The most studied and accepted pseudometric for probabilistic processes is one based on the Kantorovich distance between distributions. It comes with many theoretical and motivating results, in particular it is the fixpoint of a given functional and defines a functor on (complete) pseudometric spaces. Other notions of behavioural pseudometrics have also been proposed, one of them ($ε$-distance) based on $ε$-bisimulation. $ε$-Distance has the advantages that it is intuitively easy to understand, it relates systems that are conceptually close (for example, an imperfect implementation is close to its specification), and it comes equipped with a natural notion of $ε$-coupling. Finally, this distance is easy to compute. We show that $ε$-distance is also the greatest fixpoint of a functional and provides a functor. The latter is obtained by replacing the Kantorovich distance in the lifting functor with the Lévy-Prokhorov distance. In addition, we show that $ε$-couplings and $ε$-bisimulations have an appealing coalgebraic characterization.

Probabilistic models of computation have been studied for over three decades now, from foundational, logical, coalgebraic, categorical, as well as more practical verification-motivated point of view. In my work, and in this talk, we focus on the foundational, semantics side of probabilistic automata and transition systems, and in particular the relevant monads, and their algebras. The interplay of probability and non-determinism has been particularly challenging from a semantics point of view for some decades, as it does not just yield a monad. There are by now well-studied solutions to this and several monads for probability and non-determinism: some enriching the structure with convexity to obtain a monad, albeit a non-commutative one, others deliberately simplifying it, by imposing commutativity. It is well known that monads have two faces: a computational one - we think here of the powerset monad modelling non-determinism, or the probability distribution monad modelling probabilistic choices, and a universal-algebraic one - where we think of the algebraic presentation of the monads, like semilattices for the powerset monad and (variants of) convex algebras for (variants of) the probability distribution monad. Combining non-determinism and probability yields other combined monads, among which probably the most studied is the convex-subsets-of-distributions monad. This monad is presented by so-called convex semilattices, algebraic structures that are both a semilattice and a convex algebra, with suitable distributivity connecting the operations. From a semantics point of view, the algebraic presentations give us a nice way to define (and sometimes compute) language (aka trace) equivalence of the corresponding automata. Moreover, the presentations are useful for axiomatizations of language equivalence. From an algebraic point of view, these algebras are interesting and many questions about them are still open. We will discuss language semantics, its axiomatization, as well as some obtained and open algebraic problems for convex algebras and convex semilattices - and their computational consequences. In particular, we have a full characterization of congruences of (variants of) convex algebras, which for example yields decidability of distribution semantics; other results on congruences, e.g. a result on a congruence being finitely generated as a subalgebra, surprisingly accellerated the proof of completeness of infinite trace semanitcs, etc. We will review some existing results: all congruences are described and fp = fg for convex algebras, termination is a black hole, useful functors are proper on convex algebras, cancellativity of convex semi-lattices; as well as mention ongoing work on: mid-point-cancellativity, subalgebras, and homomorphisms for convex semi-lattices, as well as topological convex semilattices. This talk is based on previous joint works with Filippo Bonchi, Alexandra Silva, Valeria Vignudelli, and Harald Woracek, as well as on ongoing work and discussions with Matteo Mio, Alex Simpson, and Harald Woracek.

Convex semilattices are algebras that are at the same time a convex algebra and a semilattice, together with a distributivity axiom. These algebras have attracted some attention in the last years as suitable algebras for probability and nondeterminism, in particular by being the Eilenberg-Moore algebras of the nonempty finitely-generated convex subsets of the distributions monad. A convex semilattice is cancellative if the underlying convex algebra is cancellative. Cancellative convex algebras have been characterized by M. H. Stone and by H. Kneser: A convex algebra is cancellative if and only if it is isomorphic to a convex subset of a vector space (with canonical convex algebra operations). We prove an analogous theorem for convex semilattices: A convex semilattice is cancellative if and only if it is isomorphic to a convex subset of a Riesz space, i.e., a lattice-ordered vector space (with canonical convex semilattice operations).

