  The software engineering field has a long history of classifying software
failure causes. Understanding them is paramount for fault injection, focusing
testing efforts or reliability prediction. Since software fails in manifold
complex ways, a broad range of software failure cause models is meanwhile
published in dependability literature. We present the results of a meta-study
that classifies publications containing a software failure cause model in topic
clusters. Our results structure the research field and can help to identify
gaps. We applied the systematic mapping methodology for performing a repeatable
analysis.
  We identified 156 papers presenting a model of software failure causes. Their
examination confirms the assumption that a large number of the publications
discusses source code defects only. Models of fault-activating state conditions
and error states are rare. Research seems to be driven mainly by the need for
better testing methods and code-based quality improvement. Other motivations
such as online error detection are less frequently given. Mostly, the IEEE
definitions or orthogonal defect classification is used as base terminology.
The majority of use cases comes from web, safety- and security-critical
applications.
