FAULT INJECTION TECHNIQUES AND TOOLS

Citation
Mc. Hsueh et al., FAULT INJECTION TECHNIQUES AND TOOLS, Computer, 30(4), 1997, pp. 75
Citations number
10
Categorie Soggetti
Computer Sciences","Computer Science Hardware & Architecture","Computer Science Software Graphycs Programming
Journal title
ISSN journal
00189162
Volume
30
Issue
4
Year of publication
1997
Database
ISI
SICI code
0018-9162(1997)30:4<75:FITAT>2.0.ZU;2-K
Abstract
Dependability evaluation involves the study of failures and errors. Th e destructive nature of a crash and long error latency make it difficu lt to identify the causes of failures in the operational environment. It is particularly hard to recreate a failure scenario for a large, co mplex system. To identify and understand potential failures, the autho rs use an experiment-based approach for studying system dependability. This approach is applied during the conception, design, prototype, an d operational phases. To take an experiment-based approach, you must f irst understand a system's architecture, structure, and behavior. You need to know its tolerance for faults and failures, including its buil tin detection and recovery mechanisms, and you need specific instrumen ts and tools to inject faults, create failures or errors, and monitor their effects. Engineers most often use low-cost, simulation-based fau lt injection to evaluate the dependability of a system that is in the conceptual and design phases. At this point, the system under study is only a series of high-level abstractions; implementation details have yet to be determined. Thus the system is simulated on the basis of si mplified assumptions. Simulation-based fault injection, which assumes that errors or failures occur according to predetermined distribution, is useful for evaluating the effectiveness of fault-tolerant mechanis ms and a system's dependability; it does provide timely feedback to sy stem engineers. However, it requires accurate input parameters, which are difficult to supply: Design and technology changes often complicat e the use of past measurements. Testing a prototype, on the other hand , allows you to evaluate the system without any assumptions about syst em design. Instead of injecting faults, engineers can directly measure operational systems as they handle real workloads. Measurement-based analysis uses actual data, which contains much information about natur ally occurring errors and failures and sometimes about recovery attemp ts. Although these three experimental methods have limitations, their unique values complement one another and allow for a wide spectrum of dependability studies.