首页|Trustworthiness in Enterprise Crowdsourcing: A Taxonomy & Evidence from Data

Trustworthiness in Enterprise Crowdsourcing: A Taxonomy & Evidence from Data

扫码查看
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。

CrowdsourcingContextTaxonomyMalwareBest practicesMeasurement

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

展开 >

Accenture Technol. Labs., Bangalore, India

IIIT-Delhi, Delhi, India

Accenture Technol. Labs., San Jose, CA, USA

IEEE/ACM IEEE International Conference on Software Engineering Companion

Austin(US)

2016 IEEE/ACM 38th IEEE International Conference on Software Engineering Companion

41-50

2016