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Similarity mapping of software faults for self-healing applications

Published: 15 April 2010 Publication History

Abstract

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.

References

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Horn P., "Autonomic Computing: IBM's Perspective on the State of Information Technology", IBM Corporation, October 15, 2001.
[2]
Kephart J. O. and Chess D. M., "The Vision of Autonomic Computing", IEEE Computer, Vol. 36, No. 1, 2003.
[3]
Fuad, M. M., "Code Transformation Techniques and Management Architecture for Self-manageable Distributed Applications", Twentieth International Conference on Software Eng. and Knowledge Engineering, USA, 2008.
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Fuad, M. M. and Oudshoorn, M. J., "Transformation of Existing Programs into Autonomic and Self-healing Entities", 14th IEEE International Conference on the Engineering of Computer Based Systems, USA, 2007.
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Ding X., Huang H., Ruan Y., Shaikh A., and Zhang, X., "Automatic Software Fault Diagnosis by Exploiting Application Signatures", Proceedings of the 22nd Conference on Large installation System Administration Conference, USENIX Association, 2008.
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Yuan C., Lao N., Wen J., Li J., Zhang Z., Wang Y., and Ma W., "Automated Known Problem Diagnosis with Event Traces", SIGOPS Oper. Syst. Rev., Vol. 40, No. 4, 2006.
[7]
Cook, B. and Babu, S. and Candea, G. and Duan, S. Toward Self-Healing Multitier Services. Technical Report of the Duke University, 2005.
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Binkleya D., Feildb H., Lawriea D. and Pighinc M., "Increasing diversity: Natural language measures for software fault prediction", Journal of Systems and Software, Vol. 8, Issue 11, 2009.
[9]
Fuad M. M., "Issues and Challenges for an Inductive Learning Algorithm for Self-healing Applications", 7th International Conference on Information Technology: New Generation, Las Vegas, USA, April, 2010.
[10]
Java Platform Debugger Architecture, JPDA, http://java.sun.com/javase/technologies/core/toolsapis/jpda/

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cover image ACM Conferences
ACMSE '10: Proceedings of the 48th annual ACM Southeast Conference
April 2010
488 pages
ISBN:9781450300643
DOI:10.1145/1900008
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 April 2010

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Author Tags

  1. code transformation
  2. fault similarity
  3. self-healing

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  • Research-article

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ACM SE '10
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ACM SE '10: ACM Southeast Regional Conference
April 15 - 17, 2010
Mississippi, Oxford

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ACMSE '10 Paper Acceptance Rate 48 of 94 submissions, 51%;
Overall Acceptance Rate 502 of 1,023 submissions, 49%

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