Adaptable processes

We propose the concept of adaptable processes as a way of overcoming thelimitations that process calculi have for describing patterns of dynamic process evolution.Such patterns rely on direct ways of controlling the behavior and location of runningprocesses, and so they are at the heart of the adaptation capabilities present in manymodern concurrent systems. Adaptable processes have a location and are sensible toactions of dynamic update at runtime; this allows to express a wide range of evolvabilitypatterns for concurrent processes. We introduce a core calculus of adaptable processesand propose two verification problems for them: bounded and eventual adaptation. Whilethe former ensures that the number of consecutive erroneous states that can be traversedduring a computation is bound by some given number k, the latter ensures that if thesystem enters into a state with errors then a state without errors will be eventually reached.We study the (un)decidability of these two problems in several variants of the calculus,which result from considering dynamic and static topologies of adaptable processes aswell as different evolvability patterns. Rather than a specification language, our calculusintends to be a basis for investigating the fundamental properties of evolvable processesand for developing richer languages with evolvability capabilities.