Communicating X-machines: From theory to practice

Petros Kefalas, George Eleftherakis, Evangelos Kehris

Research output: Chapter in Book/Report/Conference proceedingChapter

6 Scopus citations

Abstract

Formal modeling of complex systems is a non-trivial task, especially if a formal method does not facilitate separate development of the components of a system. This paper describes a methodology of building communicating X-machines from existing stand-alone X-machine models and presents the theory that drives this methodology. An X-machine is a formal method that resembles a finite state machine but can model non-trivial data structures. This is accomplished by incorporating a typed memory tuple into the model as well as transitions labeled with functions that operate on inputs and memory values. A set of X-machines can exchange messages with each other, thus building a communicating system model. However, existing communicating X-machines theories imply that the components of a communicating system should be built from scratch. We suggest that modeling of complex systems can be split into two separate and distinct activities: (a) the modeling of standalone X-machine components and (b) the description of the communication between these components. This approach is based on a different view of the theory of communicating X-machines and it leads towards disciplined, practical, and modular development. The proposed methodology is accompanied by an example, which demonstrates the use of communicating X-machines towards the modeling of large-scale systems.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsYannis Manolopoulos, Skevos Evripidou, Antonis C. Kakas
PublisherSpringer Verlag
Pages316-335
Number of pages20
ISBN (Print)9783540075448
DOIs
StatePublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2563
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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