We present the first sound and complete axiomatization of infinite trace semantics for generative probabilistic transition systems. Our approach is categorical, and we build on recent results on proper functors over convex sets. At the core of our proof is a characterization of infinite traces as the final coalgebra of a functor over convex algebras. Somewhat surprisingly, our axiomatization of infinite trace semantics coincides with that of finite trace semantics, even though the techniques used in the completeness proof are significantly different.

Abstract The 27th International Symposium on Model Checking Software, SPIN 2021, was held online, July 12, 2021. The current special issue contains extended versions of three selected works published at the symposium. This short introduction presents these selected papers and the selection process.

This paper studies trace-based equivalences for systems combining nondeterministic and probabilistic choices. We show how trace semantics for such processes can be recovered by instantiating a coalgebraic construction known as the generalised powerset construction. We characterise and compare the resulting semantics to known definitions of trace equivalences appearing in the literature. Most of our results are based on the exciting interplay between monads and their presentations via algebraic theories.

We prove that every finitely generated convex set of finitely supported probability distributions has a unique base. We apply this result to provide an alternative proof of a recent result: the algebraic theory of convex semilattices presents the monad of convex sets of probability distributions.

We reprove the countable splitting lemma by adapting Nawrotzki’s algorithm which produces a sequence that converges to a solution. Our algorithm combines Nawrotzki’s approach with taking finite cuts. It is constructive in the sense that each term of the iteratively built approximating sequence as well as the error between the approximants and the solution is computable with finitely many algebraic operations.

Probabilistic automata (PA), also known as probabilistic nondeterministic labelled transition systems, combine probability and nondeterminism. They can be given different semantics, like strong bisimilarity, convex bisimilarity, or (more recently) distribution bisimilarity. The latter is based on the view of PA as transformers of probability distributions, also called belief states, and promotes distributions to first-class citizens. We give a coalgebraic account of distribution bisimilarity, and explain the genesis of the belief-state transformer from a PA. To do so, we make explicit the convex algebraic structure present in PA and identify belief-state transformers as transition systems with state space that carries a convex algebra. As a consequence of our abstract approach, we can give a sound proof technique which we call bisimulation up-to convex hull.

This paper studies trace-based equivalences for systems combining nondeterministic and probabilistic choices. We show how trace semantics for such processes can be recovered by instantiating a coalgebraic construction known as the generalised powerset construction. We characterise and compare the resulting semantics to known definitions of trace equivalences appearing in the literature. Most of our results are based on the exciting interplay between monads and their presentations via algebraic theories.

This special issue contains selected papers from the International Workshop on Proof, Structure, and Computation (PSC) held in Vienna on 17–18 July 2014, within the Vienna Summer of Logic (VSL). PSC was a CSL–LICS-affiliated workshop on the extraction of computational content from proofs. The focus is on the computational aspects of proofs and the specification of the structures involved; the topics of interest are proof theory, program extraction, constructive mathematics, topology and computation, realizability semantics, coalgebra and computation, categorical models and domain theory. The extraction of computational content from proofs has a long tradition in logic, but usually depends on a concrete encoding that allows us to turn proofs into algorithms. A recent trend in this field is the departure from such encoding, which not only makes it simpler to represent the mathematical content, but also makes the extracted computational content encoding independent. This shift in focus allows us to focus on what is relevant: the computational aspects of proofs and the specification (not representation) of the structures involved. We now have growing evidence that this move from representations (e.g. the signed-digit representation of the reals) to axioms (e.g. of the real numbers) is possible. This development largely parallels the step from assembler to high-level languages in programming. As a by-product, this move has already opened up the possibility to gain computational information from axiomatic proofs in more abstract and genuinely structural areas of mathematics such as algebra and topology.

