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Architecture-Guided Test Resource Allocation via Logic

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Part of the Lecture Notes in Computer Science book series (LNPSE,volume 12740)

Abstract

We introduce a new logic named Quantitative Confidence Logic (QCL) that quantifies the level of confidence one has in the conclusion of a proof. By translating a fault tree representing a system’s architecture to a proof, we show how to use QCL to give a solution to the test resource allocation problem that takes the given architecture into account. We implemented a tool called Astrahl and compared our results to other testing resource allocation strategies.

Keywords

  • Reliability
  • Test resources allocation
  • Logic

The authors are supported by ERATO HASUO Metamathematics for Systems Design Project (No. JPMJER1603).

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Notes

  1. 1.

    Here, we mean fuzzy logics interpreted in [0, 1].

  2. 2.

    The code and experimental data are publicly available on https://github.com/ERATOMMSD/qcl_tap_2021.

  3. 3.

    Functional optimisation may not be as efficient in larger dimensions, but even a naive estimate should give a better result than completely ignoring system structure.

  4. 4.

    It would equally be possible to assume a test costs one resource and scale the budget.

  5. 5.

    We used smaller confidence so that components will usually contain faults.

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Eberhart, C. et al. (2021). Architecture-Guided Test Resource Allocation via Logic. In: Loulergue, F., Wotawa, F. (eds) Tests and Proofs. TAP 2021. Lecture Notes in Computer Science(), vol 12740. Springer, Cham. https://doi.org/10.1007/978-3-030-79379-1_2

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  • DOI: https://doi.org/10.1007/978-3-030-79379-1_2

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