Optimizing Prioritization of Crowdsourced Test Reports of Web Applications through Image-to-Text Conversion
Lei Xiao,
Yunhuan Wu,
Rongshang Chen
et al.
Abstract:Collating vast test reports is a time-consuming and laborious task in crowdsourced testing. Crowdsourced test reports are usually presented in two ways, one as text and the other as images, which have symmetrical content. Researchers have proposed many text- and image-based methods for prioritizing crowdsourced test reports of mobile applications. However, crowdsourced test reports of web applications typically have clearer textual descriptions of errors but noisier screenshots of errors. This gap motivates us… Show more
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