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Data Quality Model-Based Testing of Information Systems: Two-Level Testing of the Insurance System

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Information Technology for Management: Towards Business Excellence (ISM 2020, FedCSIS-IST 2020)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 413))

Abstract

In order to develop reliable software, its operating must be verified for all possible cases of use. This can be achieved, at least partly, by means of a model-based testing (MBT), by establishing tests that check all conditions covered by the model. This paper presents a Data Quality Model-based Testing (DQMBT) using the data quality model (DQ-model) as a testing model. The DQ-model contains definitions and conditions for data objects to consider the data object as correct. The proposed testing approach allows complete testing of the conformity of the data to be entered and the data already stored in the database. The data to be entered shall be verified by means of predefined pre-conditions, while post-conditions verify the allocation of the data into the database. The paper demonstrates the application of the proposed solution to the insurance system, concluding that it is able to identify previously undetected defects even after years of operating the IS. Therefore, the proposed solution can be considered as an effective complementary testing approach capable to improve the quality of an information system significantly. In the context of this study, we also address the MBT approach and the main factors affecting its popularity and identify the most popular ways of classifying MBT approaches.

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References

  1. Garousi, V., Elberzhager, F.: Test automation: not just for test execution. IEEE Softw. 34(2), 90–96 (2017). https://doi.org/10.1109/MS.2017.34

    Article  Google Scholar 

  2. Saeed, A., Ab Hamid, S.H., Mustafa, M.B.: The experimental applications of search-based techniques for model-based testing: taxonomy and systematic literature review. Appl. Soft Comput. 49, 1094–1117 (2016)

    Article  Google Scholar 

  3. Villalobos Arias, L., Quesada López, C., Martínez Porras, A., Jenkins Coronas, M.: A tertiary study on model-based testing areas, tools and challenges: preliminary results (2018)

    Google Scholar 

  4. Uzun, B., Tekinerdogan, B.: Model-driven architecture based testing: a systematic literature review. Inf. Softw. Technol. 102, 30–48 (2018)

    Article  Google Scholar 

  5. Gurbuz, H.G., Tekinerdogan, B.: Model-based testing for software safety: a systematic mapping study. Softw. Qual. J. 26(4), 1327–1372 (2018)

    Article  Google Scholar 

  6. Iqbal, M.Z., Sherin, S.: Empirical studies omit reporting necessary details: a systematic literature review of reporting quality in model based testing. Comput. Stand. Interfaces 55, 156–170 (2018)

    Article  Google Scholar 

  7. Nikiforova, A., Bicevskis, J.: Towards a business process model-based testing of information systems functionality. In: Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 2: ICEIS, pp. 322–329 (2020). ISBN: 978-989-758-423-7. http://dx.doi.org/10.5220/0009459703220329

  8. Perez-Castillo, R., Carretero, A.G., Rodriguez, M., Caballero, I., Piattini, M. Mate, A., et al.: Data quality best practices in IoT environments. In: 2018 11th International Conference on the Quality of Information and Communications Technology (QUATIC), pp. 272–275. IEEE (2018). https://doi.org/10.1109/QUATIC.2018.00048

  9. de Cleva Farto, G., Endo, A.T.: Evaluating the model-based testing approach in the context of mobile applications. Electron. Notes Theor. Comput. Sci. 314, 3–21 (2015)

    Article  Google Scholar 

  10. Ziemba, E., Papaj, T., Descours, D.: Assessing the quality of e-government portals-the polish experience. In: 2014 Federated Conference on Computer Science and Information Systems, pp. 1259–1267. IEEE (2014). http://dx.doi.org/10.15439/2014F121

  11. Karabegovic, A., Ponjavic, M.: Geoportal as decision support system with spatial data warehouse. In: 2012 Federated Conference on Computer Science and Information Systems (FedCSIS), pp. 915–918. IEEE (2012)

    Google Scholar 

  12. Bicevskis, J., Bicevska, Z., Nikiforova, A., Oditis, I.: Data quality model-based testing of information systems. In: 2020 15th Conference on Computer Science and Information Systems (FedCSIS), pp. 595–602. IEEE (2020). https://doi.org/10.15439/2020f25

  13. Mohacsi, S., Felderer, M., Beer, A.: Estimating the cost and benefit of model-based testing: a decision support procedure for the application of model-based testing in industry. In: 2015 41st Euromicro Conference on Software Engineering and Advanced Applications, pp. 382–389. IEEE (2015)

    Google Scholar 

  14. Schieferdecker, I.: Model-based testing. IEEE Softw. 29(1), 14 (2012)

    Article  Google Scholar 

  15. Utting, M., Legeard, B.: Practical Model-Based Testing: A Tools Approach. Elsevier, Amsterdam (2010)

    Google Scholar 

  16. Jorgensen, P.C.: Software Testing: A Craftsman’s Approach. CRC Press, Boca Raton (2018)

    Book  Google Scholar 

  17. Nikiforova, A., Bicevskis, J., Bicevska, Z., Oditis, I.: User-Oriented Approach to Data Quality Evaluation. Journal of Universal Computer Science 26(1), 107–126 (2020)

