We introduce layered automata, a subclass of alternating parity automata that generalises deterministic automata. Assuming a consistency property, these automata are history deterministic and 0-1 probabilistic. We show that every omega-regular language is recognised by a unique minimal consistent layered automaton, and that this canonical form can be computed in polynomial time from every layered or deterministic automaton. We further establish that, for layered automata, both consistency checking and inclusion testing can be performed in polynomial time. Much like deterministic finite automata, minimal consistent layered automata admit a characterisation based on congruences.

Families of deterministic finite automata (FDFA) represent regular ω-languages through their ultimately periodic words (UP-words). An FDFA accepts pairs of words, where the first component corresponds to a prefix of the UP-word, and the second component represents a period of that UP-word. An FDFA is termed saturated if, for each UP-word, either all or none of the pairs representing that UP-word are accepted. We demonstrate that determining whether a given FDFA is saturated can be accomplished in polynomial time, thus improving the known PSPACE upper bound by an exponential. We illustrate the application of this result by presenting the first polynomial learning algorithms for representations of the class of all regular ω-languages. Furthermore, we establish that deciding a weaker property, referred to as almost saturation, is PSPACE-complete. Since FDFAs do not necessarily define regular ω-languages when they are not saturated, we also address the regularity problem and show that it is PSPACE-complete. Finally, we explore a variant of FDFAs called families of deterministic weak automata (FDWA), where the semantics for the periodic part of the UP-word considers ω-words instead of finite words. We demonstrate that saturation for FDWAs is also decidable in polynomial time, that FDWAs always define regular ω-languages, and we compare the succinctness of these different models.

Abu Radi and Kupferman (2019) demonstrated the efficient minimization of history-deterministic (transition-based) co-Büchi automata, building on the results of Kuperberg and Skrzypczak (2015). We give a congruence-based description of these minimal automata, and a self-contained proof of its correctness. We use this description based on congruences to create a passive learning algorithm that can learn minimal history-deterministic co-Büchi automata from a set of labeled example words. The algorithm runs in polynomial time on a given set of examples, and there is a characteristic set of examples of polynomial size for each minimal history-deterministic co-Büchi automaton.

A transducer is finite-valued if for some bound k, it maps any given input to at most k outputs. For classical, one-way transducers, it is known since the 80s that finite valuedness entails decidability of the equivalence problem. This decidability result is in contrast to the general case, which makes finite-valued transducers very attractive. For classical transducers it is also known that finite valuedness is decidable and that any k-valued finite transducer can be decomposed as a union of k single-valued finite transducers.

The notion of delay between finite transducers is a core element of numerous fundamental results of transducer theory. The goal of this work is to provide a similar notion for more complex abstract machines: we introduce a new notion of delay tailored to measure the similarity between streaming string transducers (SST). We show that our notion is regular: we design a finite automaton that can check whether the delay between any two SSTs executions is smaller than some given bound. As a consequence, our notion enjoys good decidability properties: in particular, while equivalence between non-deterministic SSTs is undecidable, we show that equivalence up to fixed delay is decidable. Moreover, we show that our notion has good completeness properties: we prove that two SSTs are equivalent if and only if they are equivalent up to some (computable) bounded delay. Together with the regularity of our delay notion, it provides an alternative proof that SSTs equivalence is decidable. Finally, the definition of our delay notion is machine-independent, as it only depends on the origin semantics of SSTs. As a corollary, the completeness result also holds for equivalent machine models such as deterministic two-way transducers, or MSO transducers.

We propose a novel logic, Frame Logic (FL), that extends first-order logic and recursive definitions with a construct Sp (·) that captures the implicit supports of formulas—the precise subset of the universe upon which their meaning depends. Using such supports, we formulate proof rules that facilitate frame reasoning elegantly when the underlying model undergoes change. We show that the logic is expressive by capturing several data-structures and also exhibit a translation from a precise fragment of separation logic to frame logic. Finally, we design a program logic based on frame logic for reasoning with programs that dynamically update heaps that facilitates local specifications and frame reasoning. This program logic consists of both localized proof rules as well as rules that derive the weakest tightest preconditions in frame logic.

