225 research outputs found

    Validating specifications of dynamic systems using automated reasoning techniques

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    In this paper, we propose a new approach to validating formal specifications of observable behavior of discrete dynamic systems. By observable behavior we mean system behavior as observed by users or other systems in the environment of the system. Validation of a formal specification of an informal domain tries to answer the question whether the specification actually describes the intended domain. This differs from the verification problem, which deals with the correspondence between formal objects, e.g. between a formal specification of a system and an implementation of it. We consider formal specifications of object-oriented dynamic systems that are subject to static and dynamic integrity constraints. To validate that such a specification expresses the intended behavior, we propose to use a tool that can answer reachability queries. In a reachability query we ask whether the system can evolve from one state into another without violating the integrity constraints. If the query is answered positively, the system should exhibit an example path between the states; if the answer is negative, the system should explain why this is so. An example path produced by the tool can be used to produce scenarios for presentations of system behavior, but can also be used as a basis for acceptance testing. In this paper, we discuss the use of planning and theoremproving techniques to answer such queries, and illustrate the use of reachability queries in the context of information system development

    Planning as Quantified Boolean Formulae

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    This work explores the idea of classical Planning as Quantified Boolean Formulae. Planning as Satisfiability (SAT) is a popular approach to Planning and has been explored in detail producing many compact and efficient encodings, Planning-specific solver implementations and innovative new constraints. However, Planning as Quantified Boolean Formulae (QBF) has been relegated to conformant Planning approaches, with the exception of one encoding that has not yet been investigated in detail. QBF is a promising setting for Planning given that the problems have the same complexity. This work introduces two approaches for translating bounded propositional reachability problems into QBF. Both exploit the expressivity of the binarytree structure of the QBF problem to produce encodings that are as small as logarithmic in the size of the instance and thus exponentially smaller than the corresponding SAT encoding with the same bound. The first approach builds on the iterative squaring formulation of Rintanen; the intuition behind the idea is to recursively fold the plan around the midpoint, reducing the number of time-steps that need to be described from n to log₂n. The second approach exploits domain-level lifting to achieve significant improvements in efficiency. Experimentation was performed to compare our formulation of the first approach with the previous formulation, and to compare both approaches with comparative and state-of-the-art SAT approaches. Results presented in this work show that our formulation of the first approach is an improvement over the previous, and that both approaches produce encodings that are indeed much smaller than corresponding SAT encodings, in both terms of encoding size and memory used during solving. Evidence is also provided to show that the first approach is feasible, if not yet competitive with the state-of-the-art, and that the second approach produces superior encodings to the SAT encodings when the domain is suited to domain-level lifting.This work explores the idea of classical Planning as Quantified Boolean Formulae. Planning as Satisfiability (SAT) is a popular approach to Planning and has been explored in detail producing many compact and efficient encodings, Planning-specific solver implementations and innovative new constraints. However, Planning as Quantified Boolean Formulae (QBF) has been relegated to conformant Planning approaches, with the exception of one encoding that has not yet been investigated in detail. QBF is a promising setting for Planning given that the problems have the same complexity. This work introduces two approaches for translating bounded propositional reachability problems into QBF. Both exploit the expressivity of the binarytree structure of the QBF problem to produce encodings that are as small as logarithmic in the size of the instance and thus exponentially smaller than the corresponding SAT encoding with the same bound. The first approach builds on the iterative squaring formulation of Rintanen; the intuition behind the idea is to recursively fold the plan around the midpoint, reducing the number of time-steps that need to be described from n to log₂n. The second approach exploits domain-level lifting to achieve significant improvements in efficiency. Experimentation was performed to compare our formulation of the first approach with the previous formulation, and to compare both approaches with comparative and state-of-the-art SAT approaches. Results presented in this work show that our formulation of the first approach is an improvement over the previous, and that both approaches produce encodings that are indeed much smaller than corresponding SAT encodings, in both terms of encoding size and memory used during solving. Evidence is also provided to show that the first approach is feasible, if not yet competitive with the state-of-the-art, and that the second approach produces superior encodings to the SAT encodings when the domain is suited to domain-level lifting

