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Within a Category you can create the actual tests. There are several different tests, which offers enough flexibility to easily set up completely new tests or execute any already existing testing tools.

Our philosophy is that even automatic assessment using AutoTest should be feedback oriented: AutoTests should always give as much feedback to the student as possible. This is already enforced by linking the AutoTest and Rubric Categories. Another way to maximize feedback to students is by naming your tests and inputs in a meaningful way, as this is the first feedback students will receive from the tests.


Use weights per test (or per input of IO test) to differentiate between the importance of tests.

IO Test

The IO Test is the most common test to create. This is a test in which you specify an input to a program and an expected output. If the students’ program returns the same output as expected, the test passes and they achieve points.

A (student) program can be specified to be run in the IO tests, then, you can specify all input and output combinations you want to check for this program.

Multiple options allow you to more flexibly compare the output of the program:

  • Case insensitive: ignore case in comparing the expected output and actual output.

  • Ignore trailing whitespace: trim all trailing whitespacing from the start and end.

  • Ignore all whitespace: all whitespace is ignored when comparing the student output with the expected output (including newlines).

  • Substring: the expected output should be a substring of the actual output.

  • Regex: the expected output is a Python3 Regex which should match with the actual output.


The options Ignore all whitespace and regex cannot be activated together.


The option substring is required when using the regex option.

Use the button in the bottom left corner to create a new input/output combination.

Use cases

As the name suggests, IO Tests are used to check the output of a program given an input. IO Tests are very useful to check the functionality of simple and advanced programs. From checking for Hello, World! to checking if a sudoku solver is correctly implemented or even complex mathematical programs. Additionally, IO Tests can be used to check the correct handling of incorrect input.


If you require files as input to your tests, upload these files as fixtures to find them in $FIXTURES/[FILE], where you can then use them as input arguments to your test.

Run Program Test

The Run Program Test simply executes a specified program and checks the return code or exit status of this program. Meaning, an exit status of 0 (or success) results in passing the test and any nonzero exit status (or failure) results in failing the test.

Use cases

Run Program Tests are easy to set up and effective to check program execution when specific output is not important. Use Run Program Tests, for instance, to check the successful compilation of student code.

Capture Points Test

The Capture Points Test is an extension of the Run Program Test. It also executes a specified program but instead of taking the exit status, captures the output of this program. The output of the program can be captured using a Python3 Regex. This output should be a valid Python Float number between 0.0 and 1.0. This number is then multiplied with the weight of the Capture Point Test to get to the final score of the test.


The float captured for a Capture Points Test is captured from the last 32 kB of output data.

Use cases

Capture Points Tests are especially useful to run programs of which the output is of importance. Use Capture Points Tests to execute and evaluate your own unit test scripts or any other specific programs you want to use to evaluate student code.

It is easy to use existing unit test frameworks with the Capture Points Test, simply write a small wrapper script around it to parse the output to a value between 0 and 1.


If you have trouble writing these wrapper scripts or using the Capture Points Test with your own frameworks, contact us and we’re happy to help you!

See also the Unit Test documentation for achieving something similar while displaying the results in a more user-friendly way.


A Checkpoint can be used to add conditions to your Test Categories. A Checkpoint can be put in between tests, to only execute the following tests if a certain percentage of points have been scored in the tests preceding to the Checkpoint.

Use cases

It can be necessary to add conditionality between tests in your Test Category. This can be done with a Checkpoint, which is for instance useful if you check compilation in a first test and you only want to run following tests if this test succeeded.

Unit Test

The Unit Test provides integration with unit testing frameworks that support JUnit XML output. The only input for this type of test is a command to be run, which must produce a JUnit XML file at the location stored in the $CG_JUNIT_XML_LOCATION environment variable. Students will then get a clear overview of all the tests that have been run, which ones failed, and the output that was produced in the case of failure.

Use cases

Unit Tests are useful if you want to run many tests but condense their output into a single entry in the test category. They are also useful when you already have a unit testing setup, and do not want to translate them all into individual AutoTest tests.

Compatibility scripts

For most unit testing frameworks it is necessary to install additional software and to figure out how to make the framework output its results to the correct location. We provide wrapper scripts for a growing list of frameworks that handle all of this for you. Want to know if your preferred testing framework is supported, or does a script not work as you need it to? Please send an email to support@codegrade.com so we can discuss the possibilities!

Supported frameworks



Script name







Tasty (Quickcheck)



Junit 4



Junit 5













Jupyter Notebook






Python 2+3


Code Quality

Code Quality tests provide integration with existing linters, but you can also provide your own code analysis tool that produces feedback programatically. The generated feedback is accessible in the code viewer by moving your cursor over the line numbers with comments, as well as in the AutoTest output.

Students will receive a penalty for each comment that was generated by the linter.

Use cases

The Code Quality test is useful when you want students to learn to adhere to a style guide, but also when you want to warn your students about common pitfalls in the language and/or framework you are using.

Compatibility scripts

For most linters it is necessary to transform their output to a format CodeGrade can understand. This is quite the tricky business, so CodeGrade provides integration for a couple of popular linters out of the box! For the linters that are already supported, refer to the table below. If your favourite linter is not in the list, please send us an email at support@codegrade.com so we can discuss how we can add support for it.

Supported linters