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.

目的 这项研究的目的是确定与跨域模型管理相关的差距和挑战，重点是一致性检查。方法 我们进行了系统的文献综述。我们在Google学术搜索上使用了基于关键字的搜索，并确定了618项可能相关的研究；在应用纳入和排除标准后，选择了96篇论文进行进一步分析。结果 主要发现/贡献是：（i）用于支持模型管理的可用工具列表；（ii）40％的工具可以对不同域的模型进行一致性检查，而25％可以对相同域的模型进行一致性检查，而35％的工具不提供任何一致性检查；（iii）保持不同领域模型之间一致性的可用策略还不够成熟；（iv）大多数提供不同域模型一致性检查的工具最多只能捕获两种不一致类型；（v）与管理不同域上的模型的工具相关的主要挑战与工具之间的互操作性和一致性维护有关。结论 本研究中提出的结果可用于指导有关维持不同领域模型之间一致性的新研究。进一步研究的例子是研究如何捕获行为和细化不一致类型。这项研究还表明，应改进工具，以解决例如更多种一致性检查问题。