  Systematic literature studies have received much attention in empirical
software engineering in recent years. They have become a powerful tool to
collect and structure reported knowledge in a systematic and reproducible way.
We distinguish systematic literature reviews to systematically analyze reported
evidence in depth, and systematic mapping studies to structure a field of
interest in a broader, usually quantified manner. Due to the rapidly increasing
body of knowledge in software engineering, researchers who want to capture the
published work in a domain often face an extensive amount of publications,
which need to be screened, rated for relevance, classified, and eventually
analyzed. Although there are several guidelines to conduct literature studies,
they do not yet help researchers coping with the specific difficulties
encountered in the practical application of these guidelines. In this article,
we present an experience-based guideline to aid researchers in designing
systematic literature studies with special emphasis on the data collection and
selection procedures. Our guideline aims at providing a blueprint for a
practical and pragmatic path through the plethora of currently available
practices and deliverables capturing the dependencies among the single steps.
The guideline emerges from various mapping studies and literature reviews
conducted by the authors and provides recommendations for the general study
design, data collection, and study selection procedures. Finally, we share our
experiences and lessons learned in applying the different practices of the
proposed guideline.
