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Towards an Acceptance Testing Approach for Internet of Things Systems

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Abstract

Internet of Things (IoT) applications and systems pervade our life increasingly and assuring their quality is of paramount importance. Unfortunately, few proposals for testing these complex—and often safety-critical—systems are present in the literature and testers are left alone to build their test cases.

This paper is a first step towards acceptance testing of an IoT system that relies on a smartphone as principal way of interaction between the user and a complex system composed by local sensors/actuators and a remote cloud-based system. A simplified mobile health (m-health) IoT system for diabetic patients is used as an example to explain the proposed approach.

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Notes

  1. 1.

    in [13] this kind of testing is called end-to-end testing.

  2. 2.

    Testware includes artifacts produced during the test process such as, test scripts, inputs, expected results, set-up and clear-up procedures, files, databases, environment, and any additional software or utilities used in testing.

  3. 3.

    e.g., https://devops.com/functional-testing-iot/.

  4. 4.

    note that since DiaMH is a safety critical system, also other verification techniques, not considered in this paper, should be applied (e.g., runtime verification [11], model checking [4]).

  5. 5.

    http://www.nemauramedical.com/sugarbeat/.

  6. 6.

    https://en.wikipedia.org/wiki/Bluetooth_low_energy.

  7. 7.

    http://docs.oasis-open.org/mqtt/mqtt/v3.1.1/mqtt-v3.1.1.html.

  8. 8.

    https://developer.android.com/studio/run/emulator.html.

  9. 9.

    https://nodered.org/.

  10. 10.

    https://www.ibm.com/cloud-computing/bluemix/.

  11. 11.

    http://phonegap.com/.

  12. 12.

    http://www.sikuli.org/.

  13. 13.

    i.e., that it behaves as specified by the requirements in response to the currently observed glucose pattern. For instance, an alarm is displayed when a problematic pattern is detected (see Test case TC1).

  14. 14.

    the log files plotted in Fig. 3 contain fictitious but realistic glucose level readings recorded every 10 min, thus using the mock of the glucose sensor at 1 read/sec allows to speed up the execution of the test of 600x.

  15. 15.

    since the mock of the glucose sensor provides a new value every second, and all of them are above the 160 mg/dl threshold, after 20 s the system can, in theory, raise the alarm. However, some computations are required on the cloud system. For this reason, system requirements state that the alarm must be shown on the smartphone within 40 s the occurrence of a problematic pattern, thus the test verifies the presence of the alarm after 20 s + 40 s from the first read.

  16. 16.

    http://martinfowler.com/bliki/PageObject.html.

References

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Acknowledgements

This research was partially supported by Actelion Pharmaceuticals Italia and SEED 2015 grants.

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Correspondence to Maurizio Leotta .

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Leotta, M. et al. (2018). Towards an Acceptance Testing Approach for Internet of Things Systems. In: Garrigós, I., Wimmer, M. (eds) Current Trends in Web Engineering. ICWE 2017. Lecture Notes in Computer Science(), vol 10544. Springer, Cham. https://doi.org/10.1007/978-3-319-74433-9_11

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  • DOI: https://doi.org/10.1007/978-3-319-74433-9_11

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