Efficient compensation handling via subjective updates

Abstract

© 2017 Copyright held by the owner/author(s). Programming abstractions for compensation handling and dynamic update are crucial in specifying reliable interacting systems, such as Collective Adaptive Systems (CAS). Compensations and updates both specify how a system reacts in response to exceptional events. Prior work showed that different semantics for compensation handling can be encoded into a calculus of adaptable processes with objective updates, in which a process is reconfigured by its context. This paper goes further by considering subjective updates, in which, intuitively, a process reconfigures itself. A calculus of adaptable processes with subjective update its introduced, and its expressivity is assessed by encoding two semantics for compensation handling. The resulting encodings are more efficient than those using objective updates: they require less computational steps.