ISC 2018 Tutorial: Better Scientific Software

The computational science and engineering (CSE) community is in the midst of an extremely challenging period created by the confluence of disruptive changes in computing architectures, demand for greater scientific reproducibility, and new opportunities for greatly improved simulation capabilities, especially through coupling physics and scales. Computer architecture changes require new software design and implementation strategies, including significant refactoring of existing code. Reproducibility demands require more rigor across the entire software endeavor. Code coupling requires aggregate team interactions including integration of software processes and practices. These challenges demand large investments in scientific software development and improved practices. Focusing on improved developer productivity and software sustainability is both urgent and essential.

This tutorial will provide information and hands-on experience with software practices, processes, and tools explicitly tailored for CSE. Goals are improving the productivity of those who develop CSE software and increasing the sustainability of software artifacts. We discuss practices that are relevant for projects of all sizes, with emphasis on small teams, and on aggregate teams composed of small teams. Topics include software licensing, effective models, tools, and processes for small teams (including agile workflow management), reproducibility, and scientific software testing and verification (including automated testing and continuous integration).

Content Level 45% beginner, 45% intermediate, 10% advanced

Target Audience This tutorial is designed to benefit any scientific software development project, irrespective of its size and scope and it can benefit people at any stage of their career. While the content skews towards beginner and intermediate levels, many established software developers appreciate learning about ideas we present in this tutorial.

Prerequisites Attendees should have an interest in improving their software development experience. Some prior experience with scientific software development would be helpful in understanding the concepts presented but is not absolutely necessary. For the hands-on activities, attendees should have a computer with wifi connectivity and a web browser. We use GitHub for portions of the hands-on, and attendees should have, or be willing to setup a GitHub user account. Access to the GNU compiler suite (via network is fine) would be beneficial for the code coverage hands-on exercises, but is not strictly necessary since we make a copy of the generated coverage report available online as well.