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References

  1. U. Junker. 2004. QuickXPlain: preferred explanations and relaxations for over-constrained problems. In Proceedings of the 19th national conference on Artificial intelligence (AAAI’04). AAAI Press, 167–172. https://dl.acm.org/doi/abs/10.5555/1597148.1597177
  2. A. Felfernig, M. Schubert, and C. Zehentner. 2012. An efficient diagnosis algorithm for inconsistent constraint sets. Artif. Intell. Eng. Des. Anal. Manuf. 26, 1 (February 2012), 53–62. DOI:https://doi.org/10.1017/S0890060411000011
  3. A. Felfernig, R. Walter, J.A. Galindo, et al. Anytime diagnosis for reconfiguration. J Intell Inf Syst 51, 161–182 (2018). https://doi.org/10.1007/s10844-017-0492-1
  4. V.M. Le, A. Felfernig, M. Uta, D. Benavides, J. Galindo, and T.N.T. Tran, DirectDebug: Automated Testing and Debugging of Feature Models, 2021 IEEE/ACM 43rd International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER), 2021, pp. 81-85, doi: https://doi.org/10.1109/ICSE-NIER52604.2021.00025.
  5. V.M. Le, A. Felfernig, T.N.T. Tran, M. Atas, M. Uta, D. Benavides, J. Galindo, DirectDebug: A software package for the automated testing and debugging of feature models, Software Impacts, Volume 9, 2021, 100085, ISSN 2665-9638, https://doi.org/10.1016/j.simpa.2021.100085.
  6. DirectDebug’s Original version with an evaluation in https://github.com/AIG-ist-tugraz/DirectDebug.
  7. An executable evaluation of DirectDebug on CodeOcean https://codeocean.com/capsule/5824065/tree/v1
  8. R. Reiter, A theory of diagnosis from first principles, Artificial Intelligence, Volume 32, Issue 1, 1987, pp. 57-95, ISSN 0004-3702, https://doi.org/10.1016/0004-3702(87)90062-2.
  9. R. Greiner, B. A. Smith, and R. W. Wilkerson, A correction to the algorithm in reiter’s theory of diagnosis, Artif Intell, vol. 41, no. 1, pp. 79–88, 1989, https://doi.org/10.1016/0004-3702(89)90079-9.
  10. D. Jannach, T. Schmitz, and K. Shchekotykhin. “Parallel model-based diagnosis on multi-core computers.” Journal of Artificial Intelligence Research 55 (2016): 835-887. https://doi.org/10.1613/jair.5001.
  11. D. Jannach, T. Schmitz, and K. Shchekotykhin. (2015). Parallelized Hitting Set Computation for Model-Based Diagnosis. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1). https://doi.org/10.1609/aaai.v29i1.9389.
  12. V.M. Le, A. Felfernig, M. Uta, T.N.T. Tran, and C. Vidal, WipeOutR: Automated Redundancy Detection for Feature Models, 26th ACM International Systems and Software Product Line Conference (SPLC 2022), 2022. https://doi.org/10.1145/3546932.3546992.
  13. An evaluation of WipeOutR algorithms in https://github.com/AIG-ist-tugraz/WipeOutR.
  14. V.M. Le, A. Felfernig, and T.N.T. Tran, Test Case Aggregation for Efficient Feature Model Testing, 26th ACM International Systems and Software Product Line Conference (SPLC 2022) - Volume B, 2022. https://doi.org/10.1145/3503229.3547046
  15. V.M. Le, C.V. Silva, A. Felfernig, T.N.T. Tran, J. Galindo, D. Benavides. FastDiagP: An Algorithm for Parallelized Direct Diagnosis. In 37th AAAI Conference on Artificial Intelligence. AAAI’23, Washington, DC, USA. 2023. (to appear)
  16. An evaluation of FastDiagP algorithm in https://github.com/AIG-ist-tugraz/FastDiagP.