# Fast Falsification of Hybrid Systems using Probabilistically Adaptive Input

## TL;DR

This paper introduces a probabilistically adaptive algorithm for rapidly finding falsifying inputs in hybrid systems, significantly improving efficiency over existing methods by dynamically adjusting search granularity.

## Contribution

The paper presents a novel 'Las Vegas tree search' algorithm that adaptively refines input space discretization based on local complexity for effective falsification.

## Key findings

- Outperforms existing falsification techniques on standard benchmarks
- Efficiently finds falsifying inputs with fewer evaluations
- Adapts to problem difficulty through probabilistic discretization

## Abstract

We present an algorithm that quickly finds falsifying inputs for hybrid systems, i.e., inputs that steer the system towards violation of a given temporal logic requirement. Our method is based on a probabilistically directed search of an increasingly fine grained spatial and temporal discretization of the input space. A key feature is that it adapts to the difficulty of a problem at hand, specifically to the local complexity of each input segment, as needed for falsification. In experiments with standard benchmarks, our approach consistently outperforms existing techniques by a significant margin. In recognition of the way it works and to distinguish it from previous work, we describe our method as a "Las Vegas tree search".