Abstract
Context and motivation: Product Line Engineering (PLE) is increasingly common practice in industry to develop complex systems for multiple customers with varying needs. In many business contexts, use cases are central development artifacts for requirements engineering and system testing. In such contexts, use case configurators can play a significant role to capture variable and common requirements in Product Line (PL) use case models and to generate Product Specific (PS) use case models for each new customer in a product family. Question/Problem: Although considerable research has been devoted to use case configurators, little attention has been paid to supporting the incremental reconfiguration of use case models with evolving configuration decisions. Principal ideas/results: We propose, apply, and assess an incremental reconfiguration approach to support evolving configuration decisions in PL use case models. PS use case models are incrementally reconfigured by focusing only on the changed decisions and their side effects. In our prior work, we proposed and applied Product line Use case modeling Method (PUM) to support variability modeling in PL use case diagrams and specifications. We also developed a use case configurator, PUMConf, which interactively collects configuration decisions from analysts to generate PS use case models from PL models. Our approach is built on top of PUM and PUMConf. Contributions: We provide fully automated tool support for incremental configuration as an extension of PUMConf. Our approach has been evaluated in an industrial case study in the automotive domain, which provided evidence it is practical and beneficial.
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Financial support was provided by IEE and FNR under grants FNR/P10/03 and FNR10045046.
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Hajri, I., Goknil, A., Briand, L.C., Stephany, T. (2017). Incremental Reconfiguration of Product Specific Use Case Models for Evolving Configuration Decisions. In: Grünbacher, P., Perini, A. (eds) Requirements Engineering: Foundation for Software Quality. REFSQ 2017. Lecture Notes in Computer Science(), vol 10153. Springer, Cham. https://doi.org/10.1007/978-3-319-54045-0_1
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