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@inproceedings{viswanadha-rv21,
author = {Kesav Viswanadha and
Edward Kim and
Francis Indaheng and
Daniel J. Fremont and
Sanjit A. Seshia},
title = {Parallel and Multi-Objective Falsification with {Scenic} and {VerifAI}},
booktitle = {21st International Conference on Runtime Verification (RV)},
series = {Lecture Notes in Computer Science},
volume = {12974},
pages = {265--276},
publisher = {Springer},
year = {2021},
abstract = {Falsification has emerged as an important tool for simulation-based verification of autonomous systems. In this paper, we present extensions to the Scenic scenario specification language and VerifAI toolkit that improve the scalability of sampling-based falsification methods by using parallelism and extend falsification to multi-objective specifications. We first present a parallelized framework that is interfaced with both the simulation and sampling capabilities of Scenic and the falsification capabilities of VerifAI, reducing the execution time bottleneck inherently present in simulation-based testing. We then present an extension of VerifAI ’s falsification algorithms to support multi-objective optimization during sampling, using the concept of rulebooks to specify a preference ordering over multiple metrics that can be used to guide the counterexample search process. Lastly, we evaluate the benefits of these extensions with a comprehensive set of benchmarks written in the Scenic language.},
}