LORIS is an open-source framework that facilitates data sharing for neuroscience labs and sites. It hosts both frontend and backend services that help facilitate data sharing and manipulation among researchers. The codebase includes many modules that perform different functionalities. Therefore, this type of service requires automated testing to ensure that all the moving parts are working correctly.

Both unit and integration tests are necessary for a large project like this to run smoothly so that any bugs can be caught and fixed early and efficiently. This is especially important for projects like this that work with data manipulation and therefore require careful attention to detail. Improving the testing database and the test datasets is also a very important part of this project since the automated tests cannot be relied upon if the datasets being used to test them do not reflect the real world. This will need to be a big focus of the project. Finally, creating documentation that can help future developers and users test LORIS themselves and write their own tests is integral to the continuation of this work.