Planning for real world problems with explicit temporal constraints is a challenging problem. Among several approaches, the use of flexible timelines in Planning and Scheduling has been shown to be successful in a number of concrete applications, such as, for instance, autonomous space systems. This paper builds on previous work and presents a revised and extended formal account of flexible timelines with the aim of providing a general semantics for related planning concepts such as domains, goals, problems, constraints, and flexible plans. Some sources of uncertainty are also modeled in the proposed framework and taken into account in the characterization of valid plans that are assumed not to take decisions on components the planner cannot control. A formal definition of different forms of plan controllability is also proposed.

Formal synthesis is the process of generating a program satisfying a high-level formal specification. In recent times, effective formal synthesis methods have been proposed based on the use of inductive learning. We refer to this class of methods that learn programs from examples as formal inductive synthesis. In this paper, we present a theoretical framework for formal inductive synthesis. We discuss how formal inductive synthesis differs from traditional machine learning. We then describe oracle-guided inductive synthesis (OGIS), a framework that captures a family of synthesizers that operate by iteratively querying an oracle. An instance of OGIS that has had much practical impact is counterexample-guided inductive synthesis (CEGIS). We present a theoretical characterization of CEGIS for learning any program that computes a recursive language. In particular, we analyze the relative power of CEGIS variants where the types of counterexamples generated by the oracle varies. We also consider the impact of bounded versus unbounded memory available to the learning algorithm. In the special case where the universe of candidate programs is finite, we relate the speed of convergence to the notion of teaching dimension studied in machine learning theory. Altogether, the results of the paper take a first step towards a theoretical foundation for the emerging field of formal inductive synthesis.

A concurrent Abstract State Machine (ASM) is a family of agents each equipped with a sequential ASM to execute. We define the semantics of concurrent ASMs by concurrent ASM runs which overcome the problems of Gurevich’s distributed ASM runs and generalize Lamport’s sequentially consistent runs. A postulate characterizing an intuitive understanding of concurrency is formulated. It allows us to state and prove an extension of the sequential ASM thesis to a concurrent ASM thesis.

We consider the problem of synthesising rate parameters for stochastic biochemical networks so that a given time-bounded CSL property is guaranteed to hold, or, in the case of quantitative properties, the probability of satisfying the property is maximised or minimised. Our method is based on extending CSL model checking and standard uniformisation to parametric models, in order to compute safe bounds on the satisfaction probability of the property. We develop synthesis algorithms that yield answers that are precise to within an arbitrarily small tolerance value. The algorithms combine the computation of probability bounds with the refinement and sampling of the parameter space. Our methods are precise and efficient, and improve on existing approximate techniques that employ discretisation and refinement. We evaluate the usefulness of the methods by synthesising rates for three biologically motivated case studies: infection control for a SIR epidemic model; reliability analysis of molecular computation by a DNA walker; and bistability in the gene regulation of the mammalian cell cycle.

Model checking is a powerful method widely explored in formal verification. Given a model of a system, e.g., a Kripke structure, and a formula specifying its expected behaviour, one can verify whether the system meets the behaviour by checking the formula against the model. Classically, system behaviour is expressed by a formula of a temporal logic, such as LTL and the like. These logics are “point-wise” interpreted, as they describe how the system evolves state-by-state. However, there are relevant properties, such as those constraining the temporal relations between pairs of temporally extended events or involving temporal aggregations, which are inherently “interval-based”, and thus asking for an interval temporal logic. In this paper, we give a formalization of the model checking problem in an interval logic setting. First, we provide an interpretation of formulas of Halpern and Shoham’s interval temporal logic HS over finite Kripke structures, which allows one to check interval properties of computations. Then, we prove that the model checking problem for HS against finite Kripke structures is decidable by a suitable small model theorem, and we provide a lower bound to its computational complexity.

Selectivity estimation of a boolean query based on frequent itemsets can be solved by describing the problem by a linear program. However, the number of variables in the equations is exponential, rendering the approach tractable only for small-dimensional cases. One natural approach would be to project the data to the variables occurring in the query. This can, however, change the outcome of the linear program.We introduce the concept of safe sets: projecting the data to a safe set does not change the outcome of the linear program. We characterise safe sets using graph theoretic concepts and give an algorithm for finding minimal safe sets containing given attributes. We describe a heuristic algorithm for finding almost-safe sets given a size restriction, and show empirically that these sets outperform the trivial projection.We also show a connection between safe sets and Markov Random Fields and use it to furtherreduce the number of variables in the linear program, given some regularity assumptions on the frequent itemsets.

