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Using the Options Analysis for Reengineering (OAR) Method for Mining Components for a Product Line

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Software Product Lines (SPLC 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2379))

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Abstract

The Options Analysis for Reengineering (OAR) method is a systematic, architecture-centric means for mining existing components for a product line or new software architecture. The method incorporates a set of scalable techniques and exercises to collaboratively analyze existing components, determine viable mining options, and evaluate the most promising options. The OAR method has 5 activities that are followed in a systematic manner to identify components for mining and estimate the cost and risk of changes required to each legacy component to enable its reuse within a new software architecture. The OAR method provides visibility into this highly complex analysis activity. It also provides insights into implicit stakeholder assumptions, constraints, and other major drivers that impact the mining of components. Results from a pilot application of the OAR method are presented in this paper.

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References

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Author information

Authors and Affiliations

  1. Software Engineering Institute, 4500 Fifth Avenue, Pittsburgh, PA, 15213

    Dennis Smith, Liam O’Brien & John Bergey

Authors
  1. Dennis Smith
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  2. Liam O’Brien
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  3. John Bergey
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Editor information

Editors and Affiliations

  1. Software Engineering Institute, Carnegie Mellon University, 4500 Fifth Avenue, Pittsburgh, PA, 15213, USA

    Gary J. Chastek

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© 2002 Springer-Verlag Berlin Heidelberg

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Smith, D., O’Brien, L., Bergey, J. (2002). Using the Options Analysis for Reengineering (OAR) Method for Mining Components for a Product Line. In: Chastek, G.J. (eds) Software Product Lines. SPLC 2002. Lecture Notes in Computer Science, vol 2379. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45652-X_20

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  • DOI: https://doi.org/10.1007/3-540-45652-X_20

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43985-1

  • Online ISBN: 978-3-540-45652-0

  • eBook Packages: Springer Book Archive

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