Declarative process model translation and text generation

Workflow technology is a hot topic in the field of service computing. Due to the traditional imperative business process models tending toward strict sequential logic, they can not accommodate users' ambiguous requirements, resulting in high complexity in process modeling and maintenance costs. To simplify modeling and maintenance costs and improve the flexibility of process models, rule-based declarative business process modeling methods have been proposed. While, declarative process models are syntactically more difficult to understand, which creates communication barriers between business analysts and modelers. Moreover, due to the emphasis on business rules and conditions rather than specific execution sequences in declarative business process models, directly describing declarative models may not facilitate users' understanding of the specific flow between nodes. In this paper, we first implement a technique for converting declarative models into sequential natural language text. Based on realistic reasoning, we transform the declarative model into an intermediate state imperative model with sequential logic through algorithmic analysis, thereby generating sequential natural language text that conforms to the user's reading habits. This design amalgamates the benefits of declarative process modeling flexibility and textual legibility, to some extent eliminating communication barriers between modelers and domain experts, and improving the efficiency of requirement analysis and verification.