D.3.3 ALGORITHMS FOR INCREMENTAL ... - SecureChange

models are too complex. The intuitiveness depends on the requirement language used
to represent before and after evolution models.
The Probability Estimation and the Reasoning phase are instead the key phases of
the approach to requirements evolution. The Probability Estimation gives the ability to
“translate” qualitative metrics that are typically used by stakeholders to classify evolution
into quantitative metrics that enable the Reasoning phase. The Reasoning phase has
turned out to be a powerful decision-support tool since it allows to select the optimal
design which is resilient to changes in the requirements model.
6.2 Experiences from Using a Qualitative Research Approach
During the execution of the user study, we have understood that several aspect can influence
the feedback collection from domain experts. The selection of domain experts
strongly influence the relevance of feedbacks collected and the satisfaction of the success
criteria chosen for the user study. In the user study, the domain experts selected had
a different background and so we were able to collect feedbacks about the approach to
requirement evolution from different perspectives.
Another important aspect to take into account is the potential communication gap
between the research team and the domain experts. Research team and domain experts
might use same terms with different meanings that can lead to misunderstandings and
to provide wrong or unrelated feedbacks. Thus, it is required to establish a common
language between the research team and the domain experts before the user study execution,
or to have a “mediator” who reformulates the questions of the research team for
the domain experts and who reformulates the domain experts’ feedback for the research
team. Moreover, the level of engagement of the domain experts depends by two main
factors: the means to provide feedbacks and the language in which such feedbacks need
to be provided. Different ways to collect feedbacks not only verbal one need to be supported.
The most effective one must be the one in which the domain experts can discuss
in their mother tongue language and then provide written feedback in English.
To collect more insightful feedbacks, hands-on sessions where the domain experts
apply/ use the artefacts under validation should be included in the validation session
execution.
Acknowledgement
We would like also to thank DeepBlue and ATM experts for participating in this study.
We would like to thank Professor John Mylopoulos, and colleagues in the ATHENA
research group at University of Trento (UNITN) for their scientific contribution, and
Dr. Alberto Battocchi (UNITN) for acting as an observer.
References
1. EUROCONTROL ATM Strategy for the Years 2000+ Executive Summary, 2003.
2. A. Bertolino, G. D. Angelis, A. D. Sandro, and A. Sabetta. Is my model right? let me ask the
expert. Journal of Systems and Software, 2011.
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