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Erschienen in:
2022 | OriginalPaper | Buchkapitel
8. Classification of Crowdsourced Testing Reports
verfasst von : Qing Wang, Zhenyu Chen, Junjie Wang, Yang Feng
Erschienen in: Intelligent Crowdsourced Testing
Verlag: Springer Nature Singapore
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Abstract
In order to attract workers, testing tasks are often financially compensated, especially for these failed reports. Under this context, workers may submit thousands of test reports. However, these test reports often have many false positives, i.e., a test report marked as failed that actually involves correct behavior or behavior that was considered outside of the studied software system. Project managers or testers need to manually verify whether a submitted test report reveals fault—-
true fault. However, such process is tedious and cumbersome, given the high volume workload. Our observation on industrial crowdsourced testing platforms shows that, approximately 100 projects are delivered per month from a typical platform, and more than 1000 test reports are submitted per day on average.