Information retrieval based feature analysis for product line adoption in 4GL systems

András Kicsi, László Vidács, Árpád Beszédes, Ferenc Kocsis, István Kovács

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 2017 17th International Conference on Computational Science and Its Applications, ICCSA 2017
EditorsDavid Taniar, Ana Maria A.C. Rocha, Sanjay Misra, Carmelo Maria Torre, Alfredo Cuzzocrea, Osvaldo Gervasi, Giuseppe Borruso, Bernady O. Apduhan, Beniamino Murgante, Alfredo Cuzzocrea, Sanjay Misra, Elena Stankova E
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538638934
DOIs
Publication statusPublished - Aug 1 2017
Event17th International Conference on Computational Science and Its Applications, ICCSA 2017 - Trieste, Italy
Duration: Jul 3 2017Jul 6 2017

Publication series

NameProceedings of the 2017 17th International Conference on Computational Science and Its Applications, ICCSA 2017

Other

Other17th International Conference on Computational Science and Its Applications, ICCSA 2017
CountryItaly
CityTrieste
Period7/3/177/6/17

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Keywords

  • 4GL
  • Feature extraction
  • Information retrieval
  • LSI
  • Magic
  • Product lines
  • SPL

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Modelling and Simulation
  • Computer Science Applications

Cite this

Kicsi, A., Vidács, L., Beszédes, Á., Kocsis, F., & Kovács, I. (2017). Information retrieval based feature analysis for product line adoption in 4GL systems. In D. Taniar, A. M. A. C. Rocha, S. Misra, C. M. Torre, A. Cuzzocrea, O. Gervasi, G. Borruso, B. O. Apduhan, B. Murgante, A. Cuzzocrea, S. Misra, & E. Stankova E (Eds.), Proceedings of the 2017 17th International Conference on Computational Science and Its Applications, ICCSA 2017 [7999651] (Proceedings of the 2017 17th International Conference on Computational Science and Its Applications, ICCSA 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCSA.2017.7999651