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A Survey of Feature Location Techniques

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Domain Engineering

Abstract

Feature location techniques aim at locating software artifacts that implement a specific program functionality, a.k.a. a feature. These techniques support developers during various activities such as software maintenance, aspect- or feature-oriented refactoring, and others. For example, detecting artifacts that correspond to product line features can assist the transition from unstructured to systematic reuse approaches promoted by software product line engineering (SPLE). Managing features, as well as the traceability between these features and the artifacts that implement them, is an essential task of the SPLE domain engineering phase, during which the product line resources are specified, designed, and implemented. In this chapter, we provide an overview of existing feature location techniques. We describe their implementation strategies and exemplify the techniques on a realistic use-case. We also discuss their properties, strengths, and weaknesses and provide guidelines that can be used by practitioners when deciding which feature location technique to choose. Our survey shows that none of the existing feature location techniques are designed to consider families of related products and only treat different products of a product line as individual, unrelated entities. We thus discuss possible directions for leveraging SPLE architectures in order to improve the feature location process.

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Notes

  1. 1.

    http://freemind.sourceforge.net.

  2. 2.

    We denote features by italic font, place natural language queries “in quotes,” and denote code elements by a monospaced font.

  3. 3.

    These are not to be confused with the extension and intension of a feature.

  4. 4.

    Several approaches, e.g., [4, 9], address the problem of input query definition. They consider not only the query but also related terms when evaluating the document models. As discussed earlier, these approaches are out of the scope of this chapter.

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Author information

Authors and Affiliations

  1. IBM Research, Haifa, Israel

    Julia Rubin

  2. University of Toronto, Toronto, Canada

    Julia Rubin & Marsha Chechik

Authors
  1. Julia Rubin
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  2. Marsha Chechik
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Correspondence to Julia Rubin .

Editor information

Editors and Affiliations

  1. Department of Information Systems, University of Haifa, Haifa, Israel

    Iris Reinhartz-Berger

  2. Ben-Gurion University of the Negev Dept. Information Systems Engineering, Beer-Sheva, Israel

    Arnon Sturm

  3. Business Information Systems, Middlesex University, London, United Kingdom

    Tony Clark

  4. Software Engineering Institute, Pittsburgh, Pennsylvania, USA

    Sholom Cohen

  5. S23M, Melbourne, Victoria, Australia

    Jorn Bettin

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Rubin, J., Chechik, M. (2013). A Survey of Feature Location Techniques. In: Reinhartz-Berger, I., Sturm, A., Clark, T., Cohen, S., Bettin, J. (eds) Domain Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36654-3_2

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  • DOI: https://doi.org/10.1007/978-3-642-36654-3_2

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  • Online ISBN: 978-3-642-36654-3

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