    Resolution-based methods for linear temporal reasoning

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    The aim of this thesis is to explore the potential of resolution-based methods for linear temporal reasoning. On the abstract level, this means to develop new algorithms for automated reasoning about properties of systems which evolve in time. More concretely, we will: 1) show how to adapt the superposition framework to proving theorems in propositional Linear Temporal Logic (LTL), 2) use a connection between superposition and the CDCL calculus of modern SAT solvers to come up with an efficient LTL prover, 3) specialize the previous to reachability properties and discover a close connection to Property Directed Reachability (PDR), an algorithm recently developed for model checking of hardware circuits, 4) further improve PDR by providing a new technique for enhancing clause propagation phase of the algorithm, and 5) adapt PDR to automated planning by replacing the SAT solver inside with a planning-specific procedure. We implemented the proposed ideas and provide experimental results which demonstrate their practical potential on representative benchmark sets. Our system LS4 is shown to be the strongest LTL prover currently publicly available. The mentioned enhancement of PDR substantially improves the performance of our implementation of the algorithm for hardware model checking in the multi-property setting. It is expected that other implementations would benefit from it in an analogous way. Finally, our planner PDRplan has been compared with the state-of-the-art planners on the benchmarks from the International Planning Competition with very promising results.Das Ziel dieser Doktorarbeit ist es, das Potential resolutionsbasierter Methoden zur linearer, temporaler Beweisführung zu untersuchen. Von einem abstrakten Gesichtspunkt aus gesehen bedeutet dies, neue Algorithmen über die Eigenschaften von sich zeitlich entwicklenden Systemen im Bereich des automatischen Theorembeweisens zu entwickeln. Konkreter gesagt werden wir 1) aufzeigen, wie sich das Rahmenprogramm der Superposition so anpassen lässt, damit es Theoreme in propositionaler Linear Temporal Logic (LTL) beweist, 2) eine Verbindung zwischen der Superposition und dem CDCL-Kalkül moderner SAT-Solver nutzen, um mit einem effizienten LTL-Prover aufzuwarten, 3) das Vorangegangene auf Erreichbarkeitseigenschaften spezialisieren, und eine starke Verbindung zu der Property Directed Reachability (PDR), einem jüngst eintwickeltem Model-Checking-Algorithmus für Hardware-Schaltkreise, aufzudecken, 4) PDR durch die Einführung neuer Technik verbessern, die die Clause-Propagation-Phase des Algorithmus beschleunigt, und 5) PDR für das automatisierte Planen anpassen, indem wir den inneren SAT-Solver durch eine planungsspezifische Prozedur ersetzen. Wir haben die vorgeschlagenen Ideen implementiert, und es werden experimentelle Ergebnisse angegeben, die das praktische Potential dieser Ideen auf repräsentativen Benchmarks aufzeigt. Es hat sich herausgestellt, dass unser System LS4 der staerkste öffentlich zugängliche LTL-Prover ist. Die erwähnte Erweiterung von PDR verbessern die Leistungsfähigkeit unserer Implementierung des Hardware-Model-Checking-Algorithmus substantiell im Bereich der Multi-Property-Einstellungen. Wir erwarten, dass andere Implementierungen in ähnlicher Weise profitieren würden. Schließlich haben wir viel versprechende Ergebnisse durch den Vergleich unser Planer PDRplan mit anderen state-of-the-art Planer auf den Benchmarks der International Planning Competition erzielt

    Automated Reasoning

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    This volume, LNAI 13385, constitutes the refereed proceedings of the 11th International Joint Conference on Automated Reasoning, IJCAR 2022, held in Haifa, Israel, in August 2022. The 32 full research papers and 9 short papers presented together with two invited talks were carefully reviewed and selected from 85 submissions. The papers focus on the following topics: Satisfiability, SMT Solving,Arithmetic; Calculi and Orderings; Knowledge Representation and Jutsification; Choices, Invariance, Substitutions and Formalization; Modal Logics; Proofs System and Proofs Search; Evolution, Termination and Decision Prolems. This is an open access book

    28th International Symposium on Temporal Representation and Reasoning (TIME 2021)

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    The 28th International Symposium on Temporal Representation and Reasoning (TIME 2021) was planned to take place in Klagenfurt, Austria, but had to move to an online conference due to the insecurities and restrictions caused by the pandemic. Since its frst edition in 1994, TIME Symposium is quite unique in the panorama of the scientifc conferences as its main goal is to bring together researchers from distinct research areas involving the management and representation of temporal data as well as the reasoning about temporal aspects of information. Moreover, TIME Symposium aims to bridge theoretical and applied research, as well as to serve as an interdisciplinary forum for exchange among researchers from the areas of artifcial intelligence, database management, logic and verifcation, and beyond

    Tools and Algorithms for the Construction and Analysis of Systems

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    This open access book constitutes the proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2022, which was held during April 2-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 46 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 159 submissions. The proceedings also contain 16 tool papers of the affiliated competition SV-Comp and 1 paper consisting of the competition report. TACAS is a forum for researchers, developers, and users interested in rigorously based tools and algorithms for the construction and analysis of systems. The conference aims to bridge the gaps between different communities with this common interest and to support them in their quest to improve the utility, reliability, exibility, and efficiency of tools and algorithms for building computer-controlled systems

