Crowdsourced Report Generation via Bug Screenshot Understanding
Wed 13 Nov 2019 13:40 - 13:55 at South Park - Student Research Competition - Selected Presentations (Undergraduate) Chair(s): Jie M. Zhang, Jin L.C. Guo
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 - 15:20: Student Research Competition - Student Research Competition - Selected Presentations (Undergraduate) at South Park Chair(s): Jie M. ZhangUniversity College London, UK, Jin L.C. GuoMcGill University | ||||||||||||||||||||||||||||||||||||||||||
13:40 - 13:55 | Crowdsourced Report Generation via Bug Screenshot Understanding Shengcheng YuNanjing University, China | |||||||||||||||||||||||||||||||||||||||||
13:55 - 14:10 | Towards Comprehensible Representation of Controllers using Machine Learning Gargi BalasubramaniamBirla Institute of Technology and Science, Pilani, K K Birla Goa Campus | |||||||||||||||||||||||||||||||||||||||||
14:10 - 14:25 | Empirical Study of Python Call Graph Li YuNanjing University | |||||||||||||||||||||||||||||||||||||||||
14:25 - 14:40 | A Machine Learning based Approach to Identify SQL Injection Vulnerabilities Kevin ZhangWayne State University | |||||||||||||||||||||||||||||||||||||||||
14:40 - 14:55 | Boosting Neural Commit Message Generation with Code Semantic Analysis Shuyao JiangFudan University |