Esik and Maletti introduced the notion of a proper semiring and proved that some important (classes of) semirings – Noetherian semirings, natural numbers – are proper. Properness matters as the equivalence problem for weighted automata over a semiring which is proper and finitely and effectively presented is decidable. Milius generalised the notion of properness from a semiring to a functor. As a consequence, a semiring is proper if and only if its associated “cubic functor” is proper. Moreover, properness of a functor renders soundness and completeness proofs for axiomatizations of equivalent behaviour. In this paper we provide a method for proving properness of functors, and instantiate it to cover both the known cases and several novel ones: (1) properness of the semirings of positive rationals and positive reals, via properness of the corresponding cubic functors; and (2) properness of two functors on (positive) convex algebras. The latter functors are important for axiomatizing trace equivalence of probabilistic transition systems. Our proofs rely on results that stretch all the way back to Hilbert and Minkowski.

Convex algebras, also called (semi)convex sets, are at the heart of modelling probabilistic systems including probabilistic automata. Abstractly, they are the Eilenberg-Moore algebras of the finitely supported distribution monad. Concretely, they have been studied for decades within algebra and convex geometry. In this paper we study the problem of extending a convex algebra by a single point. Such extensions enable the modelling of termination in probabilistic systems. We provide a full description of all possible extensions for a particular class of convex algebras: For a fixed convex subset $D$ of a vector space satisfying additional technical condition, we consider the algebra of convex subsets of $D$. This class contains the convex algebras of convex subsets of distributions, modelling (nondeterministic) probabilistic automata. We also provide a full description of all possible extensions for the class of free convex algebras, modelling fully probabilistic systems. Finally, we show that there is a unique functorial extension, the so-called black-hole extension.

Convex algebras, also called (semi)convex sets, are at the heart of modelling probabilistic systems including probabilistic automata. Abstractly, they are the Eilenberg-Moore algebras of the finitely supported distribution monad. Concretely, they have been studied for decades within algebra and convex geometry. In this paper we study the problem of extending a convex algebra by a single point. Such extensions enable the modelling of termination in probabilistic systems. We provide a full description of all possible extensions for a particular class of convex algebras: For a fixed convex subset $D$ of a vector space satisfying additional technical condition, we consider the algebra of convex subsets of $D$. This class contains the convex algebras of convex subsets of distributions, modelling (nondeterministic) probabilistic automata. We also provide a full description of all possible extensions for the class of free convex algebras, modelling fully probabilistic systems. Finally, we show that there is a unique functorial extension, the so-called black-hole extension.

Probabilistic automata (PA) combine probability and nondeterminism. They can be given different semantics, like strong bisimilarity, convex bisimilarity, or (more recently) distribution bisimilarity. The latter is based on the view of PA as transformers of probability distributions, also called belief states, and promotes distributions to first-class citizens. We give a coalgebraic account of the latter semantics, and explain the genesis of the belief-state transformer from a PA. To do so, we make explicit the convex algebraic structure present in PA and identify belief-state transformers as transition systems with state space that carries a convex algebra. As a consequence of our abstract approach, we can give a sound proof technique which we call bisimulation up-to convex hull.

Priority queues with parallel access are an attractive data structure for applications like prioritized online scheduling, discrete event simulation, or greedy algorithms. However, a classical priority queue constitutes a severe bottleneck in this context, leading to very small throughput. Hence, there has been significant interest in concurrent priority queues with relaxed semantics. We investigate the complementary quality criteria rank error (how close are deleted elements to the global minimum) and delay (for each element x, how many elements with lower priority are deleted before x). In this paper, we introduce MultiQueues as a natural approach to relaxed priority queues based on multiple sequential priority queues. Their naturally high theoretical scalability is further enhanced by using three orthogonal ways of batching operations on the sequential queues. Experiments indicate that MultiQueues present a very good performance-quality tradeoff and considerably outperform competing approaches in at least one of these aspects. We employ a seemingly paradoxical technique of "wait-free locking" that might be of more general interest to convert sequential data structures to relaxed concurrent data structures.

