This article presents HARM, a tool to generate linear temporal logic (LTL) assertions starting from a set of user-defined hints and the simulation traces of the design under verification (DUV). The tool is agnostic with respect to the design from which the trace was generated, thus the DUV source code is not necessary. The user-defined hints involve LTL templates, propositions, and ranking metrics that are exploited by the assertion miner to reduce the search space and improve the quality of the generated assertions. This way, the tool supports the work of the verification engineer by including his/her insights in the process of automatically generating assertions. The experimental results show real improvements with respect to the state-of-the-art in terms of assertion coverage and scalability.

HARM: A Hint-Based Assertion Miner

Samuele Germiniani;Graziano Pravadelli
2022-01-01

Abstract

This article presents HARM, a tool to generate linear temporal logic (LTL) assertions starting from a set of user-defined hints and the simulation traces of the design under verification (DUV). The tool is agnostic with respect to the design from which the trace was generated, thus the DUV source code is not necessary. The user-defined hints involve LTL templates, propositions, and ranking metrics that are exploited by the assertion miner to reduce the search space and improve the quality of the generated assertions. This way, the tool supports the work of the verification engineer by including his/her insights in the process of automatically generating assertions. The experimental results show real improvements with respect to the state-of-the-art in terms of assertion coverage and scalability.
Scalability
Measurement
Data mining
Source coding
Decision trees
Task analysis
Static analysis
Assertion mining
assertion ranking
assertionbased verification (ABV)
temporal assertions
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1079506
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