PUMA publications for /group/researchcode/softwareEngineeringTue Sep 12 16:10:46 CEST 2017International Journal of Software Engineering and Knowledge Engineering04463-506DEVELOPMENT OF SCIENTIFIC SOFTWARE: A SYSTEMATIC MAPPING, A BIBLIOMETRICS STUDY, AND A PAPER REPOSITORY232013softwareEngineering literatureReview software scientific research <p class="first last">Scientific and engineering research is heavily dependent on effective development and use of software artifacts. Many of these artifacts are produced by the scientists themselves, rather than by trained software engineers. To address the challenges in this area, a research community often referred to as "Development of Scientific Software" has emerged in the last few decades. As this research area has matured, there has been a sharp increase in the number of papers and results made available, and it has thus become important to summarize and provide an overview about those studies. Through a systematic mapping and bibliometrics study, we have reviewed 130 papers in this area. We present the results of our study in this paper. Also we have made the mapping data available on an online repository which is planned to be updated on a regular basis. The results of our study seem to suggest that many software engineering techniques and activities are being used in the development of scientific software. However, there is still a need for further exploration of the usefulness of specific software engineering techniques (e.g., regarding software maintenance, evolution, refactoring, re(v)-engineering, process and project management) in the scientific context. It is hoped that this article will help (new) researchers get an overview of the research space and help them to understand the trends in the area.</p> </div>Tue Sep 12 16:07:54 CEST 2017Information and Software Technology 207 - 219Claims about the use of software engineering practices in science: A systematic literature review 672015science softwareEngineering literatureReview Computational Abstract Context: Scientists have become increasingly reliant on software in order to perform research that is too time-intensive, expensive, or dangerous to perform physically. Because the results produced by the software drive important decisions, the software must be correct and developed efficiently. Various software engineering practices have been shown to increase correctness and efficiency in the development of traditional software. It is unclear whether these observations will hold in a scientific context. Objective: This paper evaluates claims from software engineers and scientific software developers about 12 different software engineering practices and their use in developing scientific software. Method: We performed a systematic literature review examining claims about how scientists develop software. Of the 189 papers originally identified, 43 are included in the literature review. These 43 papers contain 33 different claims about 12 software engineering practices. Results: The majority of the claims indicated that software engineering practices are useful for scientific software development. Every claim was supported by evidence (i.e. personal experience, interview/survey, or case study) with slightly over half supported by multiple forms of evidence. For those claims supported by only one type of evidence, interviews/surveys were the most common. The claims that received the most support were: “The effectiveness of the testing practices currently used by scientific software developers is limited” and “Version control software is necessary for research groups with more than one developer.” Additionally, many scientific software developers have unconsciously adopted an agile-like development methodology. Conclusion: Use of software engineering practices could increase the correctness of scientific software and the efficiency of its development. While there is still potential for increased use of these practices, scientific software developers have begun to embrace software engineering practices to improve their software. Additionally, software engineering practices still need to be tailored to better fit the needs of scientific software development.