Análise exploratória de dados geográficos de componente nativo para aplicativos híbridos
Abstract
The development of hybrid mobile applications is accelerated and low cost, favoring the production of multiplatform prototypes. However, hybrid development can compromise the performance of components that utilize native resources. In order to validate the data collected by a geolocation feature available for the Ionic framework, an Android mobile application for component data collection and an exploratory analysis of the collected data, and its proximity to the location data of a native solution, were developed. Thus the Haversine formula was used to evaluate the data quality, which presented considerable distance between the records.
Keywords:
mobile apps, hybrids, Ionic framework, Android
References
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Christie, T. (2019). Django rest framework.
Dabbish, L., Stuart, C., Tsay, J., and Herbsleb, J. (2012). Social coding in github: Trans- parency and collaboration in an open software repository. In Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work, CSCW ’12, pages 1277– 1286, New York, NY, USA. ACM.
Google (2019). Pol´ıtica de privacidade – privacidade e termos.
IBM (2012). Native, web or hybrid mobile-app development. White Paper. Ionic (2019). Ionic native - ionic documentation.
Kirwan, M., Vandelanotte, C., Fenning, A., and Duncan, M. J. (2013). Diabetes self- management smartphone application for adults with type 1 diabetes: randomized con- trolled trial. Journal of medical Internet research, 15(11):e235.
Lane, N. D., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., and Campbell, A. T. (2010). A survey of mobile phone sensing. IEEE Communications magazine, 48(9):140–150.
Malavolta, I., Ruberto, S., Soru, T., and Terragni, V. (2015). Hybrid mobile apps in the google play store: An exploratory investigation. In Proceedings of the second acm international conference on mobile software engineering and systems, pages 56–59. IEEE Press.
Robusto, C. C. (1957). The cosine-haversine formula. The American Mathematical Monthly, 64(1):38–40.
Vasilescu, B., Yu, Y., Wang, H., Devanbu, P., and Filkov, V. (2015). Quality and producti- vity outcomes relating to continuous integration in github. In Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, ESEC/FSE 2015, pages 805–816, New York, NY, USA. ACM.
Wang, N., Chen, X., Song, G., Lan, Q., and Parsaei, H. R. (2017). Design of a new mobile-optimized remote laboratory application architecture for m-learning. IEEE Transactions on Industrial Electronics, 64(3):2382–2391.
Published
2019-11-22
How to Cite
DE CASTRO, Bruno M. N; OLIVEIRA, Fábio Henrique M..
Análise exploratória de dados geográficos de componente nativo para aplicativos híbridos. In: REGIONAL SCHOOL ON INFORMATICS OF GOIÁS (ERI-GO), 7. , 2019, Goiânia.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
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p. 283-291.
