173 citations · 655 across the 66 of their papers we have counts for
7 papers · 1 filter
Ranking Policy Decisions
Hadrien Pouget, Hana Chockler, Youcheng Sun +1
Policies trained via Reinforcement Learning (RL) are often needlessly complex, making them difficult to analyse and interpret. In a run with time steps, a policy will make …
The Taint Rabbit: Optimizing Generic Taint Analysis with Dynamic Fast Path Generation
John Galea, Daniel Kroening
Generic taint analysis is a pivotal technique in software security. However, it suffers from staggeringly high overhead. In this paper, we explore the hypothesis whether just-in-ti…
Cautious Reinforcement Learning with Logical Constraints
Mohammadhosein Hasanbeig, Alessandro Abate, Daniel Kroening
This paper presents the concept of an adaptive safe padding that forces Reinforcement Learning (RL) to synthesise optimal control policies while ensuring safety during the learning…
CounterExample Guided Neural Synthesis
Elizabeth Polgreen, Ralph Abboud, Daniel Kroening
Program synthesis is the generation of a program from a specification. Correct synthesis is difficult, and methods that provide formal guarantees suffer from scalability issues. On…
Hardware/Software Co-verification Using Path-based Symbolic Execution
Rajdeep Mukherjee, Saurabh Joshi, John O'Leary +2
Conventional tools for formal hardware/software co-verification use bounded model checking techniques to construct a single monolithic propositional formula. Formulas generated in…
Evaluating Robustness to Context-Sensitive Feature Perturbations of Different Granularities
Isaac Dunn, Laura Hanu, Hadrien Pouget +2
We cannot guarantee that training datasets are representative of the distribution of inputs that will be encountered during deployment. So we must have confidence that our models d…