Foundations of Software Science and Computation Structures

This open access book constitutes the proceedings of the 23rd International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The 31 regular papers presented in this volume were carefully reviewed and selected from 98 submissions. The papers cover topics such as categorical models and logics; language theory, automata, and games; modal, spatial, and temporal logics; type theory and proof theory; concurrency theory and process calculi; rewriting theory; semantics of programming languages; program analysis, correctness, transformation, and verification; logics of programming; software specification and refinement; models of concurrent, reactive, stochastic, distributed, hybrid, and mobile systems; emerging models of computation; logical aspects of computational complexity; models of software security; and logical foundations of data bases.

Measurements, Models, Systems and Design

531 s.

The Soundness and Completeness of ACSR (Algebra of Communicating Shared Resources)

Recently, significant progress has been made in the development of timed process algebras for the specification and analysis of real-time systems; one of which is a timed process algebra called ACSR. ACSR supports synchronous timed actions and asynchronous instantaneous events. Timed actions are used to represent the usage of resources and to model the passage of time. Events are used to capture synchronization between processes. To be able to specify real systems accurately, ACSR supports a notion of priority that can be used to arbitrate among timed actions competing for the use of resources and among events that are ready for synchronization. Equivalence between ACSR terms is defined in terms of strong bisimulation. The paper contains a set of algebraic laws that are proven sound and complete for finite ACSR agents

Increasing the capacity of distributed generation in electricity networks by intelligent generator control

The rise of environmental awareness as well as the unstable global fossil fuel market has brought about government initiatives to increase electricity generation from renewable energy sources. These resources tend to be geographically and electrically remote from load centres. Consequently many Distributed Generators (DGs) are expected to be connected to the existing Distribution Networks (DNs), which have high impedance and low X/R ratios. Intermittence and unpredictability of the various types of renewable energy sources can be of time scales of days (hydro) down to seconds (wind, wave). As the time scale becomes smaller, the output of the DG becomes more difficult to accommodate in the DN. With the DGs operating in constant power factor mode, intermittence of the output of the generator combined with the high impedance and low X/R ratios of the DN will cause voltage variations above the statutory limits for quality of supply. This is traditionally mitigated by accepting increased operation of automated network control or network reinforcement. However, due to the distributed nature of RES, automating or reinforcing the DN can be expensive and difficult solutions to implement. The Thesis proposed was that new methods of controlling DG voltage could enable the connection of increased capacities of plant to existing DNs without the need for network management or reinforcement. The work reported here discusses the implications of the increasing capacity of DG in rural distribution networks on steady-state voltage profiles. Two methods of voltage compensation are proposed. The first is a deterministic system that uses a set of rules to intelligently switch between voltage and power factor control modes. This new control algorithm is shown to be able to respond well to slow voltage variations due to load or generation changes. The second method is a fuzzy inference system that adjusts the setpoint of the power factor controller in response to the local voltage. This system can be set to respond to any steady-state voltage variations that will be experienced. Further, control of real power is developed as a supplementary means for voltage regulation in weak rural networks. The algorithms developed in the study are shown to operate with any synchronous or asynchronous generation wherein real and reactive power can be separately controlled. Extensive simulations of typical and real rural systems using synchronous generators (small hydro) and doubly-fed induction generators (wind turbines) have verified that the proposed approaches improve the voltage profile of the distribution network. This demonstrated that the original Thesis was true and that the techniques proposed allow wider operation of greater capacities of DG within the statutory voltage limits

IST Austria Thesis

Motivated by the analysis of highly dynamic message-passing systems, i.e. unbounded thread creation, mobility, etc. we present a framework for the analysis of depth-bounded systems. Depth-bounded systems are one of the most expressive known fragment of the π-calculus for which interesting verification problems are still decidable. Even though they are infinite state systems depth-bounded systems are well-structured, thus can be analyzed algorithmically. We give an interpretation of depth-bounded systems as graph-rewriting systems. This gives more flexibility and ease of use to apply depth-bounded systems to other type of systems like shared memory concurrency. First, we develop an adequate domain of limits for depth-bounded systems, a prerequisite for the effective representation of downward-closed sets. Downward-closed sets are needed by forward saturation-based algorithms to represent potentially infinite sets of states. Then, we present an abstract interpretation framework to compute the covering set of well-structured transition systems. Because, in general, the covering set is not computable, our abstraction over-approximates the actual covering set. Our abstraction captures the essence of acceleration based-algorithms while giving up enough precision to ensure convergence. We have implemented the analysis in the PICASSO tool and show that it is accurate in practice. Finally, we build some further analyses like termination using the covering set as starting point

On the Complexity of Deciding Behavioural Equivalences and Preorders. A Survey

This paper gives an overview of the computational complexity of all the equivalences in the linear/branching time hierarchy [vG90a] and the preordersin the corresponding hierarchy of preorders. We consider finite state or regular processes as well as infinite-state BPA [BK84b] processes. A distinction, which turns out to be important in the finite-state processes, is that of simulation-like equivalences/preorders vs. trace-like equivalencesand preorders. Here we survey various known complexity results for these relations. For regular processes, all simulation-like equivalences and preorders are decidable in polynomial time whereas all trace-like equivalences and preorders are PSPACE-Complete. We also consider interesting specialclasses of regular processes such as deterministic, determinate, unary, locally unary, and tree-like processes and survey the known complexity results inthese special cases. For infinite-state processes the results are quite different. For the class of context-free processes or BPA processes any preorder or equivalence beyond bisimulation is undecidable but bisimulation equivalence is polynomial timedecidable for normed BPA processes and is known to be elementarily decidable in the general case. For the class of BPP processes, all preorders and equivalences apart from bisimilarity are undecidable. However, bisimilarityis decidable in this case and is known to be decidable in polynomial time for normed BPP processes