Abstract
As new versions of an app or other software are checked into a version control system, bugs can be introduced that are undetected by regression testing. Apps or software that have visual elements (VE) or components are particularly susceptible because regression tests usually do not include comparisons of viewports as seen by a user. This disclosure describes techniques to detect bugs in successive versions of a software under test by translating visual elements into quantitative metrics; by detecting anomalies, e.g., sudden spikes, cliffs, or drops, in quantitative metrics; and by mapping the detected anomaly to particular versions of constituent module(s) of the software. The techniques can advantageously identify bugs in pre-production software, such that bugs in production software are reduced. New bug alerts can be added by simply adding the corresponding quantitative metric, without changes to client/server modules.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Cheng, Shu-Wei; Kennell, Grant; and Wang, Fei, "Detection of Anomalies in Visual Elements", Technical Disclosure Commons, (June 25, 2024)
https://www.tdcommons.org/dpubs_series/7134