haskell/hoopl

Name: hoopl

Owner: Haskell

Description: Higher-order optimization library

Created: 2015-04-14 06:37:54.0

Updated: 2018-02-01 17:21:49.0

Pushed: 2018-03-13 04:26:41.0

Homepage: http://hackage.haskell.org/package/hoopl

Size: 1872

Language: Haskell

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README

The hoopl Package Hackage Build Status

Hoopl: A Higher-Order OPtimization Library

API documentation can be found on Hackage. For detailed explanation of the library design see paper “Hoopl: A Modular, Reusable Library for Dataflow Analysis and Transformation”

| Directory | Contents | ————– | ——— | src/ | The current official sources to the Cabal package | testing/ | Tests, including a sample client. See testing/README

Development Notes
Building and testing

To build the library run:

cabal configure
cabal build
cabal install --enable-documentation

To run the tests in the testing/ folder run:

cabal configure --enable-tests
cabal test

To run the tests with the test coverage report run:

cabal configure --enable-tests --enable-coverage
cabal test

You'll need a Haskell Platform, which should include appropriate versions of Cabal and GHC.

Coding style

Please follow Johan Tibell's Haskell Style Guide for all new/modified code.

Checklist for Making Releases

In order to facilitate GHC development's workflow, the version in hoopl.cabal is to be bumped as soon as a change requires a respective version bump (according to the PVP) relative to the last released hoopl version.

  1. Make sure hoopl passes Travis for all GHC versions in the build-matrix
  2. Update Changelog (& git commit)
  3. Generate source tarball via cabal sdist and upload a candidate to Hackage (see note below), and inspect the result.
  4. If everything checks out, make an annotated and GPG-signed Git release tag: git tag -a -s v${VER} -m "hoopl ${VER}"
  5. Publish (there's a button for that on Hackage) the package candidate
  6. Work on next release

Note: To upload to Hackage,

cabal sdist
cabal upload dist/hoopl-*.tar.gz

However, it's recommended use the Hackage feature for uploading a candidate.


This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.