使用配置管理和产品线软件范例来支持软件工程中的实验过程

Edison Gonzalo Espinosa Gallardo
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引用次数: 10

摘要

没有任何经验证据来支持软件构建所基于的大多数信念。我们还不知道用于开发软件的技术的充分性、限制、质量、成本和风险。实验有助于检验信念和观点,并将其转化为事实。本研究涉及复制区。复制是收集软件开发经验证据的关键组件,可以在工业中用于更有效地构建更好的软件。在软件工程(SE)中,复制并不是一件容易的事情,因为应用于软件开发的实验范式仍然不成熟。现在,复制主要是使用传统的复制包执行的。但是,由于某种原因,传统的复制包似乎并没有像预期的那样有效地在SE实验的研究人员之间传递信息。故障点似乎是复制设置,由材料、仪器、文档等的版本管理问题引起。事实证明,这是一个障碍,无法获得足够的实验细节,从而能够尽可能准确地重现实验。我们通过开发一个描述复制的模式来解决实验者之间信息交换的问题。我们将调整配置管理和产品线的想法来支持实验过程。这将使研究人员能够根据明确的知识而不是对重复的假设做出系统的决策。本研究将输出一个支持复制的web环境。该环境不仅可以灵活地归档实验材料,还可以灵活地管理实验材料,以允许具有大量实验数据存储的类似和差异化复制。该平台应可供几个研究小组在同一系列实验中合作使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using configuration management and product line software paradigms to support the experimentation process in software engineering
There is no empirical evidence whatsoever to support most of the beliefs on which software construction is based. We do not yet know the adequacy, limits, qualities, costs and risks of the technologies used to develop software. Experimentation helps to check and convert beliefs and opinions into facts. This research is concerned with the replication area. Replication is a key component for gathering empirical evidence on software development that can be used in industry to build better software more efficiently. Replication has not been an easy thing to do in software engineering (SE) because the experimental paradigm applied to software development is still immature. Nowadays, a replication is executed mostly using a traditional replication package. But traditional replication packages do not appear, for some reason, to have been as effective as expected for transferring information among researchers in SE experimentation. The trouble spot appears to be the replication setup, caused by version management problems with materials, instruments, documents, etc. This has proved to be an obstacle to obtaining enough details about the experiment to be able to reproduce it as exactly as possible. We address the problem of information exchange among experimenters by developing a schema to characterize replications. We will adapt configuration management and product line ideas to support the experimentation process. This will enable researchers to make systematic decisions based on explicit knowledge rather than assumptions about replications. This research will output a replication support web environment. This environment will not only archive but also manage experimental materials flexibly enough to allow both similar and differentiated replications with massive experimental data storage. The platform should be accessible to several research groups working together on the same families of experiments.
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