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[EN] Companies are facing constant pressure towards shorter release cycles while still maintaining a high level of quality. Agile development, continuous integration and testing are commonly used quality assurance techniques applied in industry. Increasing the level of test automation is a key ingredient to address the short release cycles. Testing at the graphical user interface (GUI) level is challenging to automate, and therefore many companies still do this manually. To help find solutions for better GUI test automation, academics are researching scriptless GUI testing to complement the script-based approach. In order to better match industrial problems with academic results, more academia-industry collaborations for case-based evaluations are needed. This paper describes such an initiative to improve, transfer and integrate an academic scriptless GUI testing tool TESTAR into the CI pipeline of a Spanish company Prodevelop. The paper describes the steps taken, the outcome, the challenges, and some lessons learned for successful industry-academia collaboration.
This work has been funded through the ITEA3 TESTOMAT project (www.testomatproject.eu), the EU H2020 DECODER project (www.decoderproject.eu), the EU H2020 iv4XR project (iv4xr-project.eu) and the ITEA3 IVVES project (ivves.weebly.com).
GUI level, Automated testing, CI, TESTAR, LENGUAJES Y SISTEMAS INFORMATICOS, Technology transfer
GUI level, Automated testing, CI, TESTAR, LENGUAJES Y SISTEMAS INFORMATICOS, Technology transfer
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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