The Common Lisp Cookbook – Testing

So you want to easily test the code you’re writing ? The following recipes cover how to write automated tests and see their code coverage. We also give pointers to plug those in modern continuous integration services like Travis CI and Coveralls.

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. We prefer Prove for its doc and its extensible reporters (it has different report styles and we can extend them).

Testing with Prove

Install and load

Prove is in Quicklisp:

(ql:quickload :prove)

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: ok, is, isnt, is-values, is-type, like (for regexps), is-print (checks the standard output), is-error, is-expand, pass, fail, skip, subtest.

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 usual C-c C-c.

More about Prove

Prove can also:

  • be run on Travis CI,
  • colorize the output,
  • report tests duration,
  • change the default test function,
  • set a treshold for slow tests,
  • invoke the CL debugger whenever getting an error during running tests,
  • integrate with ASDF so than we can execute (asdf:test-system) or (prove:run) in the REPL (such configuration is provided by cl-project, by the same author).

See Prove’s documentation !

Code coverage

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 sb-cover:store-coverage-data 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:

(sb-cover:report "coverage/")

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.

Continuous Integration

Travis CI and Coveralls

Travis is a service for running unit tests in the cloud and Coveralls shows you the evolution of coverage over time, and also tells you what a pull request will do to coverage.

Thanks to cl-travis we can easily test our program against one or many Lisp implementations (ABCL, Allegro CL, SBCL, CMUCL, CCL and ECL). 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:

Gitlab CI

Gitlab CI is part of Gitlab and is available on Gitlab.com, for public and private repositories. Let’s see straight away a simple .gitlab-ci.yml:

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 daewok/lisp-devel 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 make test.

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 stages (see environments), “test” and “build”, defined to run one after another. A “build” stage will start only if the “test” one succeesds.

“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 artifacts’s 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:

https://gitlab.com/username/project-name/-/jobs/artifacts/master/raw/some-file-name?job=build

When the pipelines pass, you will see:

You now have a ready to use Gitlab CI.

Page source: testing.md