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When specifying change for an existing system, the history and functionality of the system to be replaced has to be considered. This avoids neglecting important system functionality and repeating errors. The properties and the rationale behind the existing system can be elicited by analysing concrete system-usage scenarios [Pohl, K., Weidenhaupt, K., Domges, R., Haumer, P., Jarke, M., Klamma, R., 1999. Process-integrated (modelling) environments (PRIME): foundation and implementation framework. ACM Transactions on Software Engineering and Methodology (TOSEM), vol. 8, no. 4, pp. 343–410]. The results of the analysis of the existing system are then typically represented using conceptual models. To establish conceptual models of high quality reviewing the models is common practice. The problem faced with when reviewing conceptual models, is that the reviewer cannot assess and therefore understand the basis (concrete system usage) on which the conceptual models were built. In this paper, we present an approach to overcome this problem. We establish Extended Traceability, by recording concrete system-usage scenarios using rich media (e.g. video, speech, graphic) and interrelating the recorded observations with the conceptual models. We discuss the main improvements for review processes and illustrate the advantages with excerpts from a case study performed in a mechanical engineering company.

A requirements specification defines the requirements for the future system at a conceptual level (i.e., class or type level). In contrast, a scenario represents a concrete example of current or future system usage. In early RE phases, scenarios are used to support the definition of high level requirements (goals) to be achieved by the new system. In many cases, those goals can to a large degree be elicited by observing, documenting and analyzing scenarios about current system usage. To support the elicitation and validation of the goals achieved by the existing system and to illustrate problems of the old system, we propose to capture current system usage using rich media (e.g., video, speech, pictures, etc.) and to interrelate those observations with the goal definitions. Thus, we aim at making the abstraction process which leads to the definition of the conceptual models more transparent and traceable. We relate the parts of the observations which have caused the definition of a goal or against which a goal was validated with the corresponding goal. These interrelations provide the basis for: 1) explaining and illustrating a goal model to, e.g., untrained stakeholders and/or new team members; 2) detecting, analyzing, and resolving a different interpretation of the observations; 3) comparing different observations using computed goal annotations; and 4) refining or detailing a goal model during later process phases. Using the PRIME implementation framework, we have implemented the PRIME-CREWS environment, which supports the interrelation of conceptual models and captured system usage observations. We report on our experiences with PRIME-CREWS gained in an experimental case study.

When defining a new system, the history and functionality of the system to be replaced should be considered. This avoids repeating errors and neglecting important system functionality. The properties and the rationale behind the existing system are typically elicited by analysing concrete system usage-scenarios. The results of the analysis of the existing system are typically represented using conceptual models. To establish conceptual models of high quality, reviewing the models is common practice. The problem faced with when reviewing conceptual models, is that the reviewer cannot assess and therefore understand the basis (concrete system usage) on which the conceptual models where build. In this paper, we present an approach to overcome this problem. We argue to establish extended traceability, by recording concrete system usage scenarios using rich media (e.g. video, speech, graphic) and interrelating the recorded observations with the conceptual models. We discuss the main improvements for review processes resulting from the extended traceability and illustrate the advantages with excerpts from a case study performed in a mechanical engineering company.

Summary form only given. Scenario-based approaches are attracting more and more interest in requirements engineering research and practice. The research literature offers an increasing number of scenario-related methods, models and notations which highlight the consideration of concrete system descriptions from a usage-oriented perspective, prior to abstract conceptual modelling of function, data and behavior. Scenario use is also becoming a pervasive phenomenon in industrial practice, but comprehensive and expressive studies on the practical relevance of the techniques proposed by research are still rare. The European ESPRIT project CREWS (Cooperative Requirements Engineering With Scenarios) aims at a deeper understanding of the diversity of scenarios, in order to help improve methodological and tool support for scenario-based requirements engineering. The authors consider the two-pronged strategy being followed to gain this understanding.