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All issues Volume 40 / No 4 (August 2022) JNWPU, 40 4 (2022) 804-811 References
Open Access
Issue
JNWPU
Volume 40, Number 4, August 2022
Page(s) 804 - 811
DOI https://doi.org/10.1051/jnwpu/20224040804
Published online 30 September 2022
  1. KONG P, LI L, GAO J, et al. Automated testing of Android apps: a systematic literature review[J]. IEEE Trans on Reliability, 2018, 68(1): 45–66 [Google Scholar]
  2. TRAMONTANA P, AMALFITANO D, AMATUCCI N, et al. Automated functional testing of mobile applications: a systematic mapping study[J]. Software Quality Journal, 2019, 27(1): 149–201 [Article] [CrossRef] [Google Scholar]
  3. LINARES-VÁSQUEZ M, BERNAL-CÁRDENAS C, MORAN K, et al. How do developers test android applications?[C]//2017 IEEE International Conference on Software Maintenance and Evolution, 2017: 613-622 [Google Scholar]
  4. RUBINOV K, BARESI L. What are we missing when testing our android apps?[J]. Computer, 2018, 51(4): 60–68 [Article] [Google Scholar]
  5. Appium-automation for apps[EB/OL]. (2018-10-05)[2021-08-18]. http://appium.io/dols/cn/about-appium/intro [Google Scholar]
  6. Eyeautomate-visual script runner[EB/OL]. (2019-02-08)[2021-08-12]. https://eyeautomate.com/eyeautomate [Google Scholar]
  7. AMALFITANO D, RICCIO V, AMATUCCI N, et al. Combining automated GUI exploration of android apps with capture and replay through machine learning[J]. Information and Software Technology, 2019, 105:95–116 [Article] [CrossRef] [Google Scholar]
  8. GUO J, LI S, LOU J G, et al. SARA: self-replay augmented record and replay for android in industrial cases[C]//Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis, 2019: 90-100 [Google Scholar]
  9. GU T, SUN C, MA X, et al. Practical GUI testing of Android applications via model abstraction and refinement[C]//2019 IEEE/ACM 41st International Conference on Software Engineering, 2019: 269-280 [Google Scholar]
  10. SALIHU I A, IBRAHIM R, AHMED B S, et al. AMOGA: a static-dynamic model generation strategy for mobile apps testing[J]. IEEE Access, 2019, 7: 17158–17173 [Article] [CrossRef] [Google Scholar]
  11. BEHRANG F, ORSO A. Test migration between mobile apps with similar functionality[C]//2019 34th IEEE/ACM International Conference on Automated Software Engineering, 2019: 54-65 [Google Scholar]
  12. PAN M, XU T, PEI Y, et al. GUI-guided test script repair for mobile apps[J]. IEEE Trans on Software Engineering, 2022, 48(3): 910–929 [Google Scholar]
  13. CRACIUNESCU M, MOCANU S, DOBRE C, et al. Robot based automated testing procedure dedicated to mobile devices[C]//2018 25th International Conference on Systems, Signals and Image Processing, 2018: 1-4 [Google Scholar]
  14. MAO K, HARMAN M, JIA Y. Robotic testing of mobile APPS for truly black-box automation[J]. IEEE Software, 2017, 34(2): 11–16 [Article] [CrossRef] [Google Scholar]
  15. BANERJEE D, YU K. Robotic arm-based face recognition software test automation[J]. IEEE Access, 2018, 6: 37858–37868 [Article] [CrossRef] [Google Scholar]
  16. NASS M, ALÉGROTH E, FELDT R. Why many challenges with GUI test automation(will) remain[J]. Information and Software Technology, 2021, 138: 106625[Article] [CrossRef] [Google Scholar]
  17. DEKA B, HUANG Z, FRANZEN C, et al. RICO: a mobile app dataset for building data-driven design applications[C]//Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology, 2017: 845-854 [Google Scholar]
  18. BOCHKOVSKIY A, WANG C Y, LIAO H Y M. YOLOv4: Optimal speed and accuracy of object detection[J/OL]. (2020-04-05)[2021-08-12]. https://arxiv.org/abs/2004.10934 [Google Scholar]
  19. LIU W, ANGUELOV D, ERHAN D, et al. SSD: single shot multibox detector[C]//European Conference on Computer Vision, Cham, 2016: 21-37 [Google Scholar]
  20. LIN T Y, GOYAL P, GIRSHICK R, et al. Focal loss for dense object detection[C]//Proceedings of the IEEE International Conference on Computer Vision, 2017: 2980-2988 [Google Scholar]
  21. CHEN C, SU T, MENG G, et al. From UI design image to GUI skeleton: a neural machine translator to bootstrap mobile GUI implementation[C]//Proceedings of the 40th International Conference on Software Engineering. 2018: 665-676 [Google Scholar]
  22. MORAN K, BERNAL-CÁRDENAS C, CURCIO M, et al. Machine learning-based prototyping of graphical user interfaces for mobile apps[J]. IEEE Trans on Software Engineering, 2018, 46(2): 196–221 [Google Scholar]
  23. MASCI J, MEIER U, CIRESAN D, et al. Stacked convolutional auto-encoders for hierarchical feature extraction[C]//International Conference on Artificial Neural Networks, Berlin, Heidelberg, 2011: 52-59 [Google Scholar]

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