Supporting and accelerating reproducible empirical research in software evolution and maintenance using TraceLab Component Library
Supporting and accelerating reproducible empirical research in software evolution and maintenance using TraceLab Component Library
复制标题
DOI：
10.1007/s10664-014-9339-3
复制
发表时间：
2015-10-01
影响因子：
4.1
通讯作者：
Cleland-Huang, Jane
中科院分区：
文献类型：
--
作者：
Dit, Bogdan;Moritz, Evan;Cleland-Huang, Jane
众所周知，由于缺乏数据集、工具、实现细节（例如，参数值、环境设置）和其它因素。该领域的进展受到将新技术与现有技术进行比较的挑战的阻碍，因为研究人员必须将大部分资源投入到复制以前引入的方法的繁琐且容易出错的过程中。在本文中，我们解决了软件维护中的实验再现性问题，并提供了一个长期的解决方案，以确保未来的实验将是可再现的和可扩展的。我们进行了初步的映射研究的一些代表性的维护技术和方法，并实现它们作为一组实验和组件库，我们公开与TraceLab，称为组件库。这些实验和组成部分的目标是创建一个可操作的知识体系，（i）促进未来的研究，（ii）允许研究界也为之做出贡献。此外，为了说明使用和适应这些技术的过程，我们提出了一个基于现有技术创建新技术的例子，以产生更好的结果。
Research studies in software maintenance are notoriously hard to reproduce due to lack of datasets, tools, implementation details (e.g., parameter values, environmental settings) and other factors. The progress in the field is hindered by the challenge of comparing new techniques against existing ones, as researchers have to devote a large portion of their resources to the tedious and error-prone process of reproducing previously introduced approaches. In this paper, we address the problem of experiment reproducibility in software maintenance and provide a long-term solution towards ensuring that future experiments will be reproducible and extensible. We conducted a preliminary mapping study of a number of representative maintenance techniques and approaches and implemented them as a set of experiments and a library of components that we make publicly available with TraceLab, called the Component Library. The goal of these experiments and components is to create a body of actionable knowledge that would (i) facilitate future research and (ii) allow the research community to contribute to it as well. In addition, to illustrate the process of using and adapting these techniques, we present an example of creating new techniques based on existing ones, in order to produce improved results.