We demonstrate that general-purpose memory allocation involving many threads on many cores can be done with high performance, multicore scalability, and low memory consumption. For this purpose, we have designed and implemented scalloc, a concurrent allocator that generally performs and scales in our experiments better than other allocators while using less memory, and is still competitive otherwise. The main ideas behind the design of scalloc are: uniform treatment of small and big objects through so-called virtual spans, efficiently and effectively reclaiming free memory through fast and scalable global data structures, and constant-time (modulo synchronization) allocation and deallocation operations that trade off memory reuse and spatial locality without being subject to false sharing.

There is a trade-off between performance and correctness in implementing concurrent data structures. Better performance may be achieved at the expense of relaxing correctness, by redefining the semantics of data structures. We address such a redefinition of data structure semantics and present a systematic and formal framework for obtaining new data structures by quantitatively relaxing existing ones. We view a data structure as a sequential specification S containing all "legal" sequences over an alphabet of method calls. Relaxing the data structure corresponds to defining a distance from any sequence over the alphabet to the sequential specification: the k-relaxed sequential specification contains all sequences over the alphabet within distance k from the original specification. In contrast to other existing work, our relaxations are semantic (distance in terms of data structure states). As an instantiation of our framework, we present two simple yet generic relaxation schemes, called out-of-order and stuttering relaxation, along with several ways of computing distances. We show that the out-of-order relaxation, when further instantiated to stacks, queues, and priority queues, amounts to tolerating bounded out-of-order behavior, which cannot be captured by a purely syntactic relaxation (distance in terms of sequence manipulation, e.g. edit distance). We give concurrent implementations of relaxed data structures and demonstrate that bounded relaxations provide the means for trading correctness for performance in a controlled way. The relaxations are monotonic which further highlights the trade-off: increasing k increases the number of permitted sequences, which as we demonstrate can lead to better performance. Finally, since a relaxed stack or queue also implements a pool, we actually have new concurrent pool implementations that outperform the state-of-the-art ones.

We propose a new memory model called short-term memory for managing objects on the heap. In contrast to the traditional persistent memory model for heap management, objects in short-term memory expire after a finite amount of time, which makes deallocation unnecessary. Instead, expiration of objects may be extended, if necessary, by refreshing. We have developed a concurrent, incremental, and non-moving implementation of short-term memory for explicit refreshing called self-collecting mutators that is based on programmer-controlled time and integrated into state-of-the-art runtimes of three programming languages: C, Java, and Go. All memory management operations run in constant time without acquiring any locks modulo the underlying allocators. Our implementation does not require any additional heap management threads, hence the name. Expired objects may be collected anywhere between one at a time for maximal incrementality and all at once for maximal throughput and minimal memory consumption. The integrated systems are heap management hybrids with persistent memory as default and short-term memory as option. Our approach is fully backwards compatible. Legacy code runs without any modifications with negligible runtime overhead and constant per-object space overhead. Legacy code can be modified to take advantage of short-term memory by having some but not all objects allocated in short-term memory and managed by explicit refreshing. We study single- and multi-threaded use cases in all three languages macro-benchmarking C and Java and micro-benchmarking Go. Our results show that using short-term memory (1) simplifies heap management in a state-of-the-art H.264 encoder written in C without additional time and minor space overhead, and (2) improves, at the expense of safety, memory management throughput, latency, and space consumption by reducing the number of garbage collection runs, often even to zero, for a number of Java and Go programs.

Maintaining data structure semantics of concurrent queues such as first-in first-out (FIFO) ordering requires expensive synchronization mechanisms which limit scalability. However, deviating from the original semantics of a given data structure may allow for a higher degree of scalability and yet be tolerated by many concurrent applications. We introduce the notion of a k-FIFO queue which may be out of FIFO order up to a constant k (called semantical deviation). Implementations of k-FIFO queues may be distributed and therefore be accessed unsynchronized while still being starvation-free. We show that k-FIFO queues whose implementations are based on state-of-the-art FIFO queues, which typically do not scale under high contention, provide scalability. Moreover, probabilistic versions of k-FIFO queues improve scalability further but only bound semantical deviation with high probability.

