Computer Science

A binary relation on graphs is recursively enumerable if and only if it can be computed by a formula in monadic second-order logic. The latter means that the formula defines a set of graphs, in the usual way, such that each "computation graph" in that set determines a pair consisting of an input graph and an output graph.

In this paper, we investigate the problem of synthesizing computable functions of infinite words over an infinite alphabet (data ? -words). The notion of computability is defined through Turing machines with infinite inputs which can produce the corresponding infinite outputs in the limit. We use non-deterministic transducers equipped with registers, an extension of register automata with outputs, to describe specifications. Being non-deterministic, such transducers may not define functions but more generally relations of data ? -words. In order to increase the expressive power of these machines, we even allow guessing of arbitrary data values when updating their registers. For functions over data ? -words, we identify a sufficient condition (the possibility of determining the next letter to be outputted, which we call next letter problem) under which computability (resp. uniform computability) and continuity (resp. uniform continuity) coincide. We focus on two kinds of data domains: first, the general setting of oligomorphic data, which encompasses any data domain with equality, as well as the setting of rational numbers with linear order; and second, the set of natural numbers equipped with linear order. For both settings, we prove that functionality, i.e. determining whether the relation recognized by the transducer is actually a function, is decidable. We also show that the so-called next letter problem is decidable, yielding equivalence between (uniform) continuity and (uniform) computability. Last, we provide characterizations of (uniform) continuity, which allow us to prove that these notions, and thus also (uniform) computability, are decidable. We even show that all these decision problems are PSpace-complete for (N,<) and for a large class of oligomorphic data domains, including for instance (Q,<).

Here we study the computational complexity of the constrained synchronization problem for the class of regular commutative constraint languages. Utilizing a vector representation of regular commutative constraint languages, we give a full classification of the computational complexity of the constraint synchronization problem. Depending on the constraint language, our problem becomes PSPACE-complete, NP-complete or polynomial time solvable. In addition, we derive a polynomial time decision procedure for the complexity of the constraint synchronization problem, given some constraint automaton accepting a commutative language as input.

We present two new results on the computational limitations of affine automata. First, we show that the computation of bounded-error rational-values affine automata is simulated in logarithmic space. Second, we give an impossibility result for algebraic-valued affine automata. As a result, we identify some unary languages (in logarithmic space) that are not recognized by algebraic-valued affine automata with cutpoints.

The probabilistic bisimilarity distance of Deng et al. has been proposed as a robust quantitative generalization of Segala and Lynch's probabilistic bisimilarity for probabilistic automata. In this paper, we present a characterization of the bisimilarity distance as the solution of a simple stochastic game. The characterization gives us an algorithm to compute the distances by applying Condon's simple policy iteration on these games. The correctness of Condon's approach, however, relies on the assumption that the games are stopping. Our games may be non-stopping in general, yet we are able to prove termination for this extended class of games. Already other algorithms have been proposed in the literature to compute these distances, with complexity in UP∩coUP and \textbf{PPAD}. Despite the theoretical relevance, these algorithms are inefficient in practice. To the best of our knowledge, our algorithm is the first practical solution. The characterization of the probabilistic bisimilarity distance mentioned above crucially uses a dual presentation of the Hausdorff distance due to Mémoli. As an additional contribution, in this paper we show that Mémoli's result can be used also to prove that the bisimilarity distance bounds the difference in the maximal (or minimal) probability of two states to satisfying arbitrary ω -regular properties, expressed, eg., as LTL formulas.

Timed automata are a convenient mathematical model for modelling and reasoning about real-time systems. While they provide a powerful way of representing timing aspects of such systems, timed automata assume arbitrary precision and zero-delay actions; in particular, a state might be declared reachable in a timed automaton, but impossible to reach in the physical system it models. In this paper, we consider permissive strategies as a way to overcome this problem: such strategies propose intervals of delays instead of single delays, and aim at reaching a target state whichever delay actually takes place. We develop an algorithm for computing the optimal permissiveness (and an associated maximally-permissive strategy) in acyclic timed automata and games.

A two-dimensional automaton operates on arrays of symbols. While a standard (four-way) two-dimensional automaton can move its input head in four directions, restricted two-dimensional automata are only permitted to move their input heads in three or two directions; these models are called three-way and two-way two-dimensional automata, respectively. In two dimensions, we may extend the notion of concatenation in multiple ways, depending on the words to be concatenated. We may row-concatenate (resp., column-concatenate) a pair of two-dimensional words when they have the same number of columns (resp., rows). In addition, the diagonal concatenation operation combines two words at their lower-right and upper-left corners, and is not dimension-dependent. In this paper, we investigate closure properties of restricted models of two-dimensional automata under various concatenation operations. We give non-closure results for two-way two-dimensional automata under row and column concatenation in both the deterministic and nondeterministic cases. We further give positive closure results for the same concatenation operations on unary nondeterministic two-way two-dimensional automata. Finally, we study closure properties of diagonal concatenation on both two- and three-way two-dimensional automata.

Mixed-paradigm process models integrate strengths of procedural and declarative representations like Petri nets and Declare. They are specifically interesting for process mining because they allow capturing complex behaviour in a compact way. A key research challenge for the proliferation of mixed-paradigm models for process mining is the lack of corresponding conformance checking techniques. In this paper, we address this problem by devising the first approach that works with intertwined state spaces of mixed-paradigm models. More specifically, our approach uses an alignment-based replay to explore the state space and compute trace fitness in a procedural way. In every state, the declarative constraints are separately updated, such that violations disable the corresponding activities. Our technique provides for an efficient replay towards an optimal alignment by respecting all orthogonal Declare constraints. We have implemented our technique in ProM and demonstrate its performance in an evaluation with real-world event logs.

Congruences for stochastic automata are defined, the correspondin factor automata are constructed and investigated for automata ove analytic spaces. We study the behavior under finite and infinite streams. Congruences consist of multiple parts, it is shown that factoring can be done in multiple steps, guided by these parts.

We introduce the class CXRPQ of conjunctive xregex path queries, which are obtained from conjunctive regular path queries (CRPQs) by adding string variables (also called backreferences) as found in practical implementations of regular expressions. CXRPQs can be considered user-friendly, since they combine two concepts that are well-established in practice: pattern-based graph queries and regular expressions with backreferences. Due to the string variables, CXRPQs can express inter-path dependencies, which are not expressible by CRPQs. The evaluation complexity of CXRPQs, if not further restricted, is PSPACE-hard in data-complexity. We identify three natural fragments with more acceptable evaluation complexity: their data-complexity is in NL, while their combined complexity varies between EXPSPACE, PSPACE and NP. In terms of expressive power, we compare the CXRPQ-fragments with CRPQs and unions of CRPQs, and with extended conjunctive regular path queries (ECRPQs) and unions of ECRPQs.