Geração de Cenários de Testes a partir de Modelos em BPMN para Aplicações Web criadas com Sistemas de Gerenciamento de Processos de Negócio
Resumo
Sistemas de BPM (Business Process Management) têm facilitado a rápida produção de aplicações Web que executam processos expressos em BPMN. O teste automatizado de tais aplicações, no entanto, continua sendo um desafio. Neste artigo, propõe-se uma abordagem para geração de cenários para testes para aplicações Web implementadas com o apoio de BPMS, a partir de modelos BPMN. A abordagem visa abreviar o esforço de construção de scripts de teste e é focada em testes funcionais, usando as ferramentas Selenium e Cucumber. A abordagem foi aplicada a processos encontrados em diferentes repositórios e mostrou-se capaz de gerar os cenários desejados.
Palavras-chave:
BPM, BPMN, Teste funcional, Teste automatizado
Referências
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V. Vieira, P. Tedesco, and A. C. Salgado. Modelos e processos para o desenvolvimento de sistemas sensíveis ao contexto. André Ponce de Leon F. de Carvalho, Tomasz Kowaltowski.(Org.). Jornadas de Atualização em Informática, pages 381–431, 2009.
C. Xu and S.-C. Cheung. Inconsistency detection and resolution for context-aware middleware support. ACM SIGSOFT Software Engineering Notes, 30(5):336–345, 2005.
Z. Yang and D. Li. Iot information service composition driven by user requirement. In Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on, pages 1509–1513. IEEE, 2014.
K. K. F. Yuen and W. Wang. Towards a ranking approach for sensor services using primitive cognitive network process. In Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2014 IEEE 4th Annual International Conference on, pages 344–348. IEEE, 2014.
S. Zhao, Y. Zhang, B. Cheng, and J. Chen. A feedback–corrected collaborative filtering for personalized real–world service recommendation. 9(3):356–369, 2014.
Z. Zheng, S. S. Member, H. Ma, M. R. Lyu, I. King, and S. S. Member. QoS-Aware Web Service Recommendation by Collaborative Filtering. Ieee Transactions on Services Computing, 4(2):140–152, 2011.
T. Buchholz, A. Kupper, and M. Schi ¨ ffers. Quality of Context: What It Is And Why We Need It. Proceedings of the workshop of the HP OpenView University Association, pages 1–14, 2003.
A. Chen. Context-aware collaborative filtering system: predicting the user’s preferences in ubiquitous computing. Proceedings of ACM CHI 2005 Conference on Human Factors in Computing Systems, 2:1110–1111, 2005.
M. Compton, P. Barnaghi, L. Bermudez, R. GarcíA-Castro, O. Corcho, S. Cox, J. Graybeal, M. Hauswirth, C. Henson, A. Herzog, et al. The ssn ontology of the w3c semantic sensor network incubator group. Web Semantics: Science, Services and Agents on the World Wide Web, 17:25–32, 2012.
C. Desrosiers and G. Karypis. A comprehensive survey of neighborhood-based recommendation methods. In Recommender systems handbook, pages 107–144. Springer, 2011.
A. K. Dey, G. D. Abowd, and D. Salber. A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Human-computer interaction, 16(2):97–166, 2001.
Y. Evchina, J. Puttonen, A. Dvoryanchikova, and J. L. M. Lastra. Context-aware knowledge-based middleware for selective information delivery in data-intensive monitoring systems. Engineering Applications of Artificial Intelligence, 43:111–126, 2015.
R. K. Ganti, F. Ye, and H. Lei. Mobile crowdsensing: current state and future challenges. IEEE Communications Magazine, 49(11):32–39, 2011.
P. Gray and D. Salber. Modelling and using sensed context information in the design of interactive applications. Engineering for Human-Computer Interaction, (1):317–335, 2001.
P. Guillemin and P. Friess. Internet of things strategic research roadmap, 2009. [Online. Acessado em 25 jul 2016].
D. Guinard, V. Trifa, S. Karnouskos, P. Spiess, and D. Savio. Interacting with the SOA-based internet of things: Discovery, query, selection, and on-demand provisioning of web services. IEEE Transactions on Services Computing, 3(3):223–235, 2010.
C. A. Henson, J. K. Pschorr, A. P. Sheth, and K. Thirunarayan. Semsos: Semantic sensor observation service. In Collaborative Technologies and Systems, 2009. CTS’09. International Symposium on, pages 44–53. IEEE, 2009.
N. Honle, U.-P. Kappeler, D. Nicklas, T. Schwarz, and M. Grossmann. Benefits of integrating meta data into a context model. In Pervasive Computing and Communications Workshops, 2005. PerCom 2005 Workshops. Third IEEE International Conference on, pages 25–29. IEEE, 2005.
S. Jirka, A. Bröring, and C. Stasch. Discovery mechanisms for the sensor web. Sensors, 9(4):2661–2681, 2009.
G. Judd and P. Steenkiste. Providing Contextual Information to Pervasive Computing Applications. International Conference on Pervasive Computing and Communications, page 133, 2003.
