A Dashboard for System Trustworthiness Properties Evaluation
Resumo
Understanding the trustworthiness of a cloud system is a difficult task, because it encompasses a large diversity of properties such as security, privacy, performance, among others. Evaluating and improving the system regarding trustworthiness require the analysis of huge data considering their historical status. The goal of this paper is to present a dashboard developed for the visualization of these properties, the relationship among them and their relevance in the composition of a trustworthiness score over usage time.
Palavras-chave:
trustworthiness, dashboard, quality model
Referências
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Bass, L., Clements, P., and Kazman, R. (2003). Software architecture inpractice. Addison-Wesley Professional.
Basso, T., de Oliveira Silva, H., Montecchi, L., de França, B. B. N.,and de Oliveira Moraes, R. L. (2019a). Towards trustworthy cloud service selection:monitoring and as ing data privacy. In Anais do XX Workshop de Testes e Tolerânciaa Falhas, pages 6-19. SBC.
Basso, T., Matsunaga, R., Moraes, R., and Antunes, N. (2016).Challenges on anonymity, privacy, and big data. In Dependable Computing (LADC),2016 Seventh Latin-American Symposium on, pages 164-171. IEEE.
Basso, T., Silva, H., and Moraes, R. (2019b). On the use of qualitymodels to characterize trustworthiness properties. In International Workshop onSoftware Engineering for Resilient Systems, pages 147-155. Springer.
Casare, A., Basso, T., and Moraes, R. (2020). Trust metrics to measurewebsite user experience. In The Thirteenth International Conference on Advances inComputer-Human Interactions, pages 1-8. Iaria.
D. Miller (2017). Think cloud compliance: anintroduction to cloud computing for legal and compliance professionals.https://download.microsoft.com/download/0/D/6/0D68 AE95-6414-4074-B4B8-34039831 E2BF/Introduction-to-Cloud-Computing-for-Legal-and-Compliance-Professionals.pdf.
Dyczkowski, M., Korczak, J., and Dudycz, H. (2014).Miulti-criteria evaluation of the intelligent dashboard for sme managers based on scorecard framework. In the 2014 Federated Conference on Computer Science andInformation Systems, pages 1147-1155.
Faculty of Technology (2020). Softwareengineering department. URL: https://www.ft.unicamp.br/pt-br/laboratorio/sistemas-de-informação-e-engenharia-de-sofware-seis [Last access on May, 2020].
Ferreira, R., Martiniao, A., and Sassi, R. (2016). Dashboard inteligentepara apoio à tomada de decisão em empresa de courier. Revista Gestão & Tecnologia,pages 39-72.
Gesing, S., Atkinson, M., Filgueira, R., Taylor, I, Jones, A.,Stankovski, V., Liew, C. S., Spinuso, A., Terstyanszky, G., and Kacsuk, P. (2014).Workflows in a dashboard: a new generation of usability. In 2014 9th Workshop onWorkflows in Support of Large-Scale Science, pages 82-93. IEEE.
IBM Corporation (2006). An architectural blueprint for autonomiccomputing. IBM White Paper, 31:1-6.
ISO (2014). International organization for standardization. systems andsoftware engineering — systems and software quality requirements and evaluation(square) — guide to square.
Luzzardi, P. R. G. (2003). Critério de avaliação de técnicas de visualizaçãode informações hierárquicas. In Tese de Doutorado. Programa de Pós-Graduação emComputação. UFRGS, Brasil.
Magdalena, R., Ruldeviyani, Y., Sensuse, D. I., and Bernando, C.(2019). Methods to enhance the utilization of business intelligence dashboard byintegration of evaluation and user testing. In 2019 3rd International Conference onInformatics and Computational Sciences (ICICOS), pages 1-6. IEEE.
Mell, P. and Grance, T. (2011). The nist definition of cloudcomputing recommendations of the national institute of standards and technology.National Institute of Standards and Technology, Information Technology Laboratory,145:7.
Muriithi, G. and Kotzé, J. (2013). A conceptual framework fordelivering cost effective business intelligence solutions as a service. In the SouthAfrican Institute for Computer Scientists and Information Technologists Conference,pages 96-100.
Nielsen, J. (1994). Heuristic Evaluation. John Wiley Sons, Inc.
Nielsen, J. and Mack, R. L. (1994). Usability Inspection Methods.John Wiley Sons, Inc.
Smuts, M., Scholtz, B., and Calitz, A. (2015). Design guidelinesfor business intelligence tools for novice users. In Proceedings of the 2015Annual Research Conference on South African Institute of Computer Scientists andInformation Technologists, pages 1-15.
Veríssimo, P. E., Neves, N. F., and Correia, M. P. (2003).Intrusion-tolerant architectures: Concepts and design. In Architecting dependablesystems, pages 3-36. Springer.
Zuk, T., Schlesier, L., Neumann, P., Hancock, M. S., and Carpendale, S.(2006). Heuristics for information visualization evaluation. In the 2006 AVI workshop on BEyond time and errors: novel evaluation methods for information visualization,pages 55-60.
