Modeling Systemic Behavior by State-Based Holonic Modular Units Luca Pazzi University of Modena and Reggio Emilia DIEF-UNIMORE Via Vignolese 905, I-41125 Modena, Italy luca.pazzi@unimore.it Abstract. The paper explores a vision in modeling the behavior of com- plex systems by modular units hosting state machines arranged in part- whole hierarchies and communicating through event flows. Each modular unit plays at the same time the double role of part and whole, i.e. it is inspired by the philosophical idea of holon, providing both an interface and an implementation by which other component state machines may be controlled in order to achieve a global behavior. It is moreover observed that it is possible to assign a formal characterization to such state mod- ules, due to their part-whole arrangement, since higher-level behaviors can derive formally their meaning from lower-level component behaviors. Such a way of arranging behavioral modules allows to establish directly correct-by-construction safety and liveness properties of state-based sys- tems thus challenging the current approach by which state machines interact at the same level and have to be model-checked for ensuring correctness. Keywords: state-based modeling, holons, component-based modeling, model checking, correctness by construction. 1 Introduction Holons, in the terminology of Arthur Koestler in his 1967 book The Ghost in the Machine [1] are entities which are, at the same time, both parts and wholes. Ac- cordingly, complex phenomena and entities can be decomposed into part/whole hierarchies, named holarchies, with holon nodes at each level. The main interest in the holonic approach lies in the fact that it reconciles both the reductionist and the holistic view in systems analysis. By the reductionistic view, which dates back to Descartes and is sometimes referred to as divide and conquer or more formally analytic reduction, a com- plex system can be analyzed by “reduction” into distinct parts so that they can be analysed separately. Such decomposition allows to deal effectively with systems complexity, by recursively confining it into less complex and distinct parts, namely subsystems. In order to be effective, analytic reduction implies the In Proceedings of: ACM/IEEE Model Driven Engineering Languages and Systems, 17th International Conference, MODELS 2014, Valencia, Spain, September 28 - October 3, 2014.