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Variability Mining: Consistent Semi-automatic Detection of Product-Line Features

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3 Author(s)
Kastner, C. ; Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA ; Dreiling, A. ; Ostermann, K.

Software product line engineering is an efficient means to generate a set of tailored software products from a common implementation. However, adopting a product-line approach poses a major challenge and significant risks, since typically legacy code must be migrated toward a product line. Our aim is to lower the adoption barrier by providing semi-automatic tool support-called variability mining -to support developers in locating, documenting, and extracting implementations of product-line features from legacy code. Variability mining combines prior work on concern location, reverse engineering, and variability-aware type systems, but is tailored specifically for the use in product lines. Our work pursues three technical goals: (1) we provide a consistency indicator based on a variability-aware type system, (2) we mine features at a fine level of granularity, and (3) we exploit domain knowledge about the relationship between features when available. With a quantitative study, we demonstrate that variability mining can efficiently support developers in locating features.

Published in:

Software Engineering, IEEE Transactions on  (Volume:40 ,  Issue: 1 )