System testing

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System testing, a.k.a. end-to-end (E2E) testing, is testing conducted on a complete software system.

System testing describes testing as at the system level to contrast to testing at the integration or unit level.

System testing often serves the purpose of evaluating the system's compliance with its specified requirements [citation needed] – often from a functional requirement specification (FRS), a system requirement specification (SRS), another type of specification or multiple.

System testing can detect defects in the system as a whole.[citation needed] [1]

System testing can verify the design, the behavior and even the believed expectations of the customer. It is also intended to test up to and beyond the bounds of specified software and hardware requirements.[citation needed]

Approaches

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  • Destructive testing: tests are carried out to the specimen's failure, in order to understand a specimen's performance or material behaviour under different loads.
  • Nondestructive testing: analysis techniques to evaluate the properties of a material, component or system without causing damage.
  • Fault injection: A testing technique which stress the system in an unusual way to examine the system behavior.[2][3][4]

See also

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Notes

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  1. ^ "ISTQB Standard glossary of terms used in Software Testing".
  2. ^ Moradi, Mehrdad; Van Acker, Bert; Vanherpen, Ken; Denil, Joachim (2019). Chamberlain, Roger; Taha, Walid; Törngren, Martin (eds.). "Model-Implemented Hybrid Fault Injection for Simulink (Tool Demonstrations)". Cyber Physical Systems. Model-Based Design. Lecture Notes in Computer Science. 11615. Cham: Springer International Publishing: 71–90. doi:10.1007/978-3-030-23703-5_4. ISBN 978-3-030-23703-5. S2CID 195769468.
  3. ^ "Optimizing fault injection in FMI co-simulation through sensitivity partitioning | Proceedings of the 2019 Summer Simulation Conference". dl.acm.org: 1–12. 22 July 2019. Retrieved 2020-06-15.
  4. ^ Moradi, Mehrdad, Bentley James Oakes, Mustafa Saraoglu, Andrey Morozov, Klaus Janschek, and Joachim Denil. "Exploring Fault Parameter Space Using Reinforcement Learning-based Fault Injection." (2020).

References

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