Context

Extracting conceptual models, e.g., entity relationship model or Business Process model, from software requirement document is an essential task in the software development life cycle. Business process model presents a clear picture of required system's functionality. Operations in business process model together with the data entity consumed, help the software developers to understand the database design and operations to be implemented. Researchers have been aiming at automatic extraction of these artefacts from the requirement document.

Objective

In this paper, we present an automated approach to extract the entity relationship and business process models from requirements, which are possibly in different formats such as general requirements, use case specification and user stories. Our approach is based on the efficient natural language processing techniques.

Method

It is an iterative approach of Models Extraction from the Requirements (iMER). iMER has multiple iterations where each iteration is to address a sub-problem. In the first iteration, iMER extracts the data entities and attributes. Second iteration is to find the relationships between data entities, while extracting cardinalities is in the third step. Business process model is generated in the fourth iteration, containing the external (actors’) and internal (system's) operations.

Evaluation

To evaluate the performance and accuracy of iMER, experiments are conducted on various formats of the requirement documents. Additionally, we have also evaluated our approaches using the requirement documents which been modified by shuffling the sentences and by merging with other requirements. Comparative study is also performed. The preliminary results show a noticeable improvement.

Conclusion

The iMER is an efficient automated iterative approach that is able to extract the conceptual models from the various formats of requirements.

中文翻译：

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iMER：实体关系的迭代过程和从需求中提取业务流程模型

语境

从软件需求文档中提取概念模型，例如实体关系模型或业务流程模型，是软件开发生命周期中的一项基本任务。业务流程模型清晰地显示了所需系统的功能。业务流程模型中的操作以及所使用的数据实体有助于软件开发人员了解数据库设计和要实现的操作。研究人员一直致力于从需求文件中自动提取这些伪像。

客观的

在本文中，我们提出了一种自动方法，用于从需求中提取实体关系和业务流程模型，这些需求可能采用不同的格式，例如一般需求，用例规范和用户案例。我们的方法基于高效的自然语言处理技术。

方法

它是从需求（iMER）中提取模型的一种迭代方法。iMER具有多个迭代，其中每个迭代都将解决一个子问题。在第一次迭代中，iMER提取数据实体和属性。第二步是查找数据实体之间的关系，而提取基数是第三步。业务流程模型是在第四次迭代中生成的，其中包含外部（参与者）和内部（系统）操作。

评估

为了评估iMER的性能和准确性，对需求文档的各种格式进行了实验。此外，我们还使用了需求文档评估了我们的方法，需求文档通过改组句子并与其他需求合并而进行了修改。还进行了比较研究。初步结果显示出明显的改善。

结论

iMER是一种高效的自动化迭代方法，能够从各种需求格式中提取概念模型。