The aim of this work is to provide a general method to minimize the size (number of states) of a model M of an ATL∗ formula. Our approach is founded on the notion of alternating bisimulation: given a model M, it is transformed in a stepwise manner into a new model M’ minimal with respect to bisimulation. The method has been implemented and will be integrated to the prover TATL, that constructiv...

1 Généralités 3 1.1 Problèmes d’optimisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Restauration/reconstruction d’image par minimisation d’énergie . . . . . . . . . . . . . . 3 1.3 Analyse de la solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3.1 Existence, éventuellement unicité . . . . . . . . . . . . . . . . . . ...

We present a new incremental algorithm for minimising deterministic finite automata. It runs in quadratic time for any practical application and may be halted at any point, returning a partially minimised automaton. Hence, the algorithm may be applied to a given automaton at the same time as it is processing a string for acceptance. We also include some experimental comparative results.

Data minimisation is a privacy enhancing principle, stating that personal data collected should be no more than necessary for the specific purpose consented by the user. Checking that a program satisfies the data minimisation principle is not easy, even for the simple case when considering deterministic programs-as-functions. In this paper we prove (im)possibility results concerning runtime mon...