An increasingly important area of runtime monitoring is the incorporation of techniques for diagnosis and repair, for example, in autonomic control applications [9], in robotics, and in e-business process change [12]. In particular, a runtime monitor becomes a 'supervisor' - a process which not only monitors but may evolve the running system dynamically. In [4], a framework for the logical modelling of hierarchically structured supervised component systems was set out. The modelling captures the following key behavioural concepts: at runtime, a supervisory component can (i) monitor its supervisee to ensure conformance against desired behaviour, (ii) analyse reasons for non-conformance, should that arise, (iii) evolve its supervisee in a pre-programmed way following diagnosis, or via external stimulus received from higher-level supervisory components. Structurally, components may contain sub-components, actions over the state of the component, and programs over the actions. In this logical framework, components are specified by first-order logic theories. Actions are either basic revisions to the state of the component or combinations of actions. Crucially, a supervisory component is treated as a logical theory meta to its supervisee, thus providing access to all facets of the supervisee's structure. A supervisory component program is executed meta to its supervisee's program. Synchronisation between the two may occur through a variety of schemes, from lock-step synchronisation to asynchronous execution with defined synchronisation points. A supervisory program action may evolve its supervisee by making changes to its state, to its actions, to its sub-components, or to its program. This occurs in the logical framework via a theory change induced from the meta-level. © 2010 Springer-Verlag.
CITATION STYLE
Afifi, D., Rydeheard, D. E., & Barringer, H. (2010). ESAT: A tool for animating logic-based specifications of evolvable component systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6418 LNCS, pp. 469–474). https://doi.org/10.1007/978-3-642-16612-9_36
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