    Google Scholar 

  18. Muniz, L., Netto, U.S., Maia, P.H.M.: A Model-based Testing Tool for Functional and Statistical Testing. In Proceedings of the 17th International Conference on Enterprise Information Systems (ICEIS), pp. 404–411 (2015)

    Google Scholar 

  19. Utting, M., Pretschner, A., Legeard, B.: A taxonomy of model-based testing approaches. Softw. Test. Verification Reliab. 22(5), 297–312 (2012)

    Article  Google Scholar 

  20. Zander, J., Schieferdecker, I., Mosterman, P.J.: A Taxonomy of Model-Based Testing for Embedded Systems from Multiple Industry Domains, vol. 1, pp. 3–17. Taylor & Francis Group:CRC Press, Boca Raton (2011)

    Google Scholar 

  21. Dias Neto, A.C., Subramanyan, R., Vieira, M., Travassos, G.H.: A survey on model-based testing approaches: a systematic review. In: 1st ACM International Workshop on Empirical Assessment of Software Engineering Languages and Technologies, pp. 31–36 (2007)

    Google Scholar 

  22. Guerra, E., Soeken, M.: Specification-driven model transformation testing. Softw. Syst. Model. 14(2), 623–644 (2015)

    Article  Google Scholar 

  23. Carvalho, G., Barros, F., Lapschies, F., Schulze, U., Peleska, J.: Model-based testing from controlled natural language requirements. In: Artho, C., Ölveczky, P. (eds.) Formal Techniques for Safety-Critical Systems. Communications in Computer and Information Science, vol. 419, pp. 19–35. Springer, Cham (2013). https://doi.org/10.1007/978-3-319-05416-2_3

    Chapter  Google Scholar 

  24. Hierons, R.M., Bogdanov, K., Bowen, J.P., Cleaveland, R., Derrick, J., Dick, J., et al.: Using formal specifications to support testing. ACM Comput. Surv. 41(2), 1–76 (2009)

    Article  Google Scholar 

  25. Nikiforova, A., Bicevskis, J., Bicevska, Z., Oditis, I.: Data quality model-based testing of information systems: the use-case of E-scooters. In: Proceeding of 7th IEEE International Conference on Internet of Things: Systems, Management and Security (2020). https://doi.org/10.1109/IOTSMS52051.2020.9340228

  26. ISTQB. - https://www.istqb.org/downloads/send/20-istqb-glossary/210-istqb-glossary-3-2-ga-release-notes-final.html

  27. Lewis, W.E.: Software Testing and Continuous Quality Improvement. CRC Press, England, UK (2017)

    Book  Google Scholar 

  28. Rafi, D. ., Moses, K.R.K., Petersen, K., Mäntylä, M.V.: Benefits and limitations of automated software testing: systematic literature review and practitioner survey. In: 2012 7th International Workshop on Automation of Software Test (AST), pp. 36–42. IEEE (2012)

    Google Scholar 

  29. Loyola, P., Staats, M., Ko, I.Y., Rothermel, G.: Dodona: automated oracle data set selection. In: Proceedings of the 2014 International Symposium on Software Testing and Analysis, pp. 193–203 (2014) http://dx.doi.org/10.1145/2610384.2610408

  30. Kaur, H., Gupta, G.: Comparative study of automated testing tools: selenium, quick test professional and test complete. Int. J. Eng. Res. Appl. 3(5), 1739–1743 (2013)

    Google Scholar 

  31. Capa, V.: Formalizētas specifikācijas vadīta testēšana. Formalized specification-based testing (in Latvian) (2020)

    Google Scholar 

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Acknowledgements

This work has been supported by University of Latvia project AAP2016/B032 “Innovative information technologies”.

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Authors and Affiliations

  1. Faculty of Computing, University of Latvia, Riga, Latvia

    Anastasija Nikiforova, Janis Bicevskis, Zane Bicevska & Ivo Oditis

Authors
  1. Anastasija Nikiforova
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  2. Janis Bicevskis
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  3. Zane Bicevska
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  4. Ivo Oditis
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Corresponding author

Correspondence to Anastasija Nikiforova .

Editor information

Editors and Affiliations

  1. University of Economics in Katowice, Katowice, Poland

    Ewa Ziemba

  2. University of Warsaw, Warsaw, Poland

    Witold Chmielarz

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Nikiforova, A., Bicevskis, J., Bicevska, Z., Oditis, I. (2021). Data Quality Model-Based Testing of Information Systems: Two-Level Testing of the Insurance System. In: Ziemba, E., Chmielarz, W. (eds) Information Technology for Management: Towards Business Excellence. ISM FedCSIS-IST 2020 2020. Lecture Notes in Business Information Processing, vol 413. Springer, Cham. https://doi.org/10.1007/978-3-030-71846-6_2

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  • DOI: https://doi.org/10.1007/978-3-030-71846-6_2

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-71846-6

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