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Recursively defined linked data structures embedded in a pointer-based heap and their properties are naturally expressed in pure first-order logic with least fixpoint definitions (FO+lfp) with background theories. Such logics, unlike pure first-order logic, do not admit even complete procedures. In this paper, we undertake a novel approach for synthesizing inductive hypotheses to prove validity in this logic. The idea is to utilize several kinds of finite first-order models as counterexamples that capture the non-provability and invalidity of formulas to guide the search for inductive hypotheses. We implement our procedures and evaluate them extensively over theorems involving heap data structures that require inductive proofs and demonstrate the effectiveness of our methodology.

Abstract We propose a novel logic, called Frame Logic (FL), that extends first-order logic (with recursive definitions) using a construct $$\textit{Sp}(\cdot )$$ Sp ( · ) that captures the implicit supports of formulas— the precise subset of the universe upon which their meaning depends. Using such supports, we formulate proof rules that facilitate frame reasoning elegantly when the underlying model undergoes change. We show that the logic is expressive by capturing several data-structures and also exhibit a translation from a precise fragment of separation logic to frame logic. Finally, we design a program logic based on frame logic for reasoning with programs that dynamically update heaps that facilitates local specifications and frame reasoning. This program logic consists of both localized proof rules as well as rules that derive the weakest tightest preconditions in FL.

In this paper, we investigate the synthesis problem of terminating reactive systems from quantitative specifications. Such systems are modeled as finite transducers whose executions are represented as finite words in (I × O)^*, where I, O are finite sets of input and output symbols, respectively. A weighted specification S assigns a rational value (or -∞) to words in (I × O)^*, and we consider three kinds of objectives for synthesis, namely threshold objectives where the system’s executions are required to be above some given threshold, best-value and approximate objectives where the system is required to perform as best as it can by providing output symbols that yield the best value and ε-best value respectively w.r.t. S. We establish a landscape of decidability results for these three objectives and weighted specifications with partial domain over finite words given by deterministic weighted automata equipped with sum, discounted-sum and average measures. The resulting objectives are not regular in general and we develop an infinite game framework to solve the corresponding synthesis problems, namely the class of (weighted) critical prefix games.

Determinization of Büchi automata is a long-known difficult problem, and after the seminal result of Safra, who developed the first asymptotically optimal construction from Büchi into Rabin automata, much work went into improving, simplifying, or avoiding Safra’s construction. A different, less known determinization construction was proposed by Muller and Schupp. The two types of constructions share some similarities but their precise relationship was still unclear. In this paper, we shed some light on this relationship by proposing a construction from nondeterministic Büchi to deterministic parity automata that subsumes both constructions: Our construction leaves some freedom in the choice of the successor states of the deterministic automaton, and by instantiating these choices in different ways, one obtains as particular cases the construction of Safra and the construction of Muller and Schupp. The basis is a correspondence between structures that are encoded in the macrostates of the determinization procedures - Safra trees on one hand, and levels of the split-tree, which underlies the Muller and Schupp construction, on the other hand. Our construction also allows for mixing the mentioned constructions, and opens up new directions for the development of heuristics.

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We study an extension of tree automata on infinite trees with global equality and disequality constraints. These constraints can enforce that all subtrees for which in the accepting run a state q is reached (at the root of that subtree) are identical, or that these trees differ from the subtrees at which a state q' is reached. We consider the closure properties of this model and its decision problems. While the emptiness problem for the general model remains open, we show the decidability of the emptiness problem for the case that the given automaton only uses equality constraints.

We consider imperfect information stochastic games where we require the players to use pure ( i.e. non randomised) strategies. We consider reachability, safety, Büchi and co-Büchi objectives, and investigate the existence of almost-sure/positively winning strategies for the first player when the second player is perfectly informed or more informed than the first player. We obtain decidability results for positive reachability and almost-sure Büchi with optimal algorithms to decide existence of a pure winning strategy and to compute one if it exists. We complete the picture by showing that positive safety is undecidable when restricting to pure strategies even if the second player is perfectly informed.

