@misc{12897,
  author = {Razieh Behjati and Tao Yue and Lionel Briand and Bran Selic},
  title = {SimPL: a Product-Line Modeling Methodology for Families of Integrated Control Systems},
  abstract = {Product-line engineering is increasingly gaining attention in the domain of integrated control systems (ICSs), in which software and hardware components are integrated to control and monitor physical devices and processes. ICSs are typically large-scale, highly-configurable, and highly-hierarchical software intensive systems. A family of ICSs share the same software code base, which is configured differently for each product to form a unique installation and therefore a large number of interdependent variability points are introduced by both hardware and software components. Due to the complexities of such systems and inadequate automation support, product configuration and derivation is becoming an error prone and costly task and, therefore, quality and productivity of the product development process cannot be assured. To overcome these challenges, we propose a scalable, UML-based, and standard-oriented product-line modeling methodology to support automated and systematic product configuration and derivation of ICSs. We performed a comprehensive domain analysis to identify characteristics of ICS families, and their configuration requirements, based on which we propose a modeling methodology named SimPL. The SimPL methodology is evaluated based on an industrial case study. Our experience with the industrial case study shows that the SimPL methodology provides necessary and sufficient constructs and clear guidelines for modeling product-line architectures. Our evaluation results also show that SimPL is scalable and easy to use in practice, and it is capable of supporting the automated product configuration and derivation process. In conclusion, to solve the configuration problems in the domain of ICS families, it is required to automate the configuration process as much as possible by systematically and precisely providing sufficient information about software and hardware variability points and their interdependencies. UML-based modeling methodologies, according to our experience with applying SimPL in an industrial case study, appear to be applicable for this purpose.},
  year = {2011},
  number = {2011-14 (V. 4)},
  publisher = {Simula Research Laboratory},
}