@inproceedings{casanova_diagnosing_2014,
	address = {New York, NY, USA},
	series = {{SEAMS} 2014},
	title = {Diagnosing unobserved components in self-adaptive systems},
	isbn = {978-1-4503-2864-7},
	url = {https://doi.org/10.1145/2593929.2593946},
	doi = {10.1145/2593929.2593946},
	abstract = {Availability is an increasingly important quality for today's software-based systems and it has been successfully addressed by the use of closed-loop control systems in self-adaptive systems. Probes are inserted into a running system to obtain information and the information is fed to a controller that, through provided interfaces, acts on the system to alter its behavior. When a failure is detected, pinpointing the source of the failure is a critical step for a repair action. However, information obtained from a running system is commonly incomplete due to probing costs or unavailability of probes. In this paper we address the problem of fault localization in the presence of incomplete system monitoring. We may not be able to directly observe a component but we may be able to infer its health state. We provide formal criteria to determine when health states of unobservable components can be inferred and establish formal theoretical bounds for accuracy when using any spectrum-based fault localization algorithm.},
	urldate = {2021-10-29},
	booktitle = {Proceedings of the 9th {International} {Symposium} on {Software} {Engineering} for {Adaptive} and {Self}-{Managing} {Systems}},
	publisher = {Association for Computing Machinery},
	author = {Casanova, Paulo and Garlan, David and Schmerl, Bradley and Abreu, Rui},
	month = jun,
	year = {2014},
	keywords = {Diagnostics, Monitoring, Self-adaptive systems, unobserved},
	pages = {75--84},
}

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