This article describes the motivation, design, and progress of the Journal of Open Source Software (JOSS). JOSS is a free and open-access journal that publishes articles describing research software. It has the dual goals of improving the quality of the software submitted and providing a mechanism for research software developers to receive credit. While designed to work within the current merit system of science, JOSS addresses the dearth of rewards for key contributions to science made in the form of software. JOSS publishes articles that encapsulate scholarship contained in the software itself, and its rigorous peer review targets the software components: functionality, documentation, tests, continuous integration, and the license. A JOSS article contains an abstract describing the purpose and functionality of the software, references, and a link to the software archive. The article is the entry point of a JOSS submission, which encompasses the full set of software artifacts. Submission and review proceed in the open, on GitHub. Editors, reviewers, and authors work collaboratively and openly. Unlike other journals, JOSS does not reject articles requiring major revision; while not yet accepted, articles remain visible and under review until the authors make adequate changes (or withdraw, if unable to meet requirements). Once an article is accepted, JOSS gives it a DOI, deposits its metadata in Crossref, and the article can begin collecting citations on indexers like Google Scholar and other services. Authors retain copyright of their JOSS article, releasing it under a Creative Commons Attribution 4.0 International License. In its first year, starting in May 2016, JOSS published 111 articles, with more than 40 additional articles under review. JOSS is a sponsored project of the nonprofit organization NumFOCUS and is an affiliate of the Open Source Initiative.
Nov 19 2015 cs.SE
The current state of nuclear fuel cycle simulation exists in highly customized form. Satisfying a wide range of users requires model modularity within such a tool. Cyclus is a fuel cycle simulator specifically designed to combat the lack of adaptability of previous generations of simulators. This is accomplished through an agent-based infrastructure and treating time discretely. The Cyclus kernel was developed to allow for models, called archetypes, of differing fidelity and function depending on need of the users. To take advantage of this flexibility, a user must write an archetype for their desired simulation if it does not yet exist within the Cyclus ecosystem. At this stage, a user graduates to the title of archetype developer. Without automation, archetype development is difficult for the uninitiated. This paper presents the framework developed for simplifying the writing of archetypes: the Cyclus preprocessor, or cycpp. cycpp addresses the computer science and software development aspects of archetype development that can be addressed algorithmically, allowing the developer to focus on modeling the physics, social policies, and economics. cycpp passes through the code three times to perform the following tasks: normalizing the code via the C preprocessor, accumulation of notations, and code generation. Not only does this reduce the amount of code a developer must write by approximately an order of magnitude, but the archetypes are automatically validated.
As nuclear power expands, technical, economic, political, and environmental analyses of nuclear fuel cycles by simulators increase in importance. To date, however, current tools are often fleet-based rather than discrete and restrictively licensed rather than open source. Each of these choices presents a challenge to modeling fidelity, generality, efficiency, robustness, and scientific transparency. The Cyclus nuclear fuel cycle simulator framework and its modeling ecosystem incorporate modern insights from simulation science and software architecture to solve these problems so that challenges in nuclear fuel cycle analysis can be better addressed. A summary of the Cyclus fuel cycle simulator framework and its modeling ecosystem are presented. Additionally, the implementation of each is discussed in the context of motivating challenges in nuclear fuel cycle simulation. Finally, the current capabilities of Cyclus are demonstrated for both open and closed fuel cycles.
Scientists spend an increasing amount of time building and using software. However, most scientists are never taught how to do this efficiently. As a result, many are unaware of tools and practices that would allow them to write more reliable and maintainable code with less effort. We describe a set of best practices for scientific software development that have solid foundations in research and experience, and that improve scientists' productivity and the reliability of their software.