  Measuring and evaluating software quality has become a fundamental task. Many
models have been proposed to support stakeholders in dealing with software
quality. However, in most cases, quality models do not fit perfectly for the
target application context. Since approaches for efficiently adapting quality
models are largely missing, many quality models in practice are built from
scratch or reuse only high-level concepts of existing models. We present a
tool-supported approach for the efficient adaptation of quality models. An
initial empirical investigation indicates that the quality models obtained
applying the proposed approach are considerably more consistently and
appropriately adapted than those obtained following an ad-hoc approach.
Further, we could observe that model adaptation is significantly more efficient
(~factor 8) when using this approach.
