Welcome to Zen-Configurator

Nowadays, Cyber Physical Systems (CPSs) are everywhere in our daily life from video conferencing systems, subsea oil and gas production systems, smart buildings, smart healthcare products. These systems are mostly developed by reusing existing system designs, instead from the scratch, for the purpose of reducing development cost and improving product quality. Systematically doing so follows into the research stream of system product line engineering. However, configuring large-scale CPS product lines requires a systematic, interactive and maximally automated methodology (with tool support).

The goal of the Zen-Configurator project is to increase the cost-effectiveness of configuring large-scale CPS product lines at different phases of the development lifecycle of such systems (e.g., pre-deployment, post-deployment and runtime operation phases). To achieve this goal, we maximally automate error-prone and costly manual configuration activities and optimally assist the interactive configuration process. On one hand, the project relies on advanced technologies of constraint solving/evaluation, optimization using search algorithms, machine learning techniques and propose state-of-art algorithms to enable automated configuration activities. On the other hand, the project grounds itself to address real challenges faced by industry and propose a practical and applicable solution and apply it to solve real-world problems.

In the context of the project, we have developed a methodology with tool support to address pre-deployment and post-deployment phase configurations of CPSs. In the rest of the project, we aim for covering the runtime and dynamic configuration of CPSs, and conduct more empirical studies to evaluate the developed framework.


Functionalities of Zen-Configurator

  • Zen-DO will be triggered every time a variation point (VP) is configured to dynamically update the order of the un-configured VPs for minimizing manual efforts.
  • Zen-CC is to incrementally check whether the manually configured data conforms to a set of predefined rules.
  • Zen-CD can automatically configure certain VPs based on VP dependencies and previous configurations.
  • Zen-FIX relies on multi-objective search to automatically recommend nonconformity resolutions, meanwhile optimizing the overall efficiency of the interactive product configuration process.

  • Industry Application Domains

    • Energy
    • Telecommunication
    • Maritime
    • Logistic

    Related Publications

    • Behjati, Razieh, Tao Yue, Lionel Briand, and Bran Selic. "SimPL: A product-line modeling methodology for families of integrated control systems." Information and Software Technology 55, no. 3 (2013): 607-629.
    • Nie, Kunming, Tao Yue, Shaukat Ali, Li Zhang, and Zhiqiang Fan. "Constraints: The core of supporting automated product configuration of cyber-physical systems." In International Conference on Model Driven Engineering Languages and Systems, pp. 370-387. Springer, Berlin, Heidelberg, 2013.
    • Lu, Hong, Tao Yue, Shaukat Ali, Kunming Nie, and Li Zhang. "Zen-CC: An Automated and Incremental Conformance Checking Solution to Support Interactive Product Configuration." In Software Reliability Engineering (ISSRE), 2014 IEEE 25th International Symposium on, pp. 13-22. IEEE, 2014.
    • Yue, Tao, Shaukat Ali, and Bran Selic. "Cyber-physical system product line engineering: comprehensive domain analysis and experience report." In Proceedings of the 19th International Conference on Software Product Line, pp. 338-347. ACM, 2015.
    • Nie, Kunming, Tao Yue, and Shaukat Ali. "Towards a Search-based Interactive Configuration of Cyber Physical System Product Lines." In Demos/Posters/StudentResearch@ MoDELS, pp. 71-75. 2013.
    • Yue, Tao, Shaukat Ali, Hong Lu, and Kunming Nie. "Search-based decision ordering to facilitate product line engineering of cyber-physical system." In Model-Driven Engineering and Software Development (MODELSWARD), 2016 4th International Conference on, pp. 691-703. IEEE, 2016.
    • Lu, Hong, Tao Yue, Shaukat Ali, and Li Zhang. "Model-based incremental conformance checking to enable interactive product configuration." Information and Software Technology 72 (2016): 68-89.
    • 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.
    • Iglesias, Aitziber, Hong Lu, Cristóbal Arellano, Tao Yue, Shaukat Ali, and Goiuria Sagardui. "Product Line Engineering of Monitoring Functionality in Industrial Cyber-Physical Systems: A Domain Analysis." In Proceedings of the 21st International Systems and Software Product Line Conference-Volume A, pp. 195-204. ACM, 2017.
    • Qiu, Xiang, Shaukat Ali, Tao Yue, and Li Zhang. "Reliability-redundancy-location allocation with maximum reliability and minimum cost using search techniques." Information and Software Technology 82 (2017): 36-54.
    • Li, Yan, Tao Yue, Shaukat Ali, and Li Zhang. "Zen-ReqOptimizer: a search-based approach for requirements assignment optimization." Empirical Software Engineering 22, no. 1 (2017): 175-234.
    • Safdar, Safdar Aqeel, Tao Yue, Shaukat Ali, and Hong Lu. "Evaluating Variability Modeling Techniques for Supporting Cyber-Physical System Product Line Engineering." In International Conference on System Analysis and Modeling, pp. 1-19. Springer International Publishing, 2016.
    • Safdar, Safdar Aqeel, Hong Lu, Tao Yue, and Shaukat Ali. "Mining cross product line rules with multi-objective search and machine learning." In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1319-1326. ACM, 2017.
    • Li, Yan, Tao Yue, Shaukat Ali, and Li Zhang. "A multi-objective and cost-aware optimization of requirements assignment for review." In Evolutionary Computation (CEC), 2017 IEEE Congress on, pp. 89-96. IEEE, 2017.
    • Li, Yan, Man Zhang, Tao Yue, Shaukat Ali, and Li Zhang."Search-based Uncertainty-wise Requirements Prioritization." In The 22nd International Conference on Engineering of Complex Computer Systems. IEEE, 2017.

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