The evolution of modeling research challenges

Robert France, Bernhard Rumpe
<span title="">2013</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dfdth37zyfetvchsdjk5e2osrq" style="color: black;">Journal of Software and Systems Modeling</a> </i> &nbsp;
In 2007 ICSE hosted a track called "Future of Software Development" (FOSD). We were invited to write and present a paper on the future of modeling for the track. The resulting paper [1] described the state of modeling research, identified some major challenges and proposed a research road map. Parts of this road map are currently being explored, and progress has been made in addressing some of the challenges we identified. However, there is still significant research "to be done" with respect
more &raquo; ... the challenges outlined in that paper. It is not our intent to discuss the progress the community has made with respect to the road map in this editorial (our apologies for deflating expectations in this regard; an editorial is simply not the place for such discussions). Rather, we would like to use this editorial to stimulate discussions around some of the challenges that have arisen since we wrote that paper. Before we get into identifying specific challenges, let us first take a step back and ask "What is the grand challenge addressed by researchers in the SoSyM community?" The answer has typically been "To significantly reduce the time, cost, and effort required to develop complex softwareintensive systems that meet stringent quality requirements through use of models that are fit-for-purpose." This is still the focus of many research programs, but we are also seeing a broadening of the grand challenge to include not only development problems, but problems that occur throughout the lifetime of a complex system, from conception to retirement. For example, in the FOSD paper we made reference to emerging work on the use of models to manage software Rat runtime (now referred to as models@run.time). The grand challenge is thus evolving to encompass a wider range of problems that occur in the life cycle of complex systems, as it should. It is interesting to note that in other disciplines the use of models to manage work on artifacts throughout their life cycles is receiving significant attention. For example, in the construction domain building information modeling (BIM), techniques and standards are being developed to support the management to built environments from conception, to architectural design, to onsite construction, to building occupancy and finally to building demolition. In this case models are the primary means for managing work throughout a building's lifetime. Given this broader view of the role that models can play, we have identified the following research opportunities and challenges: • Systems that integrate mechanical, software and electrical engineering subsystems (e.g., cyber-physical systems (CPS)) will become commonplace, and thus, there is a need for work on how the modeling approaches used by experts in these diverse domains can be integrated. This is a very challenging problem, and thus, there is a need for significant intellectual investment in developing integrated modeling languages and associated tooling. With respect to CPS, there are two core issues that require our attention as researchers: -Mechanical, electrical and software engineering rely on entirely different theories (e.g., theories based on continuous mathematics versus those based on eventbased automata), and thus engineers in these domains use very different approaches. The challenge is to develop good bridges across these theories. 123
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