Abstract
Nowadays the technology is being created and adapted to satisfy the user necessities. Among them, obtaining information as fast as possible. Google knows how to meet this demand developing and offering new services that provide the requested information quickly. Google technology can be used to develop products using the Google App Engine (GAE). In order to manipulate the data, GAE uses the Google Query Language (GQL), a SQL-like language, that has been designed to provide a solution to the necessity of having super-fast access to data warehouses. The quality of the developed products is essential and therefore, testing them is mandatory. In this paper, we propose the use of mutation testing to detect faults during the development of applications that use GQL. With this goal, we introduce a set of specific mutation operators for GQL.
Paper partially funded by the Spanish MINECO-FEDER (grant number DArDOS, TIN2015-65845-C3-1-R, grant number FAME RTI2018-093608-B-C31 and RTI2018-093608-B-C33); the Region of Madrid (grant number FORTE-CM, S2018/TCS-4314).
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References
Barry, P.: Doing IT the app engine way. Linux J. 2010(197), 1 (2010). ISSN 1075–3583
DeMillo, R.A., Lipton, R.J., Sayward, F.G.: Hints on test data selection: help for the practicing programmer. Computer 11(4), 34–41 (1978). ISSN 0018–9162
Gómez-Abajo, P., et al.: A tool for domain-independent model mutation. Sci. Comput. Program. 163, 85–92 (2018)
Google: Google App Engine.. https://cloud.google.com/appengine/docs/. Accessed Oct 2019
Google. Google App Engine: Structuring Data for Strong consistency. https://cloud.google.com/appengine/docs/standard/java/datastore/structuring_for_strong_consistency. Accessed Oct 2019
Google. Google Cloud Patform. https://cloud.google.com/docs/. Accessed Oct 2019
Google. Google Query Language in Google App Engine. https://cloud.google.com/appengine/docs/standard/python/datastore/gqlreference. Accessed Oct 2019
Google. Pick strong consistency. https://cloud.google.com/blog/products/gcp/why-you-should-pick-strong-consistency-whenever-possible. Accessed Oct 2019
Gutiérrez-Madroñal, L., García-Domínguez, A., Medina-Bulo, I.: Evolutionary mutation testing for IoT with recorded and generated events. Softw. Pract. Exper. 49(4), 640–672 (2019)
Gutiérrez-Madroñal, L., Medina-Bulo, I., Domínguez-Jiménez, J.J.: Evaluation of EPL mutation operators with the MuEPL mutation system. Expert Syst. Appl. 116, 78–95 (2019). ISSN 0957–4174
Gutiérrez-Madroñal, L., et al.: Mutation testing of event processing queries. In: 2012 IEEE 23rd International Symposium on Software Reliability Engineering, pp. 21–30 (2012)
Hamlet, R.G.: Testing programs with the aid of a compiler. IEEE Trans. Software Eng. SE 3(4), 279–290 (1977). ISSN 2326–3881
Hees, J., Bauer, R., Folz, J., Borth, D., Dengel, A.: An evolutionary algorithm to learn SPARQL queries for source-target-pairs. In: Blomqvist, E., Ciancarini, P., Poggi, F., Vitali, F. (eds.) EKAW 2016. LNCS (LNAI), vol. 10024, pp. 337–352. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-49004-5_22
Hierons, R.M., Merayo, M.G., Núñez, M.: An extended framework for passive asynchronous testing. J. Log. Algebraic Methods Program. 86(1), 408–424 (2017)
Jia, Y., Harman, M.: An analysis and survey of the development of mutation testing. IEEE Trans. Software Eng. 37(5), 649–678 (2011). ISSN 2326–3881
Merayo, M.G., Hierons, R.M., Núñez, M.: A tool supported methodology to passively test asynchronous systems with multiple users. Inf. Softw. Technol. 104, 162–178 (2018)
Merayo, M.G., Hierons, R.M., Núñez, M.: Passive testing with asynchronous communications and timestamps. Distrib. Comput. 31(5), 327–342 (2018). ISSN 1432–0452
Tuya, J., Suárez-Cabal, M.J., la Riva, C.: Mutating database queries. Inf. Softw. Technol. 49(4), 398–417 (2007). ISSN 0950–5849
Vázquez-Ingelmo, A., Cruz-Benito, J., García-Peñalvo, F.J.: Improving the OEEU’s data-driven technological ecosystem’s interoperability with GraphQL. In: Proceedings of the 5th International Conference on Technological Ecosystems for Enhancing Multiculturality, pp. 89:1–89:8. ACM, Cádiz (2017)
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Gutiérrez-Madroñal, L., Medina-Bulo, I., Merayo, M.G. (2020). Mutation Operators for Google Query Language. In: Sitek, P., Pietranik, M., Krótkiewicz, M., Srinilta, C. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Communications in Computer and Information Science, vol 1178. Springer, Singapore. https://doi.org/10.1007/978-981-15-3380-8_31
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DOI: https://doi.org/10.1007/978-981-15-3380-8_31
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