In this novel approach, the Arabic user requirements are parsed using a natural language processing tool called MADA+TOKAN to generate the Part Of Speech (POS) tags of the parsed user requirements, then a set of heuristics are applied on the resulted tags to obtain the sequence diagram components objects, messages and work flow transitions (messages). We evaluated the technique with more than 1,400 user stories from 22 backlogs and show that (a) the technique generates syntactically valid robustness diagrams, and (b) the quality of automatically generated robustness diagrams compares to the quality of diagrams created by human experts, but depends on the quality of the textual user stories.Ī new semi-automated approach for generating sequence diagrams from Arabic user requirements is presented. The technique utilises natural language processing and rule-based transformations. Moreover, the technique supports "viewpoint-based" diagrams, i.e., diagrams that show relationships between actors, domain entities and user interfaces starting from a diagram element (e.g., an actor) selected by the analyst. In addition to creating diagrams for individual stories, the technique allows combining diagrams of multiple stories into one diagram to visualise workflows within sets of stories (e.g., a backlog). This paper proposes a technique to automatically transform textual user stories into visual use case scenarios in the form of robustness diagrams (a semi-formal scenario-based visualisation of workflows).
#Eclipse sequence diagram plugin software#
This makes it hard to (a) maintain user stories and backlogs, (b) fully understand the scope of a software project without a detailed analysis of the backlog, and (c) analyse how user stories impact design decisions during sprint planning and implementation. However, user stories are typically rather short and backlogs can include many stories. Textual user stories capture interactions of users with the system as high-level requirements.
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