We introduce in a general setting a dynamic programming method for solving reconfiguration problems. Our method is based on contracted solution graphs, which are obtained from solution graphs by performing an appropriate series of edge contractions that decrease the graph size without losing any critical information needed to solve the reconfiguration problem under consideration. Our general framework captures the approach behind known reconfiguration results of Bonsma (Discrete Appl Math 231:95–112, 2017) and Hatanaka et al. (IEICE Trans Fundam Electron Commun Comput Sci 98(6):1168–1178, 2015). As a third example, we apply the method to the following well-studied problem: given two k-colorings $$\alpha $$ α and $$\beta $$ β of a graph G, can $$\alpha $$ α be modified into $$\beta $$ β by recoloring one vertex of G at a time, while maintaining a k-coloring throughout? This problem is known to be PSPACE-hard even for bipartite planar graphs and $$k=4$$ k = 4 . By applying our method in combination with a thorough exploitation of the graph structure we obtain a polynomial-time algorithm for $$(k-2)$$ ( k - 2 ) -connected chordal graphs.

Turi and Plotkin introduced an elegant approach to structural operational semantics based on universal coalgebra, parametric in the type of syntax and the type of behaviour. Their framework includes abstract GSOS, a categorical generalisation of the classical GSOS rule format, as well as its categorical dual, coGSOS. Both formats are well behaved, in the sense that each specification has a unique model on which behavioural equivalence is a congruence. Unfortunately, the combination of the two formats does not feature these desirable properties. We show that monotone specifications—that disallow negative premises—do induce a canonical distributive law of a monad over a comonad, and therefore a unique, compositional interpretation.

We propose a calculus for concurrent reversible multiparty sessions, equipped with a flexible choice operator allowing for different sets of participants in each branch. This operator is inspired by the notion of connecting action recently introduced by Hu and Yoshida to describe protocols with optional participants. We argue that this choice operator allows for a natural description of typical communication protocols. Our calculus also supports a compact representation of the history of processes and types, which facilitates the definition of rollback. Moreover, it implements a fine-tuned strategy for backward computation. We present a session type system for the calculus and show that it enforces the expected properties of session fidelity, forward progress and backward progress.

Interface theories allow system designers to reason about the composability and compatibility of concurrent system components. Such theories often extend both de Alfaro and Henzinger’s Interface Automata and Larsen’s Modal Transition Systems, which leads, however, to several issues that are undesirable in practice: an unintuitive treatment of specified unwanted behaviour, a binary compatibility concept that does not scale to multi-component assemblies, and compatibility guarantees that are insufficient for software product lines. In this article we show that communication mismatches are central to all these problems and, thus, the ability to represent such errors semantically is an important feature of an interface theory. Accordingly, we present the error-aware interface theory EMIA, where the above shortcomings are remedied by introducing explicit fatal error states. In addition, we prove via a Galois insertion that EMIA is a conservative generalisation of the established Modal Interface Automata theory.

We combine three extensions of context-free grammars: (a) associating its nonterminals with storage configurations, (b) equipping its rules with weights, and (c) controlling its derivations. For a commutative semiring K, we introduce the class of weighted languages generated by K-weighted linear context-free grammars with storage S and with derivations controlled by (S, K)-recognizable weighted languages. The control on the derivations can be iterated in a natural way. We characterize the n-th iteration of the control in terms of the n-th iteration of the one-turn pushdown operator on the storage S of the control weighted language. Moreover, for each proper semiring we prove that iterating the control yields an infinite, strict hierarchy of classes of weighted languages.

The aim of this study is to understand the inherent expressive power of CTL operators. We investigate the complexity of model checking for all CTL fragments with one CTL operator and arbitrary Boolean operators. This gives us a fingerprint of each CTL operator. The comparison between the fingerprints yields a hierarchy of the operators that mirrors their strength with respect to model checking.