Information retrieval based feature analysis for product line
adoption in 4GL systems
András Kicsi, László Vidács, Árpád
Beszédes, Ferenc Kocsis and István Kovács
New customers often require custom features of a
successfully marketed product. As the number of variants grow, new
challenges arise in the maintenance and evolution activities.
Software product line (SPL) architecture is a timely answer to
these challenges. The SPL adoption however is a large one time
investment that affects both technical and organizational issues.
From the program code point of view, the extractive approach is
appropriate when there are already several product variants.
Analyzing the feature structure, the differences and commonalities
of the variants lead to the new common architecture. In this work
in progress paper we report initial experiments of feature
extraction from a set of product variants written in the Magic
fourth generation language (4GL). Since existing approaches are
mostly designed for mainstream languages, we adapted and reused
reverse engineering approaches to the 4GL environment. We followed
a semi-automatic feature extraction method, where the higher level
features are provided by domain experts. These features are then
linked to the internal structure of Magic applications using a
textual similarity (IR-based) method. We demonstrate the
feasibility of 4GL feature extraction method and validate it on
two variants of a real life logistical system each consisting of
more than 2000 Magic programs.
Keywords: Product lines,
SPL, feature extraction, Magic, 4GL, information retrieval, LSI.