Crowdsourced Report Generation via Bug Screenshot Understanding
Quality control is a challenge of crowdsourcing, especially in software testing. As having different levels of skills, some crowdworkers may not complete assigned tasks well. Therefore, it is necessary to propose some auxiliary methods to assist crowdworkers, raising bug report quality. This paper proposes a novel method, namely CroReG, to generate crowdsourcing reports based on bug screenshots. CroReG leverages image understanding techniques to analyze bug screenshots. Image understanding techniques including deep learning and optical character recognition (OCR) techniques are used comprehensively to analyze the screenshots and then CroReG can automatically generate corresponding bug reports. The preliminary experiment results show that CroReG can effectively generate bug reports containing accurate screenshot captions and providing guidance for crowdworkers.
An senior undergraduate student of iSE Lab, Nanjing University.
Tue 12 Nov
Wed 13 Nov
|13:40 - 13:55||Crowdsourced Report Generation via Bug Screenshot Understanding|
Shengcheng YuNanjing University, China
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