An approach for decision support on the uncertainty in feature model evolution

L.M.S. Tran; F. Massacci

doi:10.1109/RE.2014.6912251

An approach for decision support on the uncertainty in feature model evolution

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

© 2014 IEEE.Software systems could be seen as a hierarchy of features which are evolving due to the dynamic of the working environments. The companies who build software thus need to make an appropriate strategy, which takes into consideration of such dynamic, to select features to be implemented. In this work, we propose an approach to facilitate such selection by providing a means to capture the uncertainty of evolution in feature models. We also provide two analyses to support the decision makers. The approach is exemplified in the Smart Grid scenario.

Original language	English
Title of host publication	2014 IEEE 22nd International Requirements Engineering Conference, RE 2014 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	93-102
ISBN (Print)	9781479930333
DOIs	https://doi.org/10.1109/RE.2014.6912251
Publication status	Published - 26 Sept 2014
Externally published	Yes
Event	2014 IEEE 22nd International Requirements Engineering Conference, RE 2014 - Karlskrona, Sweden Duration: 25 Aug 2014 → 29 Aug 2014

Conference

Conference	2014 IEEE 22nd International Requirements Engineering Conference, RE 2014
Country/Territory	Sweden
City	Karlskrona
Period	25/08/14 → 29/08/14

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10.1109/RE.2014.6912251

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title = "An approach for decision support on the uncertainty in feature model evolution",

abstract = "{\textcopyright} 2014 IEEE.Software systems could be seen as a hierarchy of features which are evolving due to the dynamic of the working environments. The companies who build software thus need to make an appropriate strategy, which takes into consideration of such dynamic, to select features to be implemented. In this work, we propose an approach to facilitate such selection by providing a means to capture the uncertainty of evolution in feature models. We also provide two analyses to support the decision makers. The approach is exemplified in the Smart Grid scenario.",

author = "L.M.S. Tran and F. Massacci",

year = "2014",

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doi = "10.1109/RE.2014.6912251",

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pages = "93--102",

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Tran, LMS & Massacci, F 2014, An approach for decision support on the uncertainty in feature model evolution. in 2014 IEEE 22nd International Requirements Engineering Conference, RE 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., pp. 93-102, 2014 IEEE 22nd International Requirements Engineering Conference, RE 2014, Karlskrona, Sweden, 25/08/14. https://doi.org/10.1109/RE.2014.6912251

An approach for decision support on the uncertainty in feature model evolution. / Tran, L.M.S.; Massacci, F.
2014 IEEE 22nd International Requirements Engineering Conference, RE 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. p. 93-102.

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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M3 - Conference contribution

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T2 - 2014 IEEE 22nd International Requirements Engineering Conference, RE 2014

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ER -

An approach for decision support on the uncertainty in feature model evolution

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