We will use an established and well-designed regression testing
framework called Prove. It is
not the only possibility though,
FiveAM is a popular one (see
this blogpost for an
introduction) and there are others (and more again). We prefer
Prove for its documentation and its extensible reporters (it has different
report styles and we can extend them).
warning: Prove has a couple limitations and will soon be obsolete. We advise to start with another test framework.
Testing with Prove
Install and load
Prove is in Quicklisp:
This command installs
prove if necessary, and loads it.
Write a test file
(in-package :cl-user) (defpackage my-test (:use :cl :prove)) (in-package :my-test) (subtest "Showing off Prove" (ok (not (find 4 '(1 2 3)))) (is 4 4) (isnt 1 #\1))
Prove’s API contains the following testing functions:
like (for regexps),
(checks the standard output),
Run a test file
(prove:run #P"myapp/tests/my-test.lisp") (prove:run #P"myapp/tests/my-test.lisp" :reporter :list)
We get an output like:
Run one test
You can directly run one test by compiling it. With Slime, use the
More about Prove
Prove can also:
- be run on Travis CI,
- colorize the output,
- report tests duration,
- change the default test function,
- set a threshold for slow tests,
- invoke the CL debugger whenever getting an error during running tests,
- integrate with ASDF so than we can execute
(prove:run)in the REPL (such configuration is provided by cl-project, by the same author).
See Prove’s documentation !
Interactively fixing unit tests
Common Lisp is interactive by nature (or so are most implementations), and testing frameworks make use of it. It is possible to ask the framework to open the debugger on a failing test, so that we can inspect the stacktrace and go to the erroneous line instantly, fix it and re-run the test from where it left off, by choosing the suggested restart.
With Prove, set
Below is a short screencast showing all this in action (with FiveAM):
Note that in the debugger:
<enter>on a backtrace shows more of it
von a backtrace goes to the corresponding line or function.
- see more options with the menu.
A code coverage tool produces a visual output that allows to see what parts of our code were tested or not:
Generating an html test coverage output
SBCL comes with a built-in module to do code coverage analysis: sb-cover.
Coverage reports are only generated for code compiled using
compile-file with the value of the
optimization quality set to 3.
;;; Load SB-COVER (require :sb-cover) ;;; Turn on generation of code coverage instrumentation in the compiler (declaim (optimize sb-cover:store-coverage-data)) ;;; Load some code, ensuring that it's recompiled with the new optimization ;;; policy. (asdf:oos 'asdf:load-op :cl-ppcre-test :force t) ;;; Run the test suite. (prove:run :yoursystem-test)
Produce a coverage report, set the output directory:
Finally, turn off instrumentation:
(declaim (optimize (sb-cover:store-coverage-data 0)))
You can open your browser at
../yourproject/t/coverage/cover-index.html to see the report like
the capture above or like
this code coverage of cl-ppcre.
Travis CI and Coveralls
cl-travis we can easily test our program against one or many
Lisp implementations (ABCL, Allegro CL, SBCL, CMUCL, CCL and
cl-coveralls helps to post our coverage to the service. It
supports SBCL and Clozure CL with Travis CI and Circle CI.
We refer you to the lengthy and illustrated explanations of the “continuous integration” page on lisp-lang.org.
You’ll find many example projects using them in the links above, but if you want a quick overview of what it looks like:
image: daewok/lisp-devel before_script: - apt-get update -qy - apt-get install -y git-core - git clone https://github.com/foo/bar ~/quicklisp/local-projects/ test: script: - make test
Gitlab CI is based on Docker. With
image we tell it to use the
one. It includes SBCL, ECL, CCL and ABCL, and Quicklisp is installed
in the home (
/home/lisp/), so we can
quickload packages right
away. If you’re interested it also has a more bare bones option. Gitlab will load the
image, clone our project and put us at the project root with
administrative rights to run the rest of the commands.
test is a “job” we define,
script is a
recognized keywords that takes a list of commands to run.
Suppose we must install dependencies before running our tests:
before_script will run before each job. Here we clone a library
where Quicklisp can find it, and for doing so we must install git
(Docker images are usually pretty bare bones).
We can try locally ourselves. If we already installed Docker and
started its daemon (
sudo service docker start), we can do:
docker run --rm -it -v /path/to/local/code:/usr/local/share/common-lisp/source daewok/lisp-devel:latest bash
This will download the lisp image (±400Mo), mount some local code in
the image where indicated, and drop us in bash. Now we can try a
To show you a more complete example:
image: daewok/lisp-devel stages: - test - build before_script: - apt-get update -qy - apt-get install -y git-core - git clone https://github.com/foo/bar ~/quicklisp/local-projects/ test: stage: test script: - make test build: stage: build only: - tags script: - make build artifacts: paths: - some-file-name
Here we defined two
“test” and “build”, defined to run one after another. A “build” stage
will start only if the “test” one succeeds.
“build” is asked to run
only when a
new tag is pushed, not at every commit. When it succeeds, it will make
the files listed in
paths available for download. We can
download them from Gitlab’s Pipelines UI, or with an url. This one will download
the file “some-file-name” from the latest “build” job:
When the pipelines pass, you will see:
You now have a ready to use Gitlab CI.
Page source: testing.md