B. K. Kahn, D. M. Strong, and R. Y. Wang. Information Quality Benchmarks: Product and Service Performance. Commun. ACM, 45(4):184–192, 2002.
Y. Kim and K. Lee. A Quality Measurement Method of Context Information in Ubiquitous Environments. 2006 International Conference on Hybrid Information Technology, 2:576–581, 2006.
J. Lei, X. Yang, Y. Liu, Y. Qin, H. Tang, and Z. Zhao. Using physical–level context awareness to improve service ranking in wireless sensor network. Journal of Networks, 7(6):926–934, 2012.
Z. Liu and X. Xu. S-abc-a service-oriented artificial bee colony algorithm for global optimal services selection in concurrent requests environment. In Web Services (ICWS), 2014 IEEE International Conference on, pages 503–509. IEEE, 2014.
P. Lops, M. De Gemmis, and G. Semeraro. Content-based recommender systems: State of the art and trends. In Recommender systems handbook, pages 73–105. Springer, 2011.
W. T. Lunardi, E. De Matos, R. Tiburski, L. A. Amaral, S. Marczak, and F. Hessel. Context-based search engine for industrial IoT: Discovery, search, selection, and usage of devices. IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, 2015-October(July 2016), 2015.
J. McCarthy and S. Buvac. Formalizing context. 1997.
W. Niu, J. Lei, E. Tong, G. Li, L. Chang, Z. Shi, and S. Ci. Context-aware service ranking in wireless sensor networks. Journal of network and systems management, 22(1):50–74, 2014.
N. H. W. NWE, J.-m. BAO, and C. Gang. Flexible user-centric service selection algorithm for internet of things services. The Journal of China Universities of Posts and Telecommunications, 21:64–70, 2014.
OGC. Open geospatial consortium, 2016. [Online. Acessado em 25 jul 2016].
M. I. S. Oliveira, K. S. da Gama, and B. F. Lóscio. Waldo: Serviço para publicação e descoberta de produtores de dados para middleware de cidades inteligentes. XI Simpósio Brasileiro de Sistemas de Informação, 2015.
C. Perera, A. Zaslavsky, P. Christen, M. Compton, C. Liu, and D. Georgakopoulos. Sensor search techniques for sensing as a service architecture for the internet of things. IEEE 14th International Conference on Mobili Data Management, 2013.
C. Perera, A. Zaslavsky, P. Christen, and D. Georgakopoulos. Context aware computing for the internet of things: A survey. IEEE Communications Surveys & Tutorials, 16(1):414–454, 2014.
A. Ranganathan, J. Al-Muhtadi, and R. H. Campbell. Reasoning about uncertain contexts in pervasive computing environments. IEEE Pervasive Computing, 3:62–70, 2004.
S. Sawant. Collaborative Filtering using Weighted BiPartite Graph Projection - A Recommendation System for Yelp. 2013.
K. Sheikh, M. Wegdam, and M. van Sinderen. Quality-of-context and its use for protecting privacy in context aware systems. Journal of Software, 3(3):83–93, 2008.
E. C. G. F. Silva, M. I. S. Oliveira, E. Oliveira, K. Santos, and B. F. L. Um survey sobre plataformas de mediação de dados para internet das coisas. SEMISH – Seminário Integrado de Software e Hardware, 2015.
B. Soediono. Managing context data for smart spaces. Journal of Chemical Information and Modeling, 53(October):160, 1989.
V. Vieira, P. Tedesco, and A. C. Salgado. Modelos e processos para o desenvolvimento de sistemas sensíveis ao contexto. André Ponce de Leon F. de Carvalho, Tomasz Kowaltowski.(Org.). Jornadas de Atualização em Informática, pages 381–431, 2009.
C. Xu and S.-C. Cheung. Inconsistency detection and resolution for context-aware middleware support. ACM SIGSOFT Software Engineering Notes, 30(5):336–345, 2005.
Z. Yang and D. Li. Iot information service composition driven by user requirement. In Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on, pages 1509–1513. IEEE, 2014.
K. K. F. Yuen and W. Wang. Towards a ranking approach for sensor services using primitive cognitive network process. In Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2014 IEEE 4th Annual International Conference on, pages 344–348. IEEE, 2014.
S. Zhao, Y. Zhang, B. Cheng, and J. Chen. A feedback–corrected collaborative filtering for personalized real–world service recommendation. 9(3):356–369, 2014.
Z. Zheng, S. S. Member, H. Ma, M. R. Lyu, I. King, and S. S. Member. QoS-Aware Web Service Recommendation by Collaborative Filtering. Ieee Transactions on Services Computing, 4(2):140–152, 2011.
Publicado
17/05/2017
Como Citar
MOURA, Jéssica; CHARÃO, Andrea; LIMA, João.
Geração de Cenários de Testes a partir de Modelos em BPMN para Aplicações Web criadas com Sistemas de Gerenciamento de Processos de Negócio. In: SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 13. , 2017, Lavras.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2017
.
p. 253-260.
DOI: https://doi.org/10.5753/sbsi.2017.6050.
