  Model-based testing (MBT) promises a scalable solution to testing large
systems, if a model is available. Creating these models for large systems,
however, has proven to be difficult. Composing larger models from smaller ones
could solve this, but our current MBT conformance relation $\textbf{uioco}$ is
not compositional, i.e. correctly tested components, when composed into a
system, can still lead to a faulty system. To catch these integration problems,
we introduce a new relation over component models called $\textbf{mutual
acceptance}$. Mutually accepting components are guaranteed to communicate
correctly, which makes MBT compositional. In addition to providing
compositionality, mutual acceptance has benefits when retesting systems with
updated components, and when diagnosing systems consisting of components.
