Adaptable processes (extended abstract)

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Abstract

We propose the concept of adaptable processes as a way of overcoming the limitations that process calculi have for describing patterns of dynamic process evolution. Such patterns rely on direct ways of controlling the behavior and location of running processes, and so they are at the heart of the adaptation capabilities present in many modern concurrent systems. Adaptable processes have a location and are sensible to actions of dynamic update at runtime. This allows to express a wide range of evolvability patterns for processes. We introduce a core calculus of adaptable processes and propose two verification problems for them: bounded and eventual adaptation. While the former ensures that at most k consecutive errors will arise in future states, the latter ensures that if the system enters into an error state then it will eventually reach a correct state. We study the (un)decidability of these two problems in different fragments of the calculus. Rather than a specification language, our calculus intends to be a basis for investigating the fundamental properties of evolvable processes and for developing richer languages with evolvability capabilities. © 2011 IFIP International Federation for Information Processing.

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Bravetti, M., Di Giusto, C., Pérez, J. A., & Zavattaro, G. (2011). Adaptable processes (extended abstract). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6722 LNCS, pp. 90–105). https://doi.org/10.1007/978-3-642-21461-5_6

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