Detecting Silent Data Corruptions in Aerospace-Based Computing Using Program Invariants
Joint Authors
Ma, Junchi
Yu, Dengyun
Wang, Yun
Cai, Zhenbo
Zhang, Qingxiang
Hu, Cheng
Source
International Journal of Aerospace Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-11-15
Country of Publication
Egypt
No. of Pages
10
Abstract EN
Soft error caused by single event upset has been a severe challenge to aerospace-based computing.
Silent data corruption (SDC) is one of the results incurred by soft error.
SDC occurs when a program generates erroneous output with no indications.
SDC is the most insidious type of results and very difficult to detect.
To address this problem, we design and implement an invariant-based system called Radish.
Invariants describe certain properties of a program; for example, the value of a variable equals a constant.
Radish first extracts invariants at key program points and converts invariants into assertions.
It then hardens the program by inserting the assertions into the source code.
When a soft error occurs, assertions will be found to be false at run time and warn the users of soft error.
To increase the coverage of SDC, we further propose an extension of Radish, named Radish_D, which applies software-based instruction duplication mechanism to protect the uncovered code sections.
Experiments using architectural fault injections show that Radish achieves high SDC coverage with very low overhead.
Furthermore, Radish_D provides higher SDC coverage than that of either Radish or pure instruction duplication.
American Psychological Association (APA)
Ma, Junchi& Yu, Dengyun& Wang, Yun& Cai, Zhenbo& Zhang, Qingxiang& Hu, Cheng. 2016. Detecting Silent Data Corruptions in Aerospace-Based Computing Using Program Invariants. International Journal of Aerospace Engineering،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1105042
Modern Language Association (MLA)
Ma, Junchi…[et al.]. Detecting Silent Data Corruptions in Aerospace-Based Computing Using Program Invariants. International Journal of Aerospace Engineering No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1105042
American Medical Association (AMA)
Ma, Junchi& Yu, Dengyun& Wang, Yun& Cai, Zhenbo& Zhang, Qingxiang& Hu, Cheng. Detecting Silent Data Corruptions in Aerospace-Based Computing Using Program Invariants. International Journal of Aerospace Engineering. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1105042
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1105042