Similarity mapping of software faults for self-healing applications
Proceedings of the 48th Annual Southeast Regional Conference
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Day-to-day maintenance of software systems is a grand challenge due to the fact that the runtime environment changes continuously and the application can behave completely differently because of that. Users of such systems want to run their application and do not want to worry about the mundane task of system management in the face of a failure. If such management scenarios come into existence, the user wants the runtime environment to handle those situations autonomically. The user is more concerned with timely execution of their computation and production of intended results. Without expert technical help, average users have extreme difficulty managing such failure scenarios. This paper investigates the usability of explanation based learning algorithm with inductive rules to provide adaptive management of user application in the face of faults. A distributed algorithm is proposed that collects runtime program traces and signatures and combines all distributed copies to derive the domain knowledge for the learning algorithm.