  [Context] The quality of requirements engineering artifacts, e.g.
requirements specifications, is acknowledged to be an important success factor
for projects. Therefore, many companies spend significant amounts of money to
control the quality of their RE artifacts. To reduce spending and improve the
RE artifact quality, methods were proposed that combine manual quality control,
i.e. reviews, with automated approaches. [Problem] So far, we have seen various
approaches to automatically detect certain aspects in RE artifacts. However, we
still lack an overview what can and cannot be automatically detected.
[Approach] Starting from an industry guideline for RE artifacts, we classify
166 existing rules for RE artifacts along various categories to discuss the
share and the characteristics of those rules that can be automated. For those
rules, that cannot be automated, we discuss the main reasons. [Contribution] We
estimate that 53% of the 166 rules can be checked automatically either
perfectly or with a good heuristic. Most rules need only simple techniques for
checking. The main reason why some rules resist automation is due to imprecise
definition. [Impact] By giving first estimates and analyses of automatically
detectable and not automatically detectable rule violations, we aim to provide
an overview of the potential of automated methods in requirements quality
control.