We survey the work on both discrete and continuous-space probabilistic systems as coalgebras, starting with how probabilistic systems are modeled as coalgebras and followed by a discussion of their bisimilarity and behavioral equivalence, mentioning results that follow from the coalgebraic treatment of probabilistic systems. It is interesting to note that, for different reasons, for both discrete and continuous probabilistic systems it may be more convenient to work with behavioral equivalence than with bisimilarity.

Variable-bandwidth servers (VBS) control process execution speed by allocating variable CPU bandwidth to processes. VBS enables temporal isolation of EDF-scheduled processes in the sense that the variance in CPU throughput and latency of each process is bounded independently of any other concurrently running processes. In this paper we aim at reducing CPU power consumption with VBS by CPU voltage and frequency scaling while maintaining temporal isolation. Scaling to lower frequencies is possible whenever there is CPU slack in the system. We first show that, in the presence of CPU slack, frequency scaling of EDF-scheduled, possibly non-periodic tasks (as they arise with VBS) is safe up to full CPU utilization and propose a frequency-scaling VBS algorithm that exploits CPU slack to minimize operating frequencies with maximal CPU utilization while maintaining temporal isolation. Additional power may be saved by redistributing computation time of individual processes while still maintaining temporal isolation if the system has knowledge of future events. We introduce an offline algorithm as an optimal baseline and an online algorithm that approximates the baseline. While the offline algorithm works for various, possibly complex power consumption models, the online algorithm may reduce power consumption only for a simplified power consumption model by reducing the CPU utilization jitter in the system.

We propose two complementary methods to account for scheduler overhead in the schedulability analysis of Variable Bandwidth Servers (VBS), which control process execution speed by allocating variable CPU bandwidth to processes. Scheduler overhead in VBS may be accounted for either by decreasing process execution speed to maintain CPU utilization (called response accounting), or by increasing CPU utilization to maintain process execution speed (called utilization accounting). Both methods can be combined by handling an arbitrary fraction of the total scheduler overhead with one method and the rest with the other. Distinguishing scheduler overhead due to releasing and due to suspending processes allows us to further improve our analysis by accounting for releasing overhead in a separate, virtual VBS process. Although our analysis is based on the VBS model, the general idea of response and utilization accounting may also be applied to other, related scheduling methods.

Abstract. This paper investigates expressivity of modal logics for transition sys-tems, multitransition systems, Markov chains, and Markov processes, as coal-gebras of the powerset, finitely supported multiset, finitely supported distribu-tion, and measure functor, respectively. Expressivity means that logically indis-tinguishable states, satisfying the same formulas, are behaviourally indistinguish-able. The investigation is based on the framework of dual adjunctions between spaces and logics and focuses on a crucial injectivity property. The approach is generic both in the choice of systems and modalities, and in the choice of a “base logic”. Most of these expressivity results are already known, but the applicability of the uniform setting of dual adjunctions to these particular examples is what constitutes the contribution of the paper. 1

The Hierarchical Timing Language (HTL) is a real-time coordination language for distributed control systems. HTL programs must be checked for well-formedness, race freedom, transmission safety (schedulability of inter-host communication), and time safety (schedulability of host computation). We present a modular abstract syntax and semantics for HTL, modular checks of well-formedness, race freedom, and transmission safety, and modular code distribution. Our contributions here complement previous results on HTL time safety and modular code generation. Modularity in HTL can be utilized in easy program composition as well as fast program analysis and code generation, but also in so-called runtime patching, where program components may be modified at runtime.

Trace semantics has been defined for various kinds of state-based systems, notably with different forms of branching such as non-determinism vs. probability. In this paper we claim to identify one underlying mathematical structure behind these "trace semantics," namely coinduction in a Kleisli category. This claim is based on our technical result that, under a suitably order-enriched setting, a final coalgebra in a Kleisli category is given by an initial algebra in the category Sets. Formerly the theory of coalgebras has been employed mostly in Sets where coinduction yields a finer process semantics of bisimilarity. Therefore this paper extends the application field of coalgebras, providing a new instance of the principle "process semantics via coinduction."