We give foundational results that explain the efficacy of heuristics used for dealing with quantified formulas and recursive definitions. We develop a framework for first order logic (FOL) over an uninterpreted combination of background theories. Our central technical result is that systematic term instantiation is complete for a fragment of FOL that we call safe . Coupled with the fact that unfolding recursive definitions is essentially term instantiation and with the observation that heap verification engines generate verification conditions in the safe fragment explains the efficacy of verification engines like natural proofs that resort to such heuristics. Furthermore, we study recursive definitions with least fixpoint semantics and show that though they are not amenable to complete procedures, we can systematically introduce induction principles that in practice bridge the divide between FOL and FOL with recursive definitions.

We study the classification problems over string data for hypotheses specified by formulas of monadic second-order logic MSO. The goal is to design learning algorithms that run in time polynomial in the size of the training set, independently of or at least sublinear in the size of the whole data set. We prove negative as well as positive results. If the data set is an unprocessed string to which our algorithms have local access, then learning in sublinear time is impossible even for hypotheses definable in a small fragment of first-order logic. If we allow for a linear time pre-processing of the string data to build an index data structure, then learning of MSO-definable hypotheses is possible in time polynomial in the size of the training set, independently of the size of the whole data set.

This article is inspired by two works from the early 90s. The first one is by Bogaert and Tison who considered a model of automata on finite ranked trees where one can check equality and disequality constraints between direct subtrees: they proved that this class of automata is closed under Boolean operations and that both the emptiness and the finiteness problem of the accepted language are decidable. The second one is by Niwinski who showed that one can compute the cardinality of any ω-regular language of infinite trees.

We propose a new definition of regular expressions for describing languages of omega-words, called infinity-regular expressions. These expressions are obtained by adding to the standard regular expression on finite words an operator infinity that acts similar to the Kleene-star but can be iterated finitely or infinitely often (as opposed to the omega-operator from standard omega-regular expressions, which has to be iterated infinitely often). We show that standard constructions between automata and regular expressions for finite words can smoothly be adapted to infinite words in this setting: We extend the Glushkov construction yielding a simple translation of infinity-regular expressions into parity automata, and we show how to translate parity automata into infinity-regular expressions by the classical state elimination technique, where in both cases the nesting of the * and the infinity operators corresponds to the priority range used in the parity automaton. We also briefly discuss the concept of deterministic expressions that directly transfers from standard regular expressions to infinity-regular expressions.

For a given binary relation of finite trees, we consider the synthesis problem of deciding whether there is a deterministic top-down tree transducer that uniformizes the relation, and constructing such a transducer if it exists. A uniformization of a relation is a function that is contained in the relation and has the same domain as the relation. It is known that this problem is decidable if the relation is a deterministic top-down tree-automatic relation. We show that it becomes undecidable for general tree-automatic relations (specified by non-deterministic top-down tree automata). We also exhibit two cases for which the problem remains decidable. If we restrict the transducers to be path-preserving, which is a subclass of linear transducers, then the synthesis problem is decidable for general tree-automatic relations. If we consider relations that are finite unions of deterministic top-down tree-automatic relations, then the problem is decidable for synchronous transducers, which produce exactly one output symbol in each step (but can be non-linear).

In the past years, extensions of monadic second-order logic (MSO) that can specify boundedness properties by the use of operators referring to the sizes of sets have been considered. In particular, the logics costMSO introduced by T. Colcombet and MSO+U by M. Bojanczyk were analyzed and connections to automaton models have been established to obtain decision procedures for these logics. In this work, we propose the logic quantitative counting MSO (qcMSO for short), which combines aspects from both costMSO and MSO+U. We show that both logics can be embedded into qcMSO in a natural way. Moreover, we provide a decidability proof for the theory of its weak variant (quantification only over finite sets) for the natural numbers with order and the infinite binary tree. These decidability results are obtained using a regular cost function extension of automatic structures called resource-automatic structures.

