Code Monkey home page Code Monkey logo

assignment-autotest's Introduction

Github Actions Status

[Build Status

assignment-autotest

A repository which can be used for autotest of assignments, leveraging the Unity automated test framework.

This project is a CMake and script wrapper around Unity which allows:

  • Test dependencies to be included as a git submodule on student assignment repositories.
  • Instructors can define functions containing tests they expect to pass on completed student submissions, which can be shared with students through this repository in the test subfolder.
  • Instructors can define files containing tests that will not be shared with students but which should also pass on student's final submission. These will be located in the parent repository containing this repository as a submodule.
  • Students can define their own test functions/files they use to test their code in their own repositories, referencing this repository as a submodule.
  • Other tests which aren't unity based can also be located in the appropriate test/assignment subdirectory and included with automated tests

See the Unity reference documentation for information about writing Unity test cases.

Using This Repository

Follow the instructions in this section to setup your source code repository with assignments.

Setting Up Your Host

  1. Install build-essential or equivalent on non-ubuntu platforms (gcc, g++, make).
  2. Install ruby on your host. This is used to run unity helper scripts used to generate test runner files.
  3. Install cmake on your host.

On Ubuntu the above steps can be completed with sudo apt-get install -y build-essential ruby cmake.

Clone this repository as a submodule

Inside your existing git repository containing assignment example source code or completed assignment implementations, use git submodule add to add this repository as a submodule.

Then use git submodule update --init --recursive to initialize the Unity submodule referenced within this repository.

Add Example Tests

Add your example test files for students which show how they can specify and add unit tests. Unit Tests are added through a CMakeLists.txt file at the root of your repository which sets cmake variables referencing:

  • The files containing test_XXXX functions which use unity to unit test application source
  • The files containing application source code to be unit tested.

Refer to the comments in the CMakeLists-parent-example.txt for variable usage instructions

A simple example is shown in the examples subdirectory, CMakeLists-parent-example.txt file, and test/assignment1 subdirectory.

Update your gitignore

Include these patterns in your root .gitignore file

Test_*_Runner.c
build/

Running Tests

Use cmake to build your parent project using something like: mkdir build && cd build then cmake .. && make && cd ..

Then run build/assignment-autotest/assignment-autotest from within the build directory to run the Unity based automated tests.

You can run only the unity based automated tests using the test-unit.sh script.

You can add additional tests to cover other assignment requirements in the test directory, and use logic in your ./test.sh test script to pull them in.

These steps are automated in the test-basedir.sh script which you can copy into your base repository directory and use as a template example

CI Integration

Github Actions

If you can add automated CI testing to your base repo by following these steps.

  1. Copy the test-basedir.sh script to the repository containing this submodule and rename ./test.sh
  2. Copy the .github directory to the base directory of the repository containing this submodule and customize the workflow/github-actions.yml file to perform testing for your implementation.
  3. If desired, add a badge to your README.md showing build status. See the line at the top of this README.md for an example.

Running An Example

To see an example implementation in action, run the ./test.sh script, passing in an argument to a directory subfolder on the host. If the directory does not correspond to an existing git repository a git repository will be initialized there, then the steps to clone the repository as a submodule, add example tests, and run tests will be done automatically. If no argument is specified, the example will be demonstrated in a temporary directory created on the host.

Running Example Using Docker

Running tests in Docker is a useful step to simulate the behavior on the CI build system. This is especially true for gitlab-ci builds since these are configured to use the same image.

Start by setting up docker community edition on your host. See install instructions here for Ubuntu.

You can run test in a docker container using the docker/run-test.sh script. This script is currently setup to use the same image used for gitlab-ci testing, cuaesd/aesd-autotest but could be customized to use any docker container suitable for your assignments.

Run from any base directory containing a test.sh script. The script will start the docker container, pass through the base directory as a volume, change user/group ID of the user in the container to match the caller (to avoid permission issues with builds outside the container), and then run the test script.

assignment-autotest's People

Contributors

dwalkes avatar akshita-bhasin avatar maitreyee2095 avatar sarayumanagoli avatar lnxblog avatar jmiv-afk avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.