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Measuring the Complexity of Product Configuration Systems

Abstract : The complexity of product configuration systems is an important indicator of both development and maintenance effort of the systems. Existing literature proposes a couple of effort estimation approaches for configurator projects. However, these approaches do not address the issues of comprehensibility and modifiability of a configuration model. Therefore, this article proposes a metric to measure the total cognitive complexity of the configuration model corresponding to a product configuration system, expressed in the form of an UML class diagram. This metric takes into account the number and the type of attributes, constraints and the relationships between classes in an UML class diagram. The proposed metric can be used to compare two configuration models, in terms of their cognitive complexity. Moreover, a relation between development time for a PCS project and the total cognitive complexity of the corresponding configuration model is established using linear regression. To validate the proposed approach a case study is conducted where the cognitive complexity is calculated for two configuration models.
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Submitted on : Monday, December 3, 2018 - 3:10:05 PM
Last modification on : Friday, August 5, 2022 - 12:38:15 PM
Long-term archiving on: : Monday, March 4, 2019 - 2:11:12 PM


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  • HAL Id : hal-01942692, version 1



Amartya Ghosh, Katrin Kristjandottir, Lars Hvam, Élise Vareilles. Measuring the Complexity of Product Configuration Systems. ConfWS 2018 - 20th Configuration Workshop, Sep 2018, Graz, Austria. p.61-68. ⟨hal-01942692⟩



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