Publications in Scientific Journals:
D. Winkler, M. Kalinowski, R. Sabou, S. Petrovic, S. Biffl:
"Investigating a Distributed and Scalable Model Review Process";
Centro Latinoamericano de Estudios en Informatica (CLEI) (invited),
[Context] Models play an important role in Software and Systems Engineering processes.
Reviews are well-established methods for model quality assurance that support early and
efficient defect detection. However, traditional document-based review processes have
limitations with respect to the number of experts, resources, and the document size that can be
applied. [Objective] In this paper, we introduce a distributed and scalable review process for
model quality assurance to (a) improve defect detection effectiveness and (b) to increase
review artifact coverage. [Method] We introduce the novel concept of Expected Model
Elements (EMEs) as a key concept for defect detection. EMEs can be used to drive the review
process. We adapt a best-practice review process to distinguish (a) between the identification
of EMEs in the reference document and (b) the use of EMEs to detect defects in the model.
We design and evaluate the adapted review process with a crowdsourcing tool in a feasibility
study. [Results] The study results show the feasibility of the adapted review process. Further,
the study showed that inspectors using the adapted review process achieved results for defect
detection effectiveness, which are comparable to the performance of inspectors using a
traditional inspection process, and better defect detection efficiency. Moreover, from a
practical perspective the adapted review process can be used to complement inspection efforts
conducted using the traditional inspection process, enhancing the overall defect detection
effectiveness. [Conclusions] Although the study shows promising results of the novel process,
future investigations should consider larger and more diverse review artifacts and the effect of
using limited and different scopes of artifact coverage for individual inspectors.
Review, Inspection, Models, Model Quality Assurance, Crowdsourcing, Feasibility Study, Controlled Experiment.
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Created from the Publication Database of the Vienna University of Technology.