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arXiv 1809.09477cs.SE
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企业众包中的可信度:一个分类学&来自数据的证据

Trustworthiness in Enterprise Crowdsourcing: a Taxonomy & evidence from data

Anurag Dwarakanath, Shrikanth N. C., Kumar Abhinav, Alex Kass

摘要:

在本文中,我们研究了众包软件开发的人群的可信度。通过对各个领域的文献的研究,我们提出了在企业环境中影响可信度的风险。我们调查已知的技术来减轻这些风险。我们还分析了来自两家领先供应商的实际众包软件开发任务的多年经验数据的关键指标。我们提出了不值得信赖的行为和某些缓解技术的性能的指标。我们的研究和结果可以作为众包企业软件开发的指导方针。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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