With the increase of research in self-adaptive systems, there is a need to better understand the way research contributions are evaluated. Such insights will support researchers to better compare new findings when developing new knowledge for the community. However, so far there is no clear overview of how evaluations are performed in self-adaptive systems. To address this gap, we conduct a mapping study. The study focuses on experimental evaluations published in the last decade at the prime venue of research in software engineering for self-adaptive systems -- the International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). Results point out that specifics of self-adaptive systems require special attention in the experimental process, including the distinction of the managing system (i.e., the target of evaluation) and the managed system, the presence of uncertainties that affect the system behavior and hence need to be taken into account in data analysis, and the potential of managed systems to be reused across experiments, beyond replications. To conclude, we offer a set of suggestions derived from our study that can be used as input to enhance future experiments in self-adaptive systems.
翻译:随着自适应系统研究的增加,有必要更好地了解研究贡献的评价方式,这种洞察力将有助于研究人员在为社区开发新知识时更好地比较新的发现,然而,迄今为止,对于如何在自适应系统中进行评价,还没有清楚的概览。为了弥补这一差距,我们进行了一项绘图研究。这项研究的重点是过去十年在自适应系统软件工程研究的主要地点发表的实验性评价 -- -- 适应和自我管理系统软件工程国际专题讨论会。结果指出,自适应系统的具体特点需要在试验过程中得到特别注意,包括管理系统(即评价目标)和管理系统的区别、影响系统行为并因此需要在数据分析中加以考虑的不确定性的存在,以及管理下系统除复制外可在各种试验中再利用的潜力。最后,我们提出从我们的研究中得出的一系列建议,可以用来作为加强自适应系统未来试验的投入。