Conference Proceedings
Human-like summaries from heterogeneous and time-windowed software development artefacts
M Alghamdi, C Treude, M Wagner
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics | Published : 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 automatical..
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Grants
Awarded by Australian Research Council
Funding Acknowledgements
Mahfouth has been sponsored by the Institute of Public Administration (IPA), Saudi Arabia. Christoph's and Markus' work has been supported by the Australian Research Council projects DE180100153 and DE160100850, and by the 2019 Google Faculty Research Award "Rewriting software documentation for non-native speakers".