一句话：提出基于搜索的 OCL 约束自动重构方法，以提升约束的可理解性与可维护性。
OCL 约束用于为 UML 模型提供精确语义；当约束频繁演化时，其可理解性与可维护性至关重要。以癌症登记为例，为确保癌症数据质量，定义了一千余条并定期演化的医学规则，这些规则可用 OCL 表示。本文针对 OCL 约束提出自动化重构方法，标题表明其利用搜索技术来寻找重构方案，以改善约束的可理解性与可维护性。摘要未给出具体算法细节、工具实现或实验评估，主要贡献在于将该问题置于 OCL/UML 模型演化与医学规则维护背景下，并提出自动重构方向。
Object Constraint Language (OCL) constraints are typically used for providing precise semantics to models developed with the Unified Modeling Language (UML). When OCL constraints evolve in a regular basis, it is essential that they are easy to understand and maintain. For instance, in cancer registries, to ensure the quality of cancer data, more than one thousand medical rules are defined and evolve regularly. Such rules can be specified with OCL. It is, therefore, important to ensure the understandability and maintainability of medical rules specified with OCL.
DOI 原文 ·
@inproceedings{paperbot4425,
title = {Automated refactoring of OCL constraints with search},
author = {Hong Lu and Shuai Wang and Tao Yue and Shaukat Ali and Jan F. Nygård},
booktitle = {ICSE},
year = {2018},
doi = {10.1145/3180155.3182546}
}