2022
Conference article  Open Access

Testing non-testable programs using association rules

Bertolino A., Cruciani E., Miranda B., Verdecchia R.

Testing  Non-testable systems  Association rules  Plausibility testing 

We propose a novel scalable approach for testing non-testable programs denoted as ARMED testing. The approach leverages efficient Association Rules Mining algorithms to determine relevant implication relations among features and actions observed while the system is in operation. These relations are used as the specification of positive and negative tests, allowing for identifying plausible or suspicious behaviors: for those cases when oracles are inherently unknownable, such as in social testing, ARMED testing introduces the novel concept of testing for plausibility. To illustrate the approach we walk-through an application example.

Source: AST 2022 - 3rd ACM/IEEE International Conference on Automation of Software Test, pp. 87–91, Pittsburgh, USA, 17-18/05/2022


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BibTeX entry
@inproceedings{oai:it.cnr:prodotti:469241,
	title = {Testing non-testable programs using association rules},
	author = {Bertolino A. and Cruciani E. and Miranda B. and Verdecchia R.},
	doi = {10.1145/3524481.3527238},
	booktitle = {AST 2022 - 3rd ACM/IEEE International Conference on Automation of Software Test, pp. 87–91, Pittsburgh, USA, 17-18/05/2022},
	year = {2022}
}