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Big data = big insights?: operationalising brooks' law in a massive GitHub data set.

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Title: Big data = big insights?: operationalising brooks' law in a massive GitHub data set.
Authors: Gote, Christoph1, cgote@ethz.ch, Mavrodiev, Pavlin1, pmavrodiev@ethz.ch, Schweitzer, Frank1, fschweitzer@ethz.ch, Scholtes, Ingo2, ingo.scholtes@uni-wuerzburg.de
Source: ICSE: International Conference on Software Engineering; 2022, p262-273, 12p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 185195875
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PubType: Conference
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  Data: Big data = big insights?: operationalising brooks' law in a massive GitHub data set.
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1145/3510003.3510619
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      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 262
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      – TitleFull: Big data = big insights?: operationalising brooks' law in a massive GitHub data set.
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            NameFull: Gote, Christoph
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            NameFull: Mavrodiev, Pavlin
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            NameFull: Schweitzer, Frank
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            – D: 01
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              Text: 2022
              Type: published
              Y: 2022
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            – TitleFull: ICSE: International Conference on Software Engineering
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