Page 34 - 《软件学报》2021年第7期

1952 Journal of Software 软件学报 Vol.32, No.7, July 2021

本文针对不确定性处理方法的调研未能深层次挖掘不确定性处理方法的差异,对于不确定性的分类粒度较大,
对制品不确定性的分类更多地是基于软件工程的角度,所以未能更好地探究自动化领域的不确定性类型和特
征,未能更深层次地探究两个领域的研究差异.未来我们将综合考虑自动化和计算机领域(尤其是软件工程)的
差异,科学地分析两者研究不确定性的类型以及不确定性方法,从而进行两个领域的优势互补,为其他研究者提
供一些参考.

References:
[1] Lee EA. Cyber physical systems: Design challenges. In: Proc. of the 11th IEEE Int’l Symp. on Object and Component-oriented
Real-time Distributed Computing (ISORC). IEEE, 2008. 363–369.
[2] Uckelmann D, Harrison M, Michahelles F. Architecting the Internet of Things. Springer Science & Business Media, 2011.
[3] Salton G. The Smart System. In: Retrieval Results and Future Plans. 1971.
[4] Greer C, Burns M, Wollman D, Griffor E. Cyber-physical systems and Internet of Things. NIST Special Publication, 2019(202):
52,1900.
[5] Lindsay J. Aristotle and the criterion of truth. The Monist, 1921,31(3):470–475.
[6] Halpern JY. Reasoning about Uncertainty. MIT Press, 2017.
[7] Der Kiureghian A, Ditlevsen O. Aleatory or epistemic? does it matter? Structural Safety, 2009,31(2):105–112.
[8] Matthies HG. Quantifying uncertainty: Modern computational representation of probability and applications. In: Proc. of the
Extreme Man-made and Natural Hazards in Dynamics of Structures, Springer-Verlag, 2007. 105–135.
[9] Gerostathopoulos I, Skoda D, Plasil F, Bures T, Knauss A. Architectural homeostasis in self-adaptive software-intensive cyber-
physical systems. In: Proc. of the European Conf. on Software Architecture. Springer-Verlag, 2016. 113–128.
[10] Zavala E, Franch X, Marco J, Knauss A, Damian D. Sacre: Supporting contextual requirements’ adaptation in modernself-adaptive
systems in the presence of uncertainty at runtime. Expert Systems with Applications, 2018,98:166–188.
[11] Geisberger E, Broy M. AgendaCPS. Berlin, Heidelberg: Springer-Verlag, 2012.
[12] Gu X, Easwaran A. Towards safe machine learning for CPS: Infer uncertainty from training data. In: Proc. of the 10th ACM/IEEE
Int’l Conf. on Cyber-physical Systems. 2019. 249–258.
[13] Zhang M, Bran S, Shaukat A, Yue T, Okariz O, Norgren R. Understanding uncertainty in cyber-physical systems: A conceptual
model. In: Proc. of the European Conf. on Modelling Foundations and Applications. Springer-Verlag, 2016. 247–264.
[14] Esfahani N, Kouroshfar E, Malek S. Taming uncertainty in self-adaptive software. In: Proc. of the 19th ACM SIGSOFT Symp. and
the 13th European Conf. on Foundations of Software Engineering. 2011. 234–244.
[15] Marinho M, Sampaio S, Lima T, Moura H. A systematic review of uncertainties in software project management. arXiv Preprint
arXiv: 1412.3690, 2014.
[16] Asan U, Soyer A. Failure mode and effects analysis under uncertainty: A literature review and tutorial. In: Intelligent Decision
Makingin Quality Management. Springer-Verlag, 2016. 265–325.
[17] Shevtsov S, Berekmeri M, Weyns D, Maggio M. Control-theoretical software adaptation: A systematic literature review. IEEE
Trans. on Software Engineering, 2017,44(8):784–810.
[18] Salih A, Omar M, Yasin A. Understanding uncertainty of software requirements engineering: A systematic literature review
protocol. In: Proc. of the Asia Pacific Requirements Engeneering Conf. on Requirements Engineering for Internet of Things
(APRES 2017). 2018. 164–171.
[19] Zhang MY, Jin Z, Zhao HY, Luo YX. Survey of machine learning enabled software self-adaptation. Ruan Jian Xue Bao/Journal of
Software, 2020,31(8):2404−2431 (in Chinese with English abstract). http://www.jos.org.cn/1000-9825/6076.htm [doi: 10.13328/
j.cnki.jos.006076]
[20] Kitchenham B, Brereton OP, Budgen D, Turner M, Bailey J, Linkman S. Systematic literature reviews in software engineering—a
systematic literature review. Information and Software Technology, 2009,51(1):7–15.
[21] Kitchenham B, Charters S. Guidelines for performing systematic literature reviews in software engineering. Technical Report, 2007.
[22] Dybå T, Dingsøyr T. Empirical studies of agile software development: A systematic review. Information and Software Technology,
2008,50(9/10):833–859.