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A model for tracing variability from features to product-line architectures: a case study in smart grids

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Abstract

In current software systems with highly volatile requirements, traceability plays a key role to maintain the consistency between requirements and code. Traceability between artifacts involved in the development of software product line (SPL) is still more critical because it is necessary to guarantee that the selection of variants that realize the different SPL products meet the requirements. Current SPL traceability mechanisms trace from variability in features to variations in the configuration of product-line architecture (PLA) in terms of adding and removing components. However, it is not always possible to materialize the variable features of a SPL through adding or removing components, since sometimes they are materialized inside components, i.e., in part of their functionality: a class, a service, and/or an interface. Additionally, variations that happen inside components may crosscut several components of architecture. These kinds of variations are still challenging and their traceability is not currently well supported. Therefore, it is not possible to guarantee that those SPL products with these kinds of variations meet the requirements. This paper presents a solution for tracing variability from features to PLA by taking these kinds of variations into account. This solution is based on models and traceability between models in order to automate SPL configuration by selecting the variants and realizing the product application. The FPLA modeling framework supports this solution which has been deployed in a software factory. Validation has consisted in putting the solution into practice to develop a product line of power metering management applications for smart grids.

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Notes

  1. It is available on: https://syst.eui.upm.es/FPLA/home.

  2. Most services are omitted to gain readability.

  3. The feature metamodel is described in [15], while the Flexible-PLA metamodel is described in [41].

  4. https://syst.eui.upm.es/FPLA/home.

  5. http://www.upm.es/internacional.

  6. http://www.indracompany.com/en.

  7. The script of the interviews is available on https://www.surveymonkey.com/s/TSYCCN6.

  8. Redmine is web-based project management and bug-tracking tool http://www.redmine.org/.

  9. Intelligent Monitoring of Power NETworks http://www.itea2.org/project/index/view?project=10032.

  10. NEtworked MOnitoring & COntrol, Diagnostic for Electrical Distribution http://www.itea2.org/project/index/view?project=1131.

  11. Technologies for automated and intelligent management of power distribution networks of the future http://www.indracompany.com/sostenibilidad-e-innovacion/proyectos-innovacion/energos-technologies-for-automated-and-intelligent-.

  12. Oracle Berkeley DB is a high-performance embeddable database providing Java Object and Key/Value storage (NoSQL). http://www.oracle.com/technetwork/products/berkeleydb/.

  13. Apache Hadoop is a framework for running applications on large cluster built of commodity hardware. http://hadoop.apache.org/.

  14. Object-relational database management system. http://www.oracle.com/technetwork/database/.

  15. Software for clustering and high availability in Oracle db environments. http://www.oracle.com/technetwork/products/clustering/.

  16. Although other papers propose other traceability approaches [40, 43,46], we did not include them here as they do not consider SPLE.

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Acknowledgments

The work reported in here has been partially sponsored by the Spanish fund: INNOSEP (TIN2009-13849), IMPONET (ITEA 2 09030, TSI-02400-2010-103), i-SSF (IPT-430000-2010-038), NEMO&CODED (ITEA2 08022, IDI-20110864), and ENERGOS (CEN-20091048). Finally, it is also funded by the UPM (Technical University of Madrid) under their researcher training program.

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Authors and Affiliations

  1. CITSEM, Technical University of Madrid (UPM) - Universidad Politécnica de Madrid, Ctra. Valencia Km. 7, 28031, Madrid, Spain

    Jessica Díaz

  2. E.U. Informática - CITSEM, Technical University of Madrid (UPM) - Universidad Politécnica de Madrid, Ctra. Valencia Km. 7, 28031, Madrid, Spain

    Jennifer Pérez & Juan Garbajosa

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  1. Jessica Díaz
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Correspondence to Jessica Díaz.

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Díaz, J., Pérez, J. & Garbajosa, J. A model for tracing variability from features to product-line architectures: a case study in smart grids. Requirements Eng 20, 323–343 (2015). https://doi.org/10.1007/s00766-014-0203-1

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