Welcome to Zen-FIX

In the context of large-scale system product line engineering, manual configuration is often mandatory and therefore inevitably introduces nonconformities: violating pre-defined constraints for conformance checking. Resolving nonconformities without proper tool support is more or less random, as there are usually hundreds and thousands of configurable parameters and conformance constraints, in the context of configuring a large-scale and directly deployable system. Moreover, inter-connections among constraints and configurable parameters worsen the feasibility of manual resolving nonconformities without proper tool support.

we present an automatic approach (named as Zen-FIX) to optimally recommend solutions to resolve nonconformities using multi-objective search. Solutions recommended by Zen- FIX conform to all pre-defined constraints and are optimized in terms of maximizing the overall efficiency of an interactive product configuration process.

Approach & Evaluation

Heuristics for Finding Optimal Solutions
  • Minimizing the number of configurable parameter instances to fix
  • Minimizing the impact on the overall configuration of a product
  • Minimizing the conformance checking effort
  • Maximizing the number of configurable parameter instances to be automatically inferred
  • Case Studies Used For Evaluation
  • Subsea Production System
  • Evaluation Results

    We evaluated Zen-FIX with a real-world case study containing 52454 optimization problems, with which we evaluated seven multi-objective search algorithms. Results show that Zen-FIX provides nonconformity fixing solutions within seconds. Moreover, MoCell outperformed all the others: CellDE, IBEA, NSGA-II, PESA2, Random, SPEA2, for most of the problems, in terms of Efficiency (a combined metric of finding optimized solutions and time performance).

    Detailed information of the experiment data can be found here.

    Zen-FIX Publications

    • Lu, Hong, Tao Yue, Shaukat Ali, and Li Zhang. "Nonconformity Resolving Recommendations for Product Line Configuration." In Software Testing, Verification and Validation (ICST), 2016 IEEE International Conference on, pp. 57-68. IEEE, 2016.

    Project Leaders

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