Patterns for identifying and structuring features from textual descriptions: An exploratory study

Research output: Contribution to journalConference articlepeer-review

Abstract

Software Product Line Engineering (SPLE) supports developing and managing families of similar software products, termed Software Product Lines (SPLs). An essential SPLE activity is variability modeling which aims at repre-senting the differences among the SPL's members. This is commonly done with feature diagrams - graph structures specifying the user visible characteristics of SPL's members and the dependencies among them. Despite the attention that feature diagrams attract, the identification of features and structuring them into feature diagrams remain challenging. In this study, we utilized Natural Language Processing (NLP) techniques in order to explore dif-ferent patterns for identifying and structuring features from textual descriptions. Such a catalog of patterns is important for both manually-created and automati-cally-generated feature diagrams.

Original languageEnglish
Pages (from-to)121-128
Number of pages8
JournalCEUR Workshop Proceedings
Volume1367
StatePublished - 2015
EventCAiSE 2015 Forum at the 27th International Conference on Advanced Information Systems Engineering, CAiSE 2015 - Stockholm, Sweden
Duration: 8 Jun 201512 Jun 2015

Keywords

  • Empirical evaluation
  • Feature diagrams
  • Natural language pro-cessing
  • Variability analysis

ASJC Scopus subject areas

  • Computer Science (all)

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