Abstract

Objective The goal of this study is to identify gaps and challenges related to cross-domain model management focusing on consistency checking. Method We conducted a systematic literature review. We used the keyword-based search on Google Scholar, and we identified 618 potentially relevant studies; after applying inclusion and exclusion criteria, 96 papers were selected for further analysis. Results The main findings/contributions are: (i) a list of available tools used to support model management; (ii) 40% of the tools can provide consistency checking on models of different domains and 25% on models of the same domain, and 35% do not provide any consistency checking; (iii) available strategies to keep the consistency between models of different domains are not mature enough; (iv) most of the tools that provide consistency checking on models of different domains can only capture up to two inconsistency types; (v) the main challenges associated with tools that manage models on different domains are related to interoperability between tools and the consistency maintenance. Conclusion The results presented in this study can be used to guide new research on maintaining the consistency between models of different domains. Example of further research is to investigate how to capture the Behavioral and Refinement inconsistency types. This study also indicates that the tools should be improved in order to address, for example, more kinds of consistency check.

Highlights

  • Inconsistencies can cause catastrophic events: e.g., the NASA unmanned MARS Climate Orbiter [101] was destroyed in 1999 due to use of inconsistent metric units by design teams, and Airbus had 6 billion dollar loss in 2006 due to use of inconsistent specifications in different versions of design tools [114].Inconsistencies can be found in several stages of the system development life cycle

  • We provide a list of available tools used to support model management

  • We observe that 40% of the tools we found can provide consistency model checking on models from different domains, 25% on the models of the same domain, and 35% do not provide any consistency model checking

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Summary

Introduction

Inconsistencies can cause catastrophic events: e.g., the NASA unmanned MARS Climate Orbiter [101] was destroyed in 1999 due to use of inconsistent metric units by design teams, and Airbus had 6 billion dollar loss in 2006 due to use of inconsistent specifications in different versions of design tools [114].Inconsistencies can be found in several stages of the system development life cycle. It is known that systems are becoming increasingly complex to develop, especially when these systems are heterogeneous and there is a need to combine models created by engineers from different expertise and different domains [6,7,40,125,144]. One example of such a complex system is a mechatronic component: to develop it, one might need to combine expertise from different engineering domains such as mechanics, electronics and software [124]

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