Trustworthiness in Enterprise Crowdsourcing: a Taxonomy & evidence from data
September 25, 2018 ยท The Cartographer ยท ๐ 2016 IEEE/ACM 38th International Conference on Software Engineering Companion (ICSE-C)
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"Title-pattern auto-detect: Trustworthiness in Enterprise Crowdsourcing: a Taxonomy & evidence from data"
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Authors
Anurag Dwarakanath, Shrikanth N. C., Kumar Abhinav, Alex Kass
arXiv ID
1809.09477
Category
cs.SE: Software Engineering
Citations
25
Venue
2016 IEEE/ACM 38th International Conference on Software Engineering Companion (ICSE-C)
Last Checked
23 hours ago
Abstract
In this paper we study the trustworthiness of the crowd for crowdsourced software development. Through the study of literature from various domains, we present the risks that impact the trustworthiness in an enterprise context. We survey known techniques to mitigate these risks. We also analyze key metrics from multiple years of empirical data of actual crowdsourced software development tasks from two leading vendors. We present the metrics around untrustworthy behavior and the performance of certain mitigation techniques. Our study and results can serve as guidelines for crowdsourced enterprise software development.
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