Event-B has been attracting much interest because it supports a flexible refinement mechanism that reduces the complexity of constructing and verifying models of complicated target systems by taking into account multiple abstraction layers of the models. Although most previous studies on Event-B focused on model construction, the constructed models need to be maintained. Moreover, parts of existing models are often reused to construct other models. In this paper, a method is introduced that improves the maintainability and reusability of existing Event-B models. It automatically reconstructs the refinement structure of existing models by constructing models about different sets of variables than that used in the original models, while maintaining the consistencies checked in the original models. The method automatically decomposes each refinement step into multiple steps by taking certain predicates from existing models and deriving additional predicates from the consistency conditions of existing models to create new models consistent with the original ones. By combining the decomposing of refinement steps with the composing of refinement steps, this method automatically restructures a refinement step in accordance with given sets of variables to be taken into account in refinement steps of the refactored models. The results of case studies in which large refinement steps in existing models were decomposed and existing models were restructured to extract reusable parts for constructing other models demonstrated that the proposed method facilitates effective use of the refinement mechanism of Event-B.

中文翻译：

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Event-B 模型中细化结构的保持一致性重构

Event-B 之所以引起很多兴趣，是因为它支持灵活的细化机制，通过考虑模型的多个抽象层来降低构建和验证复杂目标系统模型的复杂性。尽管以前关于 Event-B 的大多数研究都集中在模型构建上，但构建的模型需要维护。此外，现有模型的一部分经常被重用于构建其他模型。本文介绍了一种提高现有 Event-B 模型的可维护性和可重用性的方法。它通过构建与原始模型中使用的变量集不同的模型来自动重建现有模型的细化结构，同时保持原始模型中检查的一致性。该方法通过从现有模型中获取某些谓词并从现有模型的一致性条件中派生额外的谓词来创建与原始模型一致的新模型，从而自动将每个细化步骤分解为多个步骤。通过将细化步骤的分解与细化步骤的组合相结合，该方法根据重构模型的细化步骤中要考虑的给定变量集自动重构细化步骤。分解现有模型中的大细化步骤并重组现有模型以提取可重用部分以构建其他模型的案例研究结果表明，所提出的方法有助于有效利用 Event-B 的细化机制。