Toward Human-Like Summaries Generated from Heterogeneous Software Artefacts
This work aims to improve efficiency and quality for software developers, but it is incremental as it focuses on initial analysis rather than a full solution.
The paper tackles the problem of automatically generating human-like multi-document summaries from heterogeneous software artefacts by analyzing 545 human-written summaries from 15 software engineering projects to guide future heuristics.
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.