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Systematic Review of Software Behavioral Model Consistency Checking


In software development, models are often used to represent multiple views of the same system. Such models need to be properly related to each other in order to provide a consistent description of the developed system. Models may contain contradictory system specifications, for instance, when they evolve independently. Therefore, it is very crucial to ensure that models conform to each other. In this context, we focus on consistency checking of behavior models. Several techniques and approaches have been proposed in the existing literature to support behavioral model consistency checking. This paper presents a Systematic Literature Review (SLR) that was carried out to obtain an overview of the various consistency concepts, problems, and solutions proposed regarding behavior models. In our study, the identification and selection of the primary studies was based on a well-planned search strategy. The search process identified a total of 1770 studies, out of which 96 have been thoroughly analyzed according to our predefined SLR protocol. The SLR aims to highlight the state-of-the-art of software behavior model consistency checking and identify potential gaps for future research. Based on research topics in selected studies, we have identified seven main categories: targeted software models, types of consistency checking, consistency checking techniques, inconsistency handling, type of study and evaluation, automation support, and practical impact. The findings of the systematic review also reveal suggestions for future research, such as improving the quality of study design and conducting evaluations, and application of research outcomes in industrial settings. For this purpose, appropriate strategy for inconsistency handling, better tool support for consistency checking and/or development tool integration should be considered in future studies.

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Journal Paper
Software Architecture
Informatik Allgemeines
Software Engineering
Journal or Publication Title
ACM Computing Surveys
April 2017
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