Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/129001
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Type: | Conference paper |
Title: | Human-like summaries from heterogeneous and time-windowed software development artefacts |
Author: | Alghamdi, M. Treude, C. Wagner, M. |
Citation: | Lecture Notes in Artificial Intelligence, 2020 / Bäck, T., Preuss, M., Deutz, A., Wang, H., Doerr, C., Emmerich, M., Trautmann, H. (ed./s), vol.12270 LNCS, pp.329-342 |
Publisher: | Springer |
Publisher Place: | Cham, Switzerland |
Issue Date: | 2020 |
Series/Report no.: | Lecture notes in Computer Science; 12270 |
ISBN: | 9783030581145 |
ISSN: | 0302-9743 1611-3349 |
Conference Name: | International Conference on Parallel Problem Solving from Nature (PPSN) (5 Sep 2020 - 9 Sep 2020 : Leiden, The Netherlands) |
Editor: | Bäck, T. Preuss, M. Deutz, A. Wang, H. Doerr, C. Emmerich, M. Trautmann, H. |
Statement of Responsibility: | Mahfouth Alghamdi, Christoph Treude, Markus Wagner |
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 |
Description: | First Online: 02 September 2020 |
Rights: | © Springer Nature Switzerland AG 2020 |
DOI: | 10.1007/978-3-030-58115-2_23 |
Grant ID: | http://purl.org/au-research/grants/arc/DE180100153 http://purl.org/au-research/grants/arc/DE160100850 |
Published version: | http://dx.doi.org/10.1007/978-3-030-58115-2_23 |
Appears in Collections: | Aurora harvest 4 Computer Science publications |
Files in This Item:
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hdl_129001.pdf | Accepted version | 850.61 kB | Adobe PDF | View/Open |
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