复杂软件系统的不确定性

Complex software systems (e.g., cyber-physical systems, Internet of Things, and adaptive software system) encounter various types of uncertainties in their different phases of development and operation. To handle these uncertainties, researchers have carried out a lot of research work, proposed a series of methods, and achieved considerable results. However, there is still a lack of systematic understanding of the current state-of-the-artapproaches. Motivated by this observation, this paper reports a systematic mapping study of 142 primary studies collected by following a rigorous literature review methodology. The scope of the study is about investigating on how the literature deals with uncertainties appearing in various phases or artifacts produced during a development lifecycle of cyber-physical systems and Internet of Things. Results show that uncertainties mainly appear in the phases of design definition, system analysis, and operation. Based on the 142 primary studies, uncertainties are first defined and classified into external uncertainty, internal uncertainty, and sensor uncertainty, and descriptive statistics are reported in terms of this classification. In order to explore the uncertainty in depth, external uncertainty is subdivided into environmental uncertainty, infrastructure uncertainty, user behavior uncertainty, and economic attribute uncertainty, and internal uncertainty is subdivided into uncertainty in system structure, internal interaction uncertainty, uncertainty in the technology supporting system operation, and uncertainty in the technology dealing with system operation. Furthermore, another classification is presented and descriptive statistics for those primary studies where uncertainties in eight different types of artifacts are discussed, including model uncertainty, data uncertainty, and parametric uncertainty. Results also show that researchers mainly focused on decision-making under uncertainty, uncertainty reasoning, and uncertainty specification/modeling when dealing with uncertainties. Based on the results, the future research trend is commented on in this area.