A curated dataset of security defects in scientific software projects

Abstract

Scientific software is defined as software that is used to explore and analyze data to investigate unanswered research questions in the scientific community [6]. The domain of scientific software includes software needed to construct a research pipeline such as software for simulation and data analysis, large-scale dataset management, and mathematical libraries [4]. Programming languages such as Julia [1] are used to develop scientific software efficiently and achieve desired program execution time. Julia was used in Celeste1, a software used in astronomy research. Celeste was used to load 178 terabytes of astronomical image data to produce a catalog of 188 million astronomical objects in 14.6 minutes2. The Celeste-related example provides anecdotal evidence on the value of studying Julia-related projects from a cybersecurity perspective.