Justin Murphy
Akond Rahman
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.
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- Nuthan Munaiah, Steven Kroh, Craig Cabrey, and Meiyappan Nagappan. 2017. Curating GitHub for engineered software projects. Empirical Software Engineering (2017), 1--35. Google ScholarDigital Library
- Akond Rahman, Amritanshu Agrawal, Rahul Krishna, and Alexander Sobran. 2018. Characterizing the Influence of Continuous Integration: Empirical Results from 250+ Open Source and Proprietary Projects (SWAN 2018). ACM, New York, NY, USA, 8--14. Google ScholarDigital Library
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Index Terms
- A curated dataset of security defects in scientific software projects
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