Dependability of service-oriented computing: time-probabilistic failure modelling
SERENE'12 Proceedings of the 4th international conference on Software Engineering for Resilient Systems
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Characterizing latent software faults is crucial to address dependability issues of current three-tier systems. A client should not have a misconception that a transaction succeeded, when in reality, it failed due to a silent error. We present a fault injection-based evaluation to characterize silent and non-silent software failures in a representative three-tier web service, one that mimics a day trading application widely used for benchmarking application servers. For failure characterization, we quantify distribution of silent and non-silent failures, and recommend low cost application-generic and application-specific consistency checks, which improve the reliability of the application. We inject three variants of null-call, where a callee returns null to the caller without executing business logic. Additionally, we inject three types of unchecked exceptions and analyze the reaction of our application. Our results show that 49% of error injections from null-calls result in silent failures, while 34% of unchecked exceptions result in silent failures. Our generic-consistency check can detect silent failures in null-calls with an accuracy as high as 100%. Non-silent failures with unchecked exceptions can be detected with an accuracy of 42% with our application-specific checks.