    On conflict-driven reasoning

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    Automated formal methods and automated reasoning are interconnected, as formal methods generate reasoning problems and incorporate reasoning techniques. For example, formal methods tools employ reasoning engines to find solutions of sets of constraints, or proofs of conjectures. From a reasoning perspective, the expressivity of the logical language is often directly proportional to the difficulty of the problem. In propositional logic, Conflict-Driven Clause Learning (CDCL) is one of the key features of state-of-the-art satisfiability solvers. The idea is to restrict inferences to those needed to explain conflicts, and use conflicts to prune a backtracking search. A current research direction in automated reasoning is to generalize this notion of conflict-driven satisfiability to a paradigm of conflict-driven reasoning in first-order theories for satisfiability modulo theories and assignments, and even in full first-order logic for generic automated theorem proving. While this is a promising and exciting lead, it also poses formidable challenges

    Logic programming for deliberative robotic task planning

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    Over the last decade, the use of robots in production and daily life has increased. With increasingly complex tasks and interaction in different environments including humans, robots are required a higher level of autonomy for efficient deliberation. Task planning is a key element of deliberation. It combines elementary operations into a structured plan to satisfy a prescribed goal, given specifications on the robot and the environment. In this manuscript, we present a survey on recent advances in the application of logic programming to the problem of task planning. Logic programming offers several advantages compared to other approaches, including greater expressivity and interpretability which may aid in the development of safe and reliable robots. We analyze different planners and their suitability for specific robotic applications, based on expressivity in domain representation, computational efficiency and software implementation. In this way, we support the robotic designer in choosing the best tool for his application

    Modelling and Analysis of Network Security Policies

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    Nowadays, computers and network communications have a pervasive presence in all our daily activities. Their correct configuration in terms of security is becoming more and more complex due to the growing number and variety of services present in a network. Generally, the security configuration of a computer network is dictated by specifying the policies of the security controls (e.g. firewall, VPN gateway) in the network. This implies that the specification of the network security policies is a crucial step to avoid errors in network configuration (e.g., blocking legitimate traffic, permitting unwanted traffic or sending insecure data). In the literature, an anomaly is an incorrect policy specification that an administrator may introduce in the network. In this thesis, we indicate as policy anomaly any conflict (e.g. two triggered policy rules enforcing contradictory actions), error (e.g. a policy cannot be enforced because it requires a cryptographic algorithm not supported by the security controls) or sub-optimization (e.g. redundant policies) that may arise in the policy specification phase. Security administrators, thus, have to face the hard job of correctly specifying the policies, which requires a high level of competence. Several studies have confirmed, in fact, that many security breaches and breakdowns are attributable to administrators’ responsibilities. Several approaches have been proposed to analyze the presence of anomalies among policy rules, in order to enforce a correct security configuration. However, we have identified two limitations of such approaches. On one hand, current literature identifies only the anomalies among policies of a single security technology (i.e., IPsec, TLS), while a network is generally configured with many technologies. On the other hand, existing approaches work on a single policy type, also named domain (i.e., filtering, communication protection). Unfortunately, the complexity of real systems is not self-contained and each network security control may affect the behavior of other controls in the same network. The objective of this PhD work was to investigate novel approaches for modelling security policies and their anomalies, and formal techniques of anomaly analysis. We present in this dissertation our contributions to the current policy analysis state of the art and the achieved results. A first contribution was the definition of a new class of policy anomalies, i.e. the inter-technology anomalies, which arises in a set of policies of multiple security technologies. We provided also a formal model able to detect these new types of anomalies. One of the results achieved by applying the inter-technology analysis to the communication protection policies was to categorize twelve new types of anomalies. The second result of this activity was derived from an empirical assessment that proved the practical significance of detecting such new anomalies. The second contribution of this thesis was the definition of a newly-defined type of policy analysis, named inter-domain analysis, which identifies any anomaly that may arise among different policy domains. We improved the state of the art by proposing a possible model to detect the inter-domain anomalies, which is a generalization of the aforementioned inter-technology model. In particular, we defined the Unified Model for Policy Analysis (UMPA) to perform the inter-domain analysis by extending the analysis model applied for a single policy domain to comprehensive analysis of anomalies among many policy domains. The result of this last part of our dissertation was to improve the effectiveness of the analysis process. Thanks to the inter-domain analysis, indeed, administrators can detect in a simple and customizable way a greater set of anomalies than the sets they could detect by running individually any other model
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