JCP 2013 Vol.8(5): 1127-1135 ISSN: 1796-203X
doi: 10.4304/jcp.8.5.1127-1135
doi: 10.4304/jcp.8.5.1127-1135
Static Analysis, Code Transformation and Runtime Profiling for Self-healing
Mohammad Muztaba Fuad, Debzani Deb and Jinsuk Baek
Department of Computer Science Winston-Salem State University, Winston-Salem, NC 27110, USA
Abstract—A self-healing application brings itself into a stable state after a failure put the software into an unstable state. For such self-healing software application, finding fix for a 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 aspect of computing. If failure scenarios come into existence, the user wants the runtime environment to handle those situations autonomically. This paper presents a new technique of finding self-healing actions by matching a fault scenario to already established fault models. By statically analyzing the code and transforming it in a way to allow the program to profile itself, it is possible to capture runtime parameters and execution pathways during runtime. The transformed program then can establish stable execution models that can be used later to match with an unstable execution scenario. Experimentation and results are presented that showed that even with additional overheads; this technique can prove beneficial for autonomically healing faults and reliving system administrators from repeated and routine troubleshooting situations.
Index Terms—Self-adaptive application, Autonomic computing, Code transformation, Fault similarity.
Abstract—A self-healing application brings itself into a stable state after a failure put the software into an unstable state. For such self-healing software application, finding fix for a 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 aspect of computing. If failure scenarios come into existence, the user wants the runtime environment to handle those situations autonomically. This paper presents a new technique of finding self-healing actions by matching a fault scenario to already established fault models. By statically analyzing the code and transforming it in a way to allow the program to profile itself, it is possible to capture runtime parameters and execution pathways during runtime. The transformed program then can establish stable execution models that can be used later to match with an unstable execution scenario. Experimentation and results are presented that showed that even with additional overheads; this technique can prove beneficial for autonomically healing faults and reliving system administrators from repeated and routine troubleshooting situations.
Index Terms—Self-adaptive application, Autonomic computing, Code transformation, Fault similarity.
Cite: Mohammad Muztaba Fuad, Debzani Deb and Jinsuk Baek, " Static Analysis, Code Transformation and Runtime Profiling for Self-healing," Journal of Computers vol. 8, no. 5, pp. 1127-1135, 2013.
General Information
ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
-
Nov 14, 2019 News!
Vol 14, No 11 has been published with online version [Click]
-
Mar 20, 2020 News!
Vol 15, No 2 has been published with online version [Click]
-
Dec 16, 2019 News!
Vol 14, No 12 has been published with online version [Click]
-
Sep 16, 2019 News!
Vol 14, No 9 has been published with online version [Click]
-
Aug 16, 2019 News!
Vol 14, No 8 has been published with online version [Click]
- Read more>>