Generating petri net-based behavioral models from textual use cases and application in railway networks

Zuohua Ding, Mingyue Jiang, Mengchu Zhou

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

A software system's requirements are often specified by textual use cases due to the latter's concrete and narrative style of expressions. However, they have limitation in the synthesis of the system behavior since they have a poor basis for the formal interpretation. Existing synthesis techniques are either largely manual or focus on the use case interactions. We present a framework from a model-based point of view to automatically synthesize system behavior from textual use cases to a Petri net model. The generated net model can well describe component module interactions and thus can be used to check the requirement properties. The function of Send-Railway-Emergency-Call of European Integrated Railway Radio Enhanced Network is used to show the proposed method. Moreover, the experimental results on a set of examples demonstrate the effectiveness of the proposed method.

Original languageEnglish (US)
Article number7471524
Pages (from-to)3330-3343
Number of pages14
JournalIEEE Transactions on Intelligent Transportation Systems
Volume17
Issue number12
DOIs
StatePublished - Dec 2016

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

Keywords

  • Petri net
  • Textual use case
  • model transformation
  • natural language processing
  • railway network

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