  Automatic text summarisation has drawn considerable interest in the field of
software engineering. It can improve the efficiency of software developers,
enhance the quality of products, and ensure timely delivery. In this paper, we
present our initial work towards automatically generating human-like
multi-document summaries from heterogeneous software artefacts. Our analysis of
the text properties of 545 human-written summaries from 15 software engineering
projects will ultimately guide heuristics searches in the automatic generation
of human-like summaries.
