Exploiting assumption-based verification for the adaptation of service-based applications

Service-based applications (SBAs) need to operate in a highly dynamic world, in which their constituent services could fail or become unavailable. Monitoring is typically used to identify such failures and, if needed, to trigger an adaptation of the SBA to compensate for those failures. However, existing monitoring approaches exhibit several limitations: (1) Monitoring individual services can uncover failures of services. Yet, it remains open whether those individual failures lead to a violation of the SBA's requirements, which would necessitate an adaptation. (2) Monitoring the SBA can uncover requirements deviations. However, it will not provide information about the failures leading to this deviation, which constitutes important information needed for the adaptation activities. Even a combination of (1) and (2) is limited. For instance, a requirements deviation will only be identified after it has occurred, e. g., after the execution of the whole SBA, which then in case of failures might require costly compensation actions. In this paper we introduce an approach that addresses those limitations by augmenting monitoring techniques for individual services with formal verification techniques. The approach explicitly encodes assumptions that the constituent services of an SBA will perform as expected. Based on those assumptions, formal verification is used to assess whether the SBA requirements are satisfied and whether a violation of those assumptions during run-time leads to a violation of the SBA requirements. Thereby, our approach allows for (a) pro-actively deciding whether the SBA requirements will be violated based on monitored failures, and (b) identifying the specific root cause for the violated requirements.