Toward Automatic Generation of Scientific Software Artifacts, SIAM CS19 MS2 Scientific Software: Practices, Concerns, and Solution Strategies, February 25, 2019

Software qualities, like maintainability, reproducibility and verifiability, often suffer for Scientific Computing Software (SCS) because of inadequate documentation, traceability, change-enabling design, and testing. Software developers would like to spend more time on documentation, and other software activities, but time and resource pressures frequently make this an unrealistic goal. Ideally, developers should be able to create traceable documentation, design, code, build scripts and tests, without the drudgery of writing and maintaining them. A potential solution is to generate the documentation, code and tests automatically by using Domain Specific Languages (DSLs) over a base of scientific, computing and documentation knowledge. This is the approach that is proposed for a new scientific software development framework called Drasil. By having one source of knowledge, along with rules for transforming and consistency checking, the qualities of completeness, consistency and traceability can be achieved by construction. Moreover, these qualities can be maintained as requirements are modified, design decisions changed, and documentation standards are varied. New projects will reuse portions of the existing knowledge and expand the base when there is new information. Improving the documentation level qualities should mean an improvement in the indirect qualities of maintainability, reproducibility and verifiability.