Translation from layout-based to visual android test scripts: An empirical evaluation
2021 (English)In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 171, article id 110845Article in journal (Refereed) Published
Abstract [en]
Mobile GUI tests can be classified as layout-based – i.e. using GUI properties as locators – or Visual – i.e. using widgets’ screen captures as locators –. Visual test scripts require significant maintenance efforts to be kept aligned with the tested application as it evolves or it is ported to different devices. This work aims to conceptualize a translation-based approach to automatically derive Visual tests from existing layout-based counterparts or repair them when graphical changes occur, and to develop a tool that implements and validates the approach. We present TOGGLE, a tool that translates Espresso layout-based tests for Android apps to Visual tests that conform to either SikuliX, EyeAutomate, or a combination of the two tools’ syntax. An experiment is conducted to measure the precision of the translation approach, which is evaluated on maintenance tasks triggered by graphical changes due to device diversity. Our results demonstrate the feasibility of a translation-based approach, show that script portability to different devices is improved (from 32% to 93%), and indicate that translation can repair up to 90% of Visual locators in failing tests. GUI test translation mitigates challenges with Visual tests like maintenance effort and portability, enabling their wider use in industrial practice. © 2020 Elsevier Inc.
Place, publisher, year, edition, pages
Elsevier Inc. , 2021. Vol. 171, article id 110845
Keywords [en]
Empirical software engineering, GUI testing, Mobile testing, Software validation, Graphical user interfaces, Repair, Testing, Android apps, Device diversities, Empirical evaluations, Industrial practices, Maintenance efforts, Maintenance tasks, Screen capture, Test scripts, Android (operating system)
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-20572DOI: 10.1016/j.jss.2020.110845ISI: 000592499600007Scopus ID: 2-s2.0-85092452309OAI: oai:DiVA.org:bth-20572DiVA, id: diva2:1478703
2020-10-232020-10-232021-01-07Bibliographically approved