In situ data infrastructure for scientific unit testing platform

Testing is a significant software development process for the management of software systems and scientific code. However, as the complexity of scientific codes increases, extra checks are needed to monitor impacts to dependent models and to verify system constraints. The software complexity also impedes the efforts of module developers and software engineers to rapidly develop and extend their code. Recently, we have developed an automatic methodology and prototype platform to facilitate scientific verification of individual functions within complex scientific codes. With this system, the scientific module builders are able to track variables conveniently in one module or track variables' changes among different modules. In this paper, we present a procedure for automatic unit testing generation. For the interest of a general audience of this conference, we are emphasizing the technical details of integrating the In Situ data infrastructure into our platform. At the end of this paper, we have included an implementation of unit testing for the ACME Land Model (ALM) to demonstrate the usefulness and correctness of the platform. We have also used single- and multipoint checks to demonstrate the efficient variable tracking capability of this platform.