• DocumentCode
    2307041
  • Title

    Scenario Analysis: Generation of Possible Scenario Interpretations and their Visualization

  • Author

    Kof, Leonid

  • Author_Institution
    Fak. fur Inf., Tech. Univ. Munchen, Garching, Germany
  • fYear
    2009
  • fDate
    1-1 Sept. 2009
  • Firstpage
    21
  • Lastpage
    30
  • Abstract
    Natural language is the main presentation means in industrial requirements documents. In such documents, system behavior is mostly specified in the form of scenarios, with every scenario written as a sequence of sentences in natural language. The scenarios are often incomplete: For the authors of requirements documents some facts are so obvious that they forget to mention them; this surely causes problems for the requirements analyst. In our previous work we developed an approach to translate textual scenarios to message sequence charts (MSCs). In order that the produced MSCs can be used for further development, they must be validated: i.e., for each MSC we have to say whether it really represents a possible system behavior, and whether the textual scenario was correctly interpreted. In the presented paper we suggest an approach to visualize different interpretations for the same scenario. For visualized scenarios, the user can decide, which of them represent allowed system behavior. This allows, in turn, to generalize exemplary scenarios to universal specifications. Applicability of the presented approach was confirmed in a case study.
  • Keywords
    natural language processing; text analysis; industrial requirements document; message sequence charts; natural language processing; possible scenario interpretations generation; scenario analysis; textual scenarios translation; Design engineering; Electronic mail; Error correction; Ignition; Instruments; Natural languages; Terminology; Turning; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Requirements Engineering Visualization (REV), 2009 Fourth International Workshop on
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    978-1-4244-7697-8
  • Electronic_ISBN
    978-0-7695-4104-4
  • Type

    conf

  • DOI
    10.1109/REV.2009.5
  • Filename
    5460243