  Background: Software Process Simulation (SPS) has become an effective tool
for software process management and improvement. However, its adoption in
industry is less than what the research community expected due to the burden of
measurement cost and the high demand for domain knowledge. The difficulty of
extracting appropriate metrics with real data from process enactment is one of
the great challenges. Objective: We aim to provide evidence-based support of
the process metrics for software process (simulation) modeling. Method: A
systematic literature review was performed by extending our previous review
series to draw a comprehensive understanding of the metrics for process
modeling following a meta-model of ontology of metrics in SPS. Results: We
identified 145 process modeling studies that collectively involve 2130 metrics
and classified them using the coding technique. Two diagrams which illustrate
the high frequency causal relationships used between metrics are proposed in
terms of two hierarchical levels of modeling purposes. We revisited the data
issues encountered in SPS data preparing phases, as well as identified the
corresponding strategies. Conclusion: The results of this study provide process
modelers with an evidence-based reference of the identification and the use of
metrics in SPS modeling, and further contribute to the development of the body
of knowledge on software metrics in the context of process modeling.
Furthermore, this study is not limited to process simulation but can be
extended to software process modeling, in general. Taking simulation metrics as
standards and references can further motivate and guide software developers to
improve the collection, governance, and application of process data in
practice.