We study stability and delay in dynamic networks under adversarial conditions. Adversarial conditions are mandatory in establishing deterministic performance guarantees in networks. Under this framework, we concentrate on the general stability region for a network, i.e. without specifying the routing algorithm. This is in contrast to related work for adversarial network conditions, where usually the backpressure routing algorithm is considered. Our work consists of four novel contributions: (1) We present a novel analysis model which is based on the theory of infinite two-player games, (2) Using this approach, we can characterize the stability region of networks under adversarial conditions for arbitrary routing schemes, (3) We determine conditions under which a delay bound for packet forwarding under adversarial conditions exists, (4) We provide a backtracking algorithm which determines in a model-checking fashion network stability. The backtracking algorithm is furthermore shown to reduce the computational effort significantly for practical scenarios.

Weakly definable languages of infinite trees are an expressive subclass of regular tree languages definable in terms of weak monadic second-order logic, or equivalently weak alternating automata. Our main result is that given a Büchi automaton, it is decidable whether the language is weakly definable. We also show that given a parity automaton, it is decidable whether the language is recognizable by a nondeterministic co-Büchi automaton. The decidability proofs build on recent results about cost automata over infinite trees. These automata use counters to define functions from infinite trees to the natural numbers extended with infinity. We reduce to testing whether the functions defined by certain "quasi-weak" cost automata are bounded by a finite value.

In this paper, we study lookahead delegators for nondeterministic finite automata (NFA), which are functions that deterministically choose transitions by additionally using a bounded lookahead on the input word. Of course, the delegator has to lead to an accepting state for each word that is accepted by the NFA. In the special case where no lookahead is allowed, a delegator coincides with a deterministic transition function that preserves the language. Typical decision problems are to decide whether a delegator with a given fixed lookahead exists, or whether a delegator with some bounded lookahead exists for a given NFA. In a paper of Ravikumar and Santean from 2007, the complexity and decidability of these questions have been tackled, mainly for the case of unambiguous NFA. In this paper, we revisit the subject and provide results for the case of general NFA. First, we correct a complexity result from the above paper by showing that the existence of delegators with fixed lookahead can be decided in time polynomial in the number of states. We use two player games on graphs as a tool to obtain the result. As second contribution, we show that the problem becomes PSPACE-complete if the bound on the lookahead is a part of the input. The third result provides a bound on the maximal required amount of lookahead. We use this to show that the (previously open) problem of deciding the existence of a bounded lookahead delegator is also PSPACE-complete.

We develop the theory of regular cost functions over finite trees: aquantitative extension to the notion of regular languages of trees: Cost functions map each input (tree) to a value in~$\omega+1$, and are considered modulo an equivalence relation which forgets about specific values, but preserves boundedness of functions on all subsets of the domain. We introduce nondeterministic and alternating finite tree cost automata for describing cost functions. We show that all these forms of automata are effectively equivalent. We also provide decision procedures for them. Finally, following B\"uchi's seminal idea, we use cost automata for providing decision procedures for cost monadic logic, a quantitative extension of monadic second order logic.

We continue the study of bottom-up unranked tree automata with equality and disequality constraints between direct subtrees. In particular, we show that the emptiness problem for the nondeterministic automata is decidable. In addition, we show that the universality problem, in contrast, is undecidable.

We consider a new kind of interpretation over relational structures: finite sets interpretations. Those interpretations are defined by weak monadic second-order (WMSO) formulas with free set variables. They transform a given structure into a structure with a domain consisting of finite sets of elements of the orignal structure. The definition of these interpretations directly implies that they send structures with a decidable WMSO theory to structures with a decidable first-order theory. In this paper, we investigate the expressive power of such interpretations applied to infinite deterministic trees. The results can be used in the study of automatic and tree-automatic structures.

Planar spatial datasets can be modeled by closed semi-algebraic sets in the plane. We establish a characterization of the topological properties of such datasets expressible in the relational calculus with real polynomial constraints. The characterization is in the form of a query language that can only point that can only talk about points in the set and the “cones” around these points.

Closed semi-algebraic sets in the plane form a powerful model of planar spatial datasets. We establish a characterization of the topological properties of such datasets expressible in the relational calculus with real polynomial constraints. The characterization is in the form of a query language that can only talk about points in the set and the "cones" around these points.