Bass, L., Clements, P., and Kazman, R. (2003). Software architecture inpractice. Addison-Wesley Professional.
Basso, T., de Oliveira Silva, H., Montecchi, L., de França, B. B. N.,and de Oliveira Moraes, R. L. (2019a). Towards trustworthy cloud service selection:monitoring and as ing data privacy. In Anais do XX Workshop de Testes e Tolerânciaa Falhas, pages 6-19. SBC.
Basso, T., Matsunaga, R., Moraes, R., and Antunes, N. (2016).Challenges on anonymity, privacy, and big data. In Dependable Computing (LADC),2016 Seventh Latin-American Symposium on, pages 164-171. IEEE.
Basso, T., Silva, H., and Moraes, R. (2019b). On the use of qualitymodels to characterize trustworthiness properties. In International Workshop onSoftware Engineering for Resilient Systems, pages 147-155. Springer.
Casare, A., Basso, T., and Moraes, R. (2020). Trust metrics to measurewebsite user experience. In The Thirteenth International Conference on Advances inComputer-Human Interactions, pages 1-8. Iaria.
D. Miller (2017). Think cloud compliance: anintroduction to cloud computing for legal and compliance professionals.https://download.microsoft.com/download/0/D/6/0D68 AE95-6414-4074-B4B8-34039831 E2BF/Introduction-to-Cloud-Computing-for-Legal-and-Compliance-Professionals.pdf.
Dyczkowski, M., Korczak, J., and Dudycz, H. (2014).Miulti-criteria evaluation of the intelligent dashboard for sme managers based on scorecard framework. In the 2014 Federated Conference on Computer Science andInformation Systems, pages 1147-1155.
Faculty of Technology (2020). Softwareengineering department. URL: https://www.ft.unicamp.br/pt-br/laboratorio/sistemas-de-informação-e-engenharia-de-sofware-seis [Last access on May, 2020].
Ferreira, R., Martiniao, A., and Sassi, R. (2016). Dashboard inteligentepara apoio à tomada de decisão em empresa de courier. Revista Gestão & Tecnologia,pages 39-72.
Gesing, S., Atkinson, M., Filgueira, R., Taylor, I, Jones, A.,Stankovski, V., Liew, C. S., Spinuso, A., Terstyanszky, G., and Kacsuk, P. (2014).Workflows in a dashboard: a new generation of usability. In 2014 9th Workshop onWorkflows in Support of Large-Scale Science, pages 82-93. IEEE.
IBM Corporation (2006). An architectural blueprint for autonomiccomputing. IBM White Paper, 31:1-6.
ISO (2014). International organization for standardization. systems andsoftware engineering — systems and software quality requirements and evaluation(square) — guide to square.
Luzzardi, P. R. G. (2003). Critério de avaliação de técnicas de visualizaçãode informações hierárquicas. In Tese de Doutorado. Programa de Pós-Graduação emComputação. UFRGS, Brasil.
Magdalena, R., Ruldeviyani, Y., Sensuse, D. I., and Bernando, C.(2019). Methods to enhance the utilization of business intelligence dashboard byintegration of evaluation and user testing. In 2019 3rd International Conference onInformatics and Computational Sciences (ICICOS), pages 1-6. IEEE.
Mell, P. and Grance, T. (2011). The nist definition of cloudcomputing recommendations of the national institute of standards and technology.National Institute of Standards and Technology, Information Technology Laboratory,145:7.
Muriithi, G. and Kotzé, J. (2013). A conceptual framework fordelivering cost effective business intelligence solutions as a service. In the SouthAfrican Institute for Computer Scientists and Information Technologists Conference,pages 96-100.
Nielsen, J. (1994). Heuristic Evaluation. John Wiley Sons, Inc.
Nielsen, J. and Mack, R. L. (1994). Usability Inspection Methods.John Wiley Sons, Inc.
Smuts, M., Scholtz, B., and Calitz, A. (2015). Design guidelinesfor business intelligence tools for novice users. In Proceedings of the 2015Annual Research Conference on South African Institute of Computer Scientists andInformation Technologists, pages 1-15.
Veríssimo, P. E., Neves, N. F., and Correia, M. P. (2003).Intrusion-tolerant architectures: Concepts and design. In Architecting dependablesystems, pages 3-36. Springer.
Zuk, T., Schlesier, L., Neumann, P., Hancock, M. S., and Carpendale, S.(2006). Heuristics for information visualization evaluation. In the 2006 AVI workshop on BEyond time and errors: novel evaluation methods for information visualization,pages 55-60.
Publicado
07/12/2020
Como Citar
CAMARGO, Diego; GAIA, Felipe Nunes; BASSO, Tania; MORAES, Regina Lúcia de Oliveira.
A Dashboard for System Trustworthiness Properties Evaluation. In: WORKSHOP DE TESTES E TOLERÂNCIA A FALHAS (WTF), 21. , 2020, Rio de Janeiro.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 55-68.
ISSN 2595-2684.
DOI: https://doi.org/10.5753/wtf.2020.12487.
