Toward human-like summaries generated from heterogeneous software artefacts

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...

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Main Authors:	ALGHAMDI, Mahfouth, TREUDE, Christoph, WAGNER, Markus
Format:	text
Language:	English
Published:	Institutional Knowledge at Singapore Management University 2019
Subjects:	Heterogeneous software artefacts extractive summarisation humanlike summaries Software Engineering
Online Access:	https://ink.library.smu.edu.sg/sis_research/8872 https://ink.library.smu.edu.sg/context/sis_research/article/9875/viewcontent/gi19.pdf
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Institution:	Singapore Management University
Language:	English

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spelling	sg-smu-ink.sis_research-98752024-06-13T08:58:07Z Toward human-like summaries generated from heterogeneous software artefacts ALGHAMDI, Mahfouth TREUDE, Christoph WAGNER, Markus 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. 2019-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/8872 info:doi/10.1145/3319619.3326814 https://ink.library.smu.edu.sg/context/sis_research/article/9875/viewcontent/gi19.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Heterogeneous software artefacts extractive summarisation humanlike summaries Software Engineering
institution	Singapore Management University
building	SMU Libraries
continent	Asia
country	Singapore Singapore
content_provider	SMU Libraries
collection	InK@SMU
language	English
topic	Heterogeneous software artefacts extractive summarisation humanlike summaries Software Engineering
spellingShingle	Heterogeneous software artefacts extractive summarisation humanlike summaries Software Engineering ALGHAMDI, Mahfouth TREUDE, Christoph WAGNER, Markus Toward human-like summaries generated from heterogeneous software artefacts
description	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.
format	text
author	ALGHAMDI, Mahfouth TREUDE, Christoph WAGNER, Markus
author_facet	ALGHAMDI, Mahfouth TREUDE, Christoph WAGNER, Markus
author_sort	ALGHAMDI, Mahfouth
title	Toward human-like summaries generated from heterogeneous software artefacts
title_short	Toward human-like summaries generated from heterogeneous software artefacts
title_full	Toward human-like summaries generated from heterogeneous software artefacts
title_fullStr	Toward human-like summaries generated from heterogeneous software artefacts
title_full_unstemmed	Toward human-like summaries generated from heterogeneous software artefacts
title_sort	toward human-like summaries generated from heterogeneous software artefacts
publisher	Institutional Knowledge at Singapore Management University
publishDate	2019
url	https://ink.library.smu.edu.sg/sis_research/8872 https://ink.library.smu.edu.sg/context/sis_research/article/9875/viewcontent/gi19.pdf
_version_	1814047603069812736

Toward human-like summaries generated from heterogeneous software artefacts

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