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A framework for constructing semantically composable feature models from natural language requirements

Published: 24 August 2009 Publication History

Abstract

Software Product Line Engineering (SPLE) requires the construction of feature models from large, unstructured and heterogeneous documents, and the reliable derivation of product variants from the resulting model. This can be an arduous task when performed manually, and can be error-prone in the presence of a change in requirements. In this paper we introduce a tool suite which automatically processes natural-language requirements documents into a candidate feature model, which can be refined by the requirements engineer. The framework also guides the process of identifying variant concerns and their composition with other features. We also provide language support for specifying semantic variant feature compositions which are resilient to change. We show that feature models produced by this framework compare favourably with those produced by domain experts by application to a real-life industrial example.

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Cited By

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  • (2022)Sometimes you have to treat the symptoms: tackling model drift in an industrial clone-and-own software product lineProceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3540250.3558960(1355-1366)Online publication date: 7-Nov-2022
  • (2022)Variability-Aware Design of Space Systems: Variability Modelling, Configuration Workflow and Research DirectionsProceedings of the 16th International Working Conference on Variability Modelling of Software-Intensive Systems10.1145/3510466.3510472(1-10)Online publication date: 23-Feb-2022
  • (2020)Automated extraction of domain knowledge in practiceProceedings of the 24th ACM Conference on Systems and Software Product Line: Volume A - Volume A10.1145/3382025.3414968(1-11)Online publication date: 19-Oct-2020
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Published In

cover image ACM Other conferences
SPLC '09: Proceedings of the 13th International Software Product Line Conference
August 2009
319 pages

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Carnegie Mellon University

United States

Publication History

Published: 24 August 2009

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SPLC '09
SPLC '09: 13th International Software Product Line Conference
August 24 - 28, 2009
California, San Francisco, USA

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SPLC '09 Paper Acceptance Rate 30 of 82 submissions, 37%;
Overall Acceptance Rate 167 of 463 submissions, 36%

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Cited By

View all
  • (2022)Sometimes you have to treat the symptoms: tackling model drift in an industrial clone-and-own software product lineProceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3540250.3558960(1355-1366)Online publication date: 7-Nov-2022
  • (2022)Variability-Aware Design of Space Systems: Variability Modelling, Configuration Workflow and Research DirectionsProceedings of the 16th International Working Conference on Variability Modelling of Software-Intensive Systems10.1145/3510466.3510472(1-10)Online publication date: 23-Feb-2022
  • (2020)Automated extraction of domain knowledge in practiceProceedings of the 24th ACM Conference on Systems and Software Product Line: Volume A - Volume A10.1145/3382025.3414968(1-11)Online publication date: 19-Oct-2020
  • (2020)AMADEUSProceedings of the 24th ACM Conference on Systems and Software Product Line: Volume A - Volume A10.1145/3382025.3414952(1-12)Online publication date: 19-Oct-2020
  • (2019)Enabling automated requirements reuse and configurationSoftware and Systems Modeling (SoSyM)10.1007/s10270-017-0641-618:3(2177-2211)Online publication date: 1-Jun-2019
  • (2018)Feature and variability extraction from natural language software requirements specificationsProceedings of the 22nd International Systems and Software Product Line Conference - Volume 210.1145/3236405.3236427(72-78)Online publication date: 10-Sep-2018
  • (2018)Feature-based reuse in the ERP domainProceedings of the 22nd International Systems and Software Product Line Conference - Volume 110.1145/3233027.3233051(170-178)Online publication date: 10-Sep-2018
  • (2018)Reverse engineering variability from requirement documents based on probabilistic relevance and word embeddingProceedings of the 22nd International Systems and Software Product Line Conference - Volume 110.1145/3233027.3233033(121-131)Online publication date: 10-Sep-2018
  • (2018)An inductive learning perspective on automated generation of feature models from given product specificationsProceedings of the 22nd International Systems and Software Product Line Conference - Volume 110.1145/3233027.3233031(25-30)Online publication date: 10-Sep-2018
  • (2018)Extracting software product line feature models from natural language specificationsProceedings of the 22nd International Systems and Software Product Line Conference - Volume 110.1145/3233027.3233029(43-53)Online publication date: 10-Sep-2018
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