33 citations · 43 across the 5 of their papers we have counts for
5 papers
A Fast Quantitative Analyzer for NetKAT
Thomas Lu, Qiancheng Fu, Kevin Batz +5
When designing a network, engineers must navigate trade-offs (e.g., one topology offers more aggregate bandwidth, another lower latency or better resilience) that demand reasoning…
Conflict-Aware Active Automata Learning
Tiago Ferreira, Léo Henry, Raquel Fernandes da Silva +1
Active automata learning algorithms cannot easily handle conflict in the observation data (different outputs observed for the same inputs). This inherent inability to recover after…
Conflict-Aware Active Automata Learning (Extended Version)
Tiago Ferreira, Léo Henry, Raquel Fernandes da Silva +1
Active automata learning algorithms cannot easily handle conflict in the observation data (different outputs observed for the same inputs). This inherent inability to recover after…
Tree-Based Adaptive Model Learning
Tiago Ferreira, Gerco van Heerdt, Alexandra Silva
We extend the Kearns-Vazirani learning algorithm to be able to handle systems that change over time. We present a new learning algorithm that can reuse and update previously learne…
Prognosis: Closed-Box Analysis of Network Protocol Implementations
Tiago Ferreira, Harrison Brewton, Loris D'Antoni +1
We present Prognosis, a framework offering automated closed-box learning and analysis of models of network protocol implementations. Prognosis can learn models that vary in abstrac…