SEJul 22, 2021

Architecture-Guided Test Resource Allocation Via Logic

arXiv:2107.10948v11 citations
Originality Synthesis-oriented
AI Analysis

This addresses the problem of optimizing testing resources for system architects, but appears incremental as it builds on existing logic and allocation methods.

The paper tackled the test resource allocation problem by introducing Quantitative Confidence Logic (QCL) to quantify confidence in proofs derived from system architectures, and implemented a tool called Astrahl that showed results compared to other strategies.

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.

Code Implementations1 repo
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