Which Sustainable Software Practices Do Scientists Find Most Useful?

We studied scientists who attended two-day workshops on basic software skills to determine which tools and practices they found most useful. Our pre- and post-workshop surveys showed increases in self-reported familiarity, while our interviews showed that participants found learning Python more useful than learning the Unix shell, that they found pointers to further resources very valuable, and that background material---the "why" behind the skills---was also very valuable

Code Review For and By Scientists

We describe two pilot studies of code review by and for scientists. Our principal findings are that scientists are enthusiastic, but need to be shown code review in action, and that just-in-time review of small code changes is more likely to succeed than large-scale end-of-work reviews.Comment: 4 page

The Scalability-Efficiency/Maintainability-Portability Trade-off in Simulation Software Engineering: Examples and a Preliminary Systematic Literature Review

Large-scale simulations play a central role in science and the industry. Several challenges occur when building simulation software, because simulations require complex software developed in a dynamic construction process. That is why simulation software engineering (SSE) is emerging lately as a research focus. The dichotomous trade-off between scalability and efficiency (SE) on the one hand and maintainability and portability (MP) on the other hand is one of the core challenges. We report on the SE/MP trade-off in the context of an ongoing systematic literature review (SLR). After characterizing the issue of the SE/MP trade-off using two examples from our own research, we (1) review the 33 identified articles that assess the trade-off, (2) summarize the proposed solutions for the trade-off, and (3) discuss the findings for SSE and future work. Overall, we see evidence for the SE/MP trade-off and first solution approaches. However, a strong empirical foundation has yet to be established; general quantitative metrics and methods supporting software developers in addressing the trade-off have to be developed. We foresee considerable future work in SSE across scientific communities.Comment: 9 pages, 2 figures. Accepted for presentation at the Fourth International Workshop on Software Engineering for High Performance Computing in Computational Science and Engineering (SEHPCCSE 2016

Interpreting environmental computational spreadsheets

Abstract. Environmental computational spreadsheets are important tools in supporting decision making. However, as the underlying concepts and relations are not made explicit, the transparency and re-use of these spreadsheets is severely limited. The goal of this project is to provide a semi-automatic methodology for constructing the underlying knowl-edge level model of environmental computational spreadsheets. We de-velop and test this methodology in a limited number of case studies. Our methodology combines heuristics on spreadsheet layout and for-mulas, with existing methods from computer science. We evaluate our constructed model with both the original developers and their peers. 1 Problem Statement Current environmental issues, like climate change and biodiversity loss, are uni-versal in their scale and long-term in their impact, their mechanisms are complex, and empirical data are scarce [1–3]. In addition there is an urgent need to find strategies to cope with these issues, and political pressure on the research com

HydroShare – A Case Study of the Application of Modern Software Engineering to a Large Distributed Federally-Funded Scientific Software Development Project

HydroShare is an online collaborative system under development to support the open sharing of hydrologic data, analytical tools, and computer models. With HydroShare, scientists can easily discover, access, and analyze hydrologic data and thereby enhance the production and reproducibility of hydrologic scientific results. HydroShare also takes advantage of emerging social media functionality to enable users to enhance information about and collaboration around hydrologic data and models. HydroShare is being developed by an interdisciplinary collaborative team of domain scientists, university software developers, and professional software engineers from ten institutions located across the United States. While the combination of non–co-located, diverse stakeholders presents communication and management challenges, the interdisciplinary nature of the team is integral to the project’s goal of improving scientific software development and capabilities in academia. This chapter describes the challenges faced and lessons learned with the development of HydroShare, as well as the approach to software development that the HydroShare team adopted on the basis of the lessons learned. The chapter closes with recommendations for the application of modern software engineering techniques to large, collaborative, scientific software development projects, similar to the National Science Foundation (NSF)–funded HydroShare, in order to promote the successful application of the approach described herein by other teams for other projects

Interactive tool for iterative test suite construction

We can only test software effectively if we understand how it is intended to behave. For some categories of programs, such as scientific models, it is not obvious what the output of the software should be. New techniques are needed to help domain experts, such as scientists, gather the knowledge they need to construct suitable tests and oracles. This paper introduces a new interactive tool for iterative test suite construction that is based upon the scientific method paradigm that scientists are familiar with. We apply our technique to a deterministic mathematical model, used to predict the spread of disease, and show how it helps scientists uncover situations they had not yet considered. Of the 15 hypotheses originally created by modellers, our technique found discrepancies in all but one, allowing us to refine them into a more rigorous test suite.University of Cambridge/Wellcome Trust Junior Interdisciplinary FellowshipThis is the author accepted manuscript. It is currently under an indefinite embargo pending publication by KSI Research Inc