Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/129194
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dc.contributor.authorBaltes, S.-
dc.contributor.authorWagner, M.-
dc.date.issued2020-
dc.identifier.citationProceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO'20). GECCO 2020 Companion, 2020, pp.1923-1925-
dc.identifier.isbn9781450371278-
dc.identifier.urihttp://hdl.handle.net/2440/129194-
dc.description.abstractTo improve software engineering, software repositories have been mined for code snippets and bug fixes. Typically, this mining takes place at the level of files or commits. To be able to dig deeper and to extract insights at a higher resolution, we hereby present an annotated dataset that contains over 7 million edits of code and text on Stack Overflow. Our preliminary study indicates that these edits might be a treasure trove for mining information about fine-grained patches, e.g., for the optimisation of non-functional properties.-
dc.description.statementofresponsibilitySebastian Baltes, Markus Wagner-
dc.language.isoen-
dc.publisherAssociation for Computing Machinery-
dc.rights© 2020 Copyright held by the owner/author(s). Publication rights licensed to ACM.-
dc.source.urihttps://dl.acm.org/doi/proceedings/10.1145/3377929-
dc.subjectSoftware documentation; software evolution; patches; mining software repositories; stack overflow-
dc.titleAn annotated dataset of stack overflow post edits-
dc.typeConference paper-
dc.contributor.conferenceGenetic and Evolutionary Computation Conference (GECCO) (8 Jul 2020 - 12 Jul 2020 : virtual online)-
dc.identifier.doi10.1145/3377929.3398108-
dc.publisher.placeonline-
pubs.publication-statusPublished-
dc.identifier.orcidBaltes, S. [0000-0002-2442-7522]-
dc.identifier.orcidWagner, M. [0000-0002-3124-0061]-
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Computer Science publications

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