The Vision of Autonomic Computing
Computer
Automated known problem diagnosis with event traces
Proceedings of the 1st ACM SIGOPS/EuroSys European Conference on Computer Systems 2006
Transformation of Existing Programs into Autonomic and Self-healing Entities
ECBS '07 Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems
Automatic software fault diagnosis by exploiting application signatures
LISA'08 Proceedings of the 22nd conference on Large installation system administration conference
Increasing diversity: Natural language measures for software fault prediction
Journal of Systems and Software
Issues and Challenges of an Inductive Learning Algorithm for Self-Healing Applications
ITNG '10 Proceedings of the 2010 Seventh International Conference on Information Technology: New Generations
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For self-healing software application, finding fix for a previously unseen fault is a grand challenge. Asking the user to provide fixes for every fault is bad for productivity, especially when the users are non-savvy in technical computing. If failure scenarios come into existence, the user wants the runtime environment to handle those situations autonomically. This paper proposes a new technique of matching unknown fault scenarios to already established fault models. By capturing runtime parameters and execution pathways, stable execution models are established and later are used to match with an unstable execution scenario. All these support is provided transparently and the added functionalities are incorporated into existing user application by using appropriate code transformation techniques. Initial results from experimentation show signs of promise and to be successful in providing transparent self-healing support to end user.