TY - JOUR
T1 - The invariant refinement method
AU - Bureš, Tomáš
AU - Gerostathopoulos, Ilias
AU - Hnetynka, Petr
AU - Keznikl, Jaroslav
AU - Kit, Michal
AU - Plasil, Frantisek
PY - 2015/1/1
Y1 - 2015/1/1
N2 - The chapter describes IRM, a method that guides the design of smart-cyber physical systems that are built according to the autonomic service-component paradigm. IRM is a requirements-oriented design method that focuses on distributed collaboration. It relies on the invariant concept to model both high-level system goals and low-level software obligations. In IRM, high-level invariants are iteratively decomposed into more specific sub-invariants up to the level that they can be operationalized by autonomous components and component collaborations (ensembles). We present the main concepts behind the method, as well the main decomposition patterns that back up the design process, and illustrate them in the ASCENS e-mobility case study.
AB - The chapter describes IRM, a method that guides the design of smart-cyber physical systems that are built according to the autonomic service-component paradigm. IRM is a requirements-oriented design method that focuses on distributed collaboration. It relies on the invariant concept to model both high-level system goals and low-level software obligations. In IRM, high-level invariants are iteratively decomposed into more specific sub-invariants up to the level that they can be operationalized by autonomous components and component collaborations (ensembles). We present the main concepts behind the method, as well the main decomposition patterns that back up the design process, and illustrate them in the ASCENS e-mobility case study.
KW - Dependability
KW - Self-adaptivity
KW - System design
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M3 - Article
AN - SCOPUS:84924402246
SN - 0302-9743
VL - 8998
SP - 405
EP - 428
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -