Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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University of Hertfordshire

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2024Mobile-UI-Repair: a deep learning based UI smell detection technique for mobile user interface4citations

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Chart of shared publication
Ali, Asif
1 / 8 shared
Aldakheel, Eman Abdullah
1 / 1 shared
Khafaga, Doaa
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Khan, Zohaib Ahmad
1 / 1 shared
Xia, Yuanqing
1 / 1 shared
Navid, Qamar
1 / 1 shared
Chart of publication period
2024

Co-Authors (by relevance)

  • Ali, Asif
  • Aldakheel, Eman Abdullah
  • Khafaga, Doaa
  • Khan, Zohaib Ahmad
  • Xia, Yuanqing
  • Navid, Qamar
OrganizationsLocationPeople

article

Mobile-UI-Repair: a deep learning based UI smell detection technique for mobile user interface

  • Ali, Asif
  • Aldakheel, Eman Abdullah
  • Khafaga, Doaa
  • Khan, Javed Ali
  • Khan, Zohaib Ahmad
  • Xia, Yuanqing
  • Navid, Qamar
Abstract

The graphical user interface (GUI) in mobile applications plays a crucial role in connecting users with mobile applications. GUIs often receive many UI design smells, bugs, or feature enhancement requests. The design smells include text overlap, component occlusion, blur screens, null values, and missing images. It also provides for the behavior of mobile applications during their usage. Manual testing of mobile applications (app as short in the rest of the document) is essential to ensuring app quality, especially for identifying usability and accessibility that may be missed during automated testing. However, it is time-consuming and inefficient due to the need for testers to perform actions repeatedly and the possibility of missing some functionalities. Although several approaches have been proposed, they require significant performance improvement. In addition, the key challenges of these approaches are incorporating the design guidelines and rules necessary to follow during app development and combine the syntactical and semantic information available on the development forums. In this study, we proposed a UI bug identification and localization approach called Mobile-UI-Repair (M-UI-R). M-UI-R is capable of recognizing graphical user interfaces (GUIs) display issues and accurately identifying the specific location of the bug within the GUI. M-UI-R is trained and tested on the history data and also validated on real-time data. The evaluation shows that the average precision is 87.7% and the average recall is 86.5% achieved in the detection of UI display issues. M-UI-R also achieved an average precision of 71.5% and an average recall of 70.7% in the localization of UI design smell. Moreover, a survey involving eight developers demonstrates that the proposed approach provides valuable support for enhancing the user interface of mobile applications. This aids developers in their efforts to fix bugs.

Topics
  • impedance spectroscopy