Proceedings of the Symposium on Applied Computing 2017
DOI: 10.1145/3019612.3019625
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Efficient compensation handling via subjective updates

Abstract: 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 upda… Show more

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Cited by 1 publication
(5 citation statements)
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References 15 publications
(45 reference statements)
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“…Origin of the results. This paper distills, improves, and collects preliminary results from our papers [9] and [10]. While in [9] we studied encodings into adaptable processes with objective updates, in [10] we studied encodings into adaptable processes with subjective updates, and compared them against those in [9].…”
Section: Contributionsmentioning
confidence: 99%
See 4 more Smart Citations
“…Origin of the results. This paper distills, improves, and collects preliminary results from our papers [9] and [10]. While in [9] we studied encodings into adaptable processes with objective updates, in [10] we studied encodings into adaptable processes with subjective updates, and compared them against those in [9].…”
Section: Contributionsmentioning
confidence: 99%
“…This paper distills, improves, and collects preliminary results from our papers [9] and [10]. While in [9] we studied encodings into adaptable processes with objective updates, in [10] we studied encodings into adaptable processes with subjective updates, and compared them against those in [9]. A main difference between [9,10] and the current paper is that here we concentrate on a specific source calculus, namely the calculus in [15] with static recovery and discarding semantics.…”
Section: Contributionsmentioning
confidence: 99%
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