We offer a range of open-source libraries and tools to aid in research and development in the field of Knowledge-Based Configuration Systems.

This site provides the documentation of the following Java library and apps:

  1. hiconfit-core
  2. KBStatistics
  3. FMGen

To use hiconfit-core, please first follow the guide in Get libraries.

Used by

hiconfit-core are used by the following projects:

  1. FMTesting - A Eclipse plug-in for feature model testing and debugging
  2. A Python implementation of hiconfit-core’s algorithms can be found in FlamaPy
  3. A Restful Webservice for developing product configurators with the following state-of-art technologies:
    • Domain reduction - decreases options that a user can select on the basis of previous selections of the user
    • Matrix Factorization-based Configuration and Recommendation - identifies Value Variable Heuristics on the basis of user requirements
    • Reordering the order of component’s options on the basis of the Value Variable Heuristic
    • Conflict and diagnosis detection

and also used in the following published papers:

  1. A. Felfernig, V.M. Le, A. Haag, S. Lubos. 2023. Solving Constraint Satisfaction Problems with Database Queries. In 25th International Workshop on Configuration (ConfWS 2023). Malaga, Spain. to appear
  2. S. Lubos, V.M. Le, A. Felfernig, T.N.T. Tran. 2023. Analysis Operations for Constraint-based Recommender Systems. In 17th ACM Conference on Recommender Systems (RecSys 2023). Singapore. to appear
  3. S. Lubos, A. Felfernig, V.M. Le, T.N.T. Tran, D. Benavides, J.A. Zamudio, D. Garber. 2023. Analysis Operations On The Run: Feature Model Analysis in Constraint-based Recommender Systems. In 27th ACM International Systems and Software Product Line Conference (SPLC 2023). to appear
  4. A. Felfernig, V.M. Le, S. Lubos. 2023. Conjunctive Query Based Constraint Solving For Feature Model Configuration. In 12th Conference on Information Technology and Its Applications. CITA’23, Danang, Vietnam. [arXiv]
  5. V.M. Le, C.V. Silva, A. Felfernig, T.N.T. Tran, J. Galindo, D. Benavides. 2023. FastDiagP: An Algorithm for Parallelized Direct Diagnosis. In 37th AAAI Conference on Artificial Intelligence. AAAI’23, Washington, DC, USA. [AAAI]
  6. V.M. Le, A. Felfernig, and T.N.T. Tran. 2022. Test Case Aggregation for Efficient Feature Model Testing, In 26th ACM International Systems and Software Product Line Conference (SPLC 2022). [ACM]
  7. V.M. Le, A. Felfernig, M. Uta, T.N.T. Tran, and C. Vidal. 2022. WipeOutR: Automated Redundancy Detection for Feature Models, In 26th ACM International Systems and Software Product Line Conference (SPLC 2022). [ACM]
  8. M. Uta, A. Felfernig, D. Helic, and V.M. Le. 2022. Accuracy- and consistency-aware recommendation of configurations. In 26th ACM International Systems and Software Product Line Conference (SPLC ‘22). [ACM]
  9. V.M. Le, A. Felfernig, T.N.T. Tran, M. Atas, M. Uta, D. Benavides, J. Galindo. 2021. DirectDebug: A software package for the automated testing and debugging of feature models. Software Impacts, Volume 9. [Elsevier]
  10. V.M. Le, A. Felfernig, M. Uta, D. Benavides, J. Galindo, and T.N.T. Tran. 2021. DirectDebug: Automated Testing and Debugging of Feature Models. IEEE/ACM 43rd International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER). [IEEE]

Development team

  • Mẫn (Graz University of Technology, Austria)
  • Tamim (Graz University of Technology, Austria)

Connect with us

  • For more information about the projects, support requests, and technical questions, do not hesitate to contact us.
  • Report and discuss issues on our corresponding GitHub repositories.
  • We welcome contributions from anyone.

Citing

If our implementations are utilized in your research, kindly cite the corresponding papers listed in the References.