Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

9-2020

Abstract

Automatic text summarisation has drawn considerable interest in the area of software engineering. It is challenging to summarise the activities related to a software project, (1) because of the volume and heterogeneity of involved software artefacts, and (2) because it is unclear what information a developer seeks in such a multi-document summary. We present the first framework for summarising multi-document software artefacts containing heterogeneous data within a given time frame. To produce human-like summaries, we employ a range of iterative heuristics to minimise the cosine-similarity between texts and high-dimensional feature vectors. A first study shows that users find the automatically generated summaries the most useful when they are generated using word similarity and based on the eight most relevant software artefacts.

Keywords

Extractive summarisation, Heuristic optimisation, Software development

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Proceedings of the 16th International Conference on Parallel Problem Solving from Nature, Leiden, The Netherlands, 2020 September 5-9

Last Page

329

ISBN

9783030581145

Identifier

10.1007/978-3-030-58115-2_23

Publisher

SpringerLink

City or Country

Verlag, Berlin

Additional URL

https://doi.org/10.1007/978-3-030-58115-2_23

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