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Research Article | Open Access |

Reviewing Diagnosis Solutions for Valid Product Configurations in the Automated Analysis of Feature Models

Author 1: Cristian L. Vidal-Silva
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 10, No. 1 · Published 2019

DOI: https://doi.org/10.14569/IJACSA.2019.0100168

Abstract

A Feature Model (FM) is an information model to represent commonalities and variabilities for all the products of a Software Product Line (SPL). The complexity and large-scale of real feature models makes their manual analysis for determining the product configurations validity a tedious or even infeasible task. Efficient solutions for the diagnosis of errors in the Automated Analysis of Feature Models (AAFM) already exist such as FMDiag and FlexDiag. Thus, this work describes the fundamental basis for both diagnosis algorithms to apply the first of them on the validity of FM product configurations. The results highlight the applicability and efficiency of FMDiag and invite us to look for additional applications in the AAFM scenarios.

Keywords

How to Cite this Article

Vidal-Silva, C. L. (2019). Reviewing Diagnosis Solutions for Valid Product Configurations in the Automated Analysis of Feature Models. International Journal of Advanced Computer Science and Applications, 10(1). https://doi.org/10.14569/IJACSA.2019.0100168

Vidal-Silva, Cristian L.. "Reviewing Diagnosis Solutions for Valid Product Configurations in the Automated Analysis of Feature Models." International Journal of Advanced Computer Science and Applications, vol. 10, no. 1, 2019, https://doi.org/10.14569/IJACSA.2019.0100168.

@article{Vidal-Silva2019,
  title     = {Reviewing Diagnosis Solutions for Valid Product Configurations in the Automated Analysis of Feature Models},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {1},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Cristian L. Vidal-Silva},
  doi       = {10.14569/IJACSA.2019.0100168},
  url       = {https://doi.org/10.14569/IJACSA.2019.0100168}
}

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