Robustness testing

Robustness testing is any quality assurance methodology focused on testing the robustness of software. Robustness testing has also been used to describe the process of verifying the robustness (i.e. correctness) of test cases in a test process.

ANSI and IEEE have defined robustness as the degree to which a system or component can function correctly in the presence of invalid inputs or stressful environmental conditions.[1]

The term "robustness testing" was first used by the Ballista project at Carnegie Mellon University. They performed testing of operating systems for dependability based on the data types of POSIX API, producing complete system crashes in some systems. [2] The term was also used by OUSPG and VTT researchers taking part in the PROTOS project in the context of software security testing.[3] Eventually the term Fuzzing (which security people use for mostly non-intelligent and random robustness testing) extended to also cover model-based robustness testing.

Methods

Fault injection

Fault injection is a testing method that can be used for checking robustness of systems. They inject fault into system and observe system's resilient[4]. In the [5][6] authors worked on an efficient method which aid fault injection to find critical faults that can fail the system.

gollark: Fascinating.
gollark: If you want to gaze upon the full glory of my code, do so.
gollark: I might just have to find one of the nim communities™.
gollark: I would probably like to do something something objects but I don't know how.
gollark: I did bother to do tail recursion though, for sorting big lists.

See also

References
  1. "Standard Glossary of Software Engineering Terminology (ANSI)". The Institute of Electrical and Electronics Engineers Inc. 1991.
  2. Kropp, Koopman, Siewiorek. 1998. Automated Robustness Testing of Off-the_Shelf Software Components. Proceedings of FTCS'98. http://www.ece.cmu.edu/~koopman/ballista/ftcs98/ftcs98.pdf
  3. Kaksonen, Rauli. 2001. A Functional Method for Assessing Protocol Implementation Security (Licentiate thesis). Espoo. Technical Research Centre of Finland, VTT Publications 448. 128 p. + app. 15 p. ISBN 951-38-5873-1 (soft back ed.) ISBN 951-38-5874-X (on-line ed.). https://www.ee.oulu.fi/research/ouspg/PROTOS_VTT2001-functional
  4. 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. Cham: Springer International Publishing: 71–90. doi:10.1007/978-3-030-23703-5_4. ISBN 978-3-030-23703-5.
  5. "Optimizing fault injection in FMI co-simulation through sensitivity partitioning | Proceedings of the 2019 Summer Simulation Conference". dl.acm.org. Retrieved 2020-06-15.
  6. 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).


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