  Managing models in a consistent manner is an important task in the field of
Model-Driven Engineering (MDE). Although restoring and maintaining consistency
is desired in general, recent work has pointed out that always strictly
enforcing consistency at any point of time is often not feasible in real-world
scenarios, and sometimes even contrary to what a user expects from a
trustworthy MDE tool. The challenge of tolerating inconsistencies has been
discussed from different viewpoints within and outside the modelling community,
but there exists no structured overview of existing and current work in this
regard. In this paper, we provide such an overview to help join forces tackling
the unresolved problems of tolerating inconsistencies in MDE. We follow the
standard process of a Systematic Literature Review (SLR) to point out what
tolerance means, how it relates to uncertainty, which examples for tolerant
software systems have already been discussed, and which benefits and drawbacks
tolerating inconsistencies entails. Furthermore, we propose a tool-chain that
helps conducting SLRs in computer science and also eases the reproduction of
results. Relevant meta-data of the collected sources is uniformly described in
a textual modelling language and exported to the graph database Neo4j to query
aggregated information.
