Generating descriptions for screenshots to assist crowdsourced testing

Di Liu, Xiaofang Zhang, Yang Feng, James A. Jones
2018 2018 IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER)  
Crowdsourced software testing has been shown to be capable of detecting many bugs and simulating real usage scenarios. As such, it is popular in mobile-application testing. However in mobile testing, test reports often consist of only some screenshots and short text descriptions. Inspecting and understanding the overwhelming number of mobile crowdsourced test reports becomes a time-consuming but inevitable task. The paucity and potential inaccuracy of textual information and the welldefined
more » ... enshots of activity views within mobile applications motivate us to propose a novel technique to assist developers in understanding crowdsourced test reports by automatically describing the screenshots. To reach this goal, in this paper, we propose a fully automatic technique to generate descriptive words for the well-defined screenshots. We employ the test reports written by professional testers to build up language models. We use the computer-vision technique, namely Spatial Pyramid Matching (SPM), to measure similarities and extract features from the screenshot images. The experimental results, based on more than 1000 test reports from 4 industrial crowdsourced projects, show that our proposed technique is promising for developers to better understand the mobile crowdsourced test reports.
doi:10.1109/saner.2018.8330246 dblp:conf/wcre/LiuZFJ18 fatcat:us43klehgzhsrkx7yksyicbeei