steps to set up the dev environment are:

  • Do a local clone of the asterius repo

  • Install VSCode (at least 1.45) and its remote extension

  • Install podman, and make sure the podman command works with the current user

  • Set up a docker symlink which points to podman, according to VSCode announcement of podman support

  • docker pull terrorjack/asterius:dev

  • Open the asterius repo with remote containers

Opening the repo with remote containers for the first time will take some time, since it runs the build script to build asterius and perform booting. Later re-opening will be near instant, since it reuses the previous container.

The dev image shall work with docker too if the userns-remap related settings are correctly set up. Check the documentation section for relevant explanation; when using docker with default settings, there is a file permission issue when mounting your local filesystem into the prebuilt container images.

Using direnv

If direnv is enabled, the PATH of the current shell session will be extended to include the locations of Asterius executables. This means it’s possible to run ahc-link .. instead of stack exec ahc-link -- ...

Hacking with ghcid

A known-to-work workflow of hacking Asterius is using ghcid. We also include an example .ghcid file, so running ghcid at the project root directory shall work out of the box.

Some notes regarding the usage of ghcid:

  • Multiple lib targets can be loaded at once, but only one main target (exe/test) can be loaded. When hacking a specific exe/test, modify the local utils/ghcid.sh script first. Before committing changes in the Haskell codebase, it would be nice to run stack build --test --no-run-tests to make sure all executables are not broken by lib changes.

To boot or not to boot

As described in the building guide, stack build only builds the Asterius compiler itself; additionally we need to run stack exec ahc-boot to run the compiler on the boot libs. This process is typically only needed once, but there are cases when it needs to be re-run:

  • The boot libs in ghc-toolkit/boot-libs are modified.

  • The Asterius.Types module is modified, so the IR types have changed.

  • The Asterius.CodeGen module is modified and you’re sure different code will be generated when compiling the same Haskell/Cmm files.

Most other modifications in the Asterius lib/exes won’t need a reboot. Specifically:

  • Asterius.Builtins modifications don’t impact the boot cache. The builtin module is generated on the fly with every linker invocation.

When rebooting, run utils/reboot.sh in the project root directory, so that we can ensure the booting is used with the up-to-date version of asterius and the boot lib sources.

The ahc-boot process is configurable via these environment variables:




Doing profiled builds

Doing profiled builds within a local git tree

Use stack-profile.yaml to overwrite stack.yaml, and then run utils/reboot.sh to kick off the rebooting process. This will be quite slow due to the nature of profiled builds; all libraries will be rebuilt with the profiled flavor. Better to perform a profiled build in a standalone git tree.

Once the profiled build is complete, it’s possible to use RTS flags to obtain profile data when compiling Haskell sources. At runtime there are two ways to pass RTS flags to a Haskell executable:

  • The GHCRTS environment variable

  • The +RTS ... -RTS command line arguments

Always use GHCRTS when running programs like ahc-link, since those programs can spawn other processes (e.g. ahc-ld), and we’re often interested in the profile data of all Asterius executables. The GHCRTS environment variable can propagate to all processes.

See the relevant section in the GHC user guide for more information on profiling Haskell apps. There are also some third party applications useful for analyzing the profiling data, e.g. eventlog2html, ghc-prof-flamegraph.

Fow now, a major problem with the profiled build is: it seems to emit dysfunctional code which doesn’t work. Consequently, this affects the TH runner, so any dependencies relying on TH isn’t supported by the profiled build.

Measuring time/allocation differences

When working on a performance-related PR, we often want to measure the time/allocation differences it introduced. The workflow is roughly:

  • Perform two profiled builds with Docker; one builds from the master branch, one from the PR’s branch.

  • Run ahc-link in the built images on the example program below, setting the necessary GHCRTS to generate the profile reports. The code should be put in two standalone directories, otherwise the .hi/.o files may conflict or be accidentally reused.

The profiled Docker images contain pre-compiled Cabal. And the example program we use to stress-test the linker is:

import Distribution.Simple
main = defaultMain

We choose this program since it’s classic, and although being short, it pulls in a lot of data segments and functions, so it exposes the linker’s performance bottleneck pretty well.

Adding a test case

To add a test case, it is best to replicate what has been done for an existing testcase.

  • For example, git grep bytearraymini should show all the places where the test case bytearraymini has been used. Replicating the same files for a new test case should “just work”.