Software reliability modelling
When should testing stop, and when is a release safe? Probabilistic models that estimate reliability from failure data.
Fault-tolerant system theory, software reliability, and performance evaluation — the mathematics of designing for failure.
When should testing stop, and when is a release safe? Probabilistic models that estimate reliability from failure data.
From automatic test generation to model-driven development — techniques that support the work of building software.
Solving very large Markov chains quickly — phase-type distributions, Markovian arrival processes and the EM algorithm.
When should a unit be replaced, repaired or inspected? The theory of optimal preventive maintenance built on stochastic processes.
Software rejuvenation, checkpointing, and the performance and availability of cloud and 5G networks.
Classifying malware and detecting vulnerabilities, from both machine learning and stochastic modelling.
Play against an agent that learns your habits, and watch the statistics update in real time.
Watch a reinforcement-learning agent learn to keep a pole upright through trial and error.
Where should sensors go to cover a region reliably? Binary decision diagrams give an exact answer, recomputed in the browser as you move sensors.