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Case-Based Reasoning for Autonomous Service Failure Diagnosis and Remediation in Software

Summary: Case-Based Reasoning for Autonomous Service
Failure Diagnosis and Remediation in Software
Stefania Montani and Cosimo Anglano
Dipartimento di Informatica, Universit`a del Piemonte Orientale, Alessandria, Italy
stefania.montani, cosimo.anglano@unipmn.it
Abstract. Self-healing, one of the four key properties characterizing Au-
tonomic Systems, aims to enable large-scale software systems delivering
complex services on a 24/7 basis to meet their goals without any human
intervention. Achieving self-healing requires the elicitation and main-
tenance of domain knowledge in the form of service failure diagnosis,
remediation strategy patterns, a task which can be overwhelming. Case-
Based Reasoning (CBR) is a lazy learning paradigm that largely reduces
this kind of knowledge acquisition bottleneck. Moreover, the application
of CBR for failure diagnosis and remediation in software systems appears
to be very suitable, as in this domain most errors are re-occurrences of
known problems. In this paper, we describe a CBR approach for provid-
ing large-scale, distributed software systems with self-healing capabili-
ties, and demonstrate the practical applicability of our methodology by
means of some experimental results on a real world application.


Source: Anglano, Cosimo - Dipartimento di Informatica, UniversitÓ del Piemonte Orientale "A. Avogadro"


Collections: Computer Technologies and Information Sciences