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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/124530
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dc.contributor.authorAlghamdi, M.-
dc.contributor.authorTreude, C.-
dc.contributor.authorWagner, M.-
dc.date.issued2019-
dc.identifier.citationProceedings of the 2019 Genetic and Evolutionary Computation Conference (GECCO 2019 Companion), 2019, pp.1701-1702-
dc.identifier.isbn1450367488-
dc.identifier.isbn9781450367486-
dc.identifier.urihttp://hdl.handle.net/2440/124530-
dc.description.abstractAutomatic 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.-
dc.description.statementofresponsibilityMahfouth Alghamdi, Christoph Treude, Markus Wagner-
dc.language.isoen-
dc.publisherAssociation for Computing Machinery-
dc.rights© 2019 Association for Computing Machinery.-
dc.source.urihttps://dl.acm.org/doi/proceedings/10.1145/3319619-
dc.subjectSoftware and its engineering; Search-based software engineering-
dc.titleToward human-like summaries generated from heterogeneous software artefacts-
dc.typeConference paper-
dc.contributor.conferenceGenetic and Evolutionary Computation Conference (GECCO) (13 Jul 2019 - 17 Jul 2019 : Prague, Czech Republic)-
dc.identifier.doi10.1145/3319619.3326814-
dc.publisher.placeNew York-
dc.relation.granthttp://purl.org/au-research/grants/arc/DE160100850-
pubs.publication-statusPublished-
dc.identifier.orcidTreude, C. [0000-0002-6919-2149]-
dc.identifier.orcidWagner, M. [0000-0002-3124-0061]-
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Computer Science publications

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