根据Boehm和Turner模型的科学软件开发项目的经验特征:进度报告

Carlton A. Crabtree, A. G. Koru, C. Seaman, H. Erdogmus
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引用次数: 12

摘要

最近的一些研究报告了在科学软件开发项目中应用敏捷方法的成功。这些研究发现,敏捷方法非常适合科学探究的探索性、迭代性和协作性。然而,这些发现可能不适用于与科学软件开发项目相关的所有情况。此外,在决定应该采用哪种开发方法和实践时,它们只构成重要因素的一个子集。因此,在就该领域采用某些开发方法和实践提出建议之前,进行进一步的研究变得非常重要。在这份进度报告中,我们讨论了我们正在进行的研究,这些研究将根据Boehm和Turner提出的模型,实证地研究各种科学软件开发项目的特征。我们计划从巴尔的摩-华盛顿地区的各种科学软件开发项目中进行访谈和收集数据。我们期望我们的定性结果将增加我们对那些支持计划驱动方法或敏捷方法的项目的特征的理解,以及与这些特征相关的需求和条件。我们的研究为科学的软件开发人员提供了指导,提高了他们评估和理解自己项目特征的能力,并选择了有效的软件实践。作为同一方向的长期利益,我们的定性结果将产生一组假设,这些假设可以在不同的项目环境中进行测试,以更好地理解和分类科学的软件开发项目。因此,在未来,可以为科学的软件开发项目提出更一般化和可操作的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An empirical characterization of scientific software development projects according to the Boehm and Turner model: A progress report
A number of recent studies reported on the success of applying agile methods in scientific software development projects. These studies found that agile methods are well suited to the exploratory, iterative, and collaborative nature of scientific inquiry. However, these findings might not be applicable in all situations pertaining to scientific software development projects. In addition, they only constitute a subset of the important factors while deciding which development methods and practices should be adopted. Therefore, it becomes important to conduct further research before making recommendations regarding the adoption of certain development methods and practices in this domain. In this progress report, we discuss our on-going research that will empirically study the characteristics of various scientific software development projects according to a model suggested by Boehm and Turner. We plan to conduct interviews and collect data from various scientific software development projects in the Baltimore-Washington area. We expect that our qualitative results will increase our understanding of the characteristics in those projects favoring plan-driven approaches or agile methods, and the needs and conditions associated with those characteristics. Our research provides guidance to scientific software developers by enhancing their capacity to evaluate and understand their own project characteristics and select effective software practices. As a long-term benefit in the same direction, our qualitative results will generate a set of hypotheses that can be tested in different project environments to better understand and categorize scientific software development projects. Consequently, in the future, more generalizable and actionable recommendations can be made for scientific software development projects.
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