arXiv subjects

Ichiro Hasuo

Publications and source records attributed to Ichiro Hasuo.

At least 37 records · Page 2Linked to original sources

arXiv2024

Temporal Logic Formalisation of ISO 34502 Critical Scenarios: Modular Construction with the RSS Safety Distance

As the development of autonomous vehicles progresses, efficient safety assurance methods become increasingly necessary. Safety assurance methods such as monitoring and scenario-based testing call for formalisation of driving scenarios. In this paper, we develop a temporal-logic formalisation of an important class of critical scenarios in the ISO standard 34502. We use signal temporal logic (STL) as a logical formalism. Our formalisation has two main features: 1) modular composition of logical formulas for systematic and comprehensive formalisation (following the compositional methodology of ISO 34502); 2) use of the RSS distance for defining danger. We find our formalisation comes with few parameters to tune thanks to the RSS distance. We experimentally evaluated our formalisation; using its results, we discuss the validity of our formalisation and its stability with respect to the choice of some parameter values.

cs.RO↗

arXiv2024

Efficient Matching with Memoization for Regexes with Look-around and Atomic Grouping (Extended Version)

Regular expression (regex) matching is fundamental in many applications, especially in web services. However, matching by backtracking -- preferred by most real-world implementations for its practical performance and backward compatibility -- can suffer from so-called catastrophic backtracking, which makes the number of backtracking super-linear and leads to the well-known ReDoS vulnerability. Inspired by a recent algorithm by Davis et al. that runs in linear time for (non-extended) regexes, we study efficient backtracking matching for regexes with two common extensions, namely look-around and atomic grouping. We present linear-time backtracking matching algorithms for these extended regexes. Their efficiency relies on memoization, much like the one by Davis et al.; we also strive for smaller memoization tables by carefully trimming their range. Our experiments -- we used some real-world regexes with the aforementioned extensions -- confirm the performance advantage of our algorithms.

cs.PL↗

arXiv2024

Pareto Curves for Compositionally Model Checking String Diagrams of MDPs

Computing schedulers that optimize reachability probabilities in MDPs is a standard verification task. To address scalability concerns, we focus on MDPs that are compositionally described in a high-level description formalism. In particular, this paper considers string diagrams, which specify an algebraic, sequential composition of subMDPs. Towards their compositional verification, the key challenge is to locally optimize schedulers on subMDPs without considering their context in the string diagram. This paper proposes to consider the schedulers in a subMDP which form a Pareto curve on a combination of local objectives. While considering all such schedulers is intractable, it gives rise to a highly efficient sound approximation algorithm. The prototype on top of the model checker Storm demonstrates the scalability of this approach.

cs.LO↗

arXiv2023

Control-Data Separation and Logical Condition Propagation for Efficient Inference on Probabilistic Programs

We present a novel sampling framework for probabilistic programs. The framework combines two recent ideas -- \emph{control-data separation} and \emph{logical condition propagation} -- in a nontrivial manner so that the two ideas boost the benefits of each other. We implemented our algorithm on top of Anglican. The experimental results demonstrate our algorithm's efficiency, especially for programs with while loops and rare observations.

cs.LG↗

arXiv2023

Formal Verification of Safety Architectures for Automated Driving

Safety architectures play a crucial role in the safety assurance of automated driving vehicles (ADVs). They can be used as safety envelopes of black-box ADV controllers, and for graceful degradation from one ODD to another. Building on our previous work on the formalization of responsibility-sensitive safety (RSS), we introduce a novel program logic that accommodates assume-guarantee reasoning and fallback-like constructs. This allows us to formally define and prove the safety of existing and novel safety architectures. We apply the logic to a pull over scenario and experimentally evaluate the resulting safety architecture.

cs.RO↗

arXiv2023

Formal Verification of Intersection Safety for Automated Driving

We build on our recent work on formalization of responsibility-sensitive safety (RSS) and present the first formal framework that enables mathematical proofs of the safety of control strategies in intersection scenarios. Intersection scenarios are challenging due to the complex interaction between vehicles; to cope with it, we extend the program logic dFHL in the previous work and introduce a novel formalism of hybrid control flow graphs on which our algorithm can automatically discover an RSS condition that ensures safety. An RSS condition thus discovered is experimentally evaluated; we observe that it is safe (as our safety proof says) and is not overly conservative.

cs.RO↗

arXiv2023

Compositional Probabilistic Model Checking with String Diagrams of MDPs

We present a compositional model checking algorithm for Markov decision processes, in which they are composed in the categorical graphical language of string diagrams. The algorithm computes optimal expected rewards. Our theoretical development of the algorithm is supported by category theory, while what we call decomposition equalities for expected rewards act as a key enabler. Experimental evaluation demonstrates its performance advantages.

cs.LO↗

arXiv2023

Compositional Solution of Mean Payoff Games by String Diagrams

Following our recent development of a compositional model checking algorithm for Markov decision processes, we present a compositional framework for solving mean payoff games (MPGs). The framework is derived from category theory, specifically that of monoidal categories: MPGs (extended with open ends) get composed in so-called string diagrams and thus organized in a monoidal category; their solution is then expressed as a functor, whose preservation properties embody compositionality. As usual, the key question to compositionality is how to enrich the semantic domain; the categorical framework gives an informed guidance in solving the question by singling out the algebraic structure required in the extended semantic domain. We implemented our compositional solution in Haskell; depending on benchmarks, it can outperform an existing algorithm by an order of magnitude.

cs.LO↗

arXiv2023

Exploiting Adjoints in Property Directed Reachability Analysis

We formulate, in lattice-theoretic terms, two novel algorithms inspired by Bradley's property directed reachability algorithm. For finding safe invariants or counterexamples, the first algorithm exploits over-approximations of both forward and backward transition relations, expressed abstractly by the notion of adjoints. In the absence of adjoints, one can use the second algorithm, which exploits lower sets and their principals. As a notable example of application, we consider quantitative reachability problems for Markov Decision Processes.

cs.LO↗

arXiv2023

Online Causation Monitoring of Signal Temporal Logic

Online monitoring is an effective validation approach for hybrid systems, that, at runtime, checks whether the (partial) signals of a system satisfy a specification in, e.g., Signal Temporal Logic (STL). The classic STL monitoring is performed by computing a robustness interval that specifies, at each instant, how far the monitored signals are from violating and satisfying the specification. However, since a robustness interval monotonically shrinks during monitoring, classic online monitors may fail in reporting new violations or in precisely describing the system evolution at the current instant. In this paper, we tackle these issues by considering the causation of violation or satisfaction, instead of directly using the robustness. We first introduce a Boolean causation monitor that decides whether each instant is relevant to the violation or satisfaction of the specification. We then extend this monitor to a quantitative causation monitor that tells how far an instant is from being relevant to the violation or satisfaction. We further show that classic monitors can be derived from our proposed ones. Experimental results show that the two proposed monitors are able to provide more detailed information about system evolution, without requiring a significantly higher monitoring cost.

eess.SY↗

arXiv2022

The Lattice-Theoretic Essence of Property Directed Reachability Analysis

We present LT-PDR, a lattice-theoretic generalization of Bradley's property directed reachability analysis (PDR) algorithm. LT-PDR identifies the essence of PDR to be an ingenious combination of verification and refutation attempts based on the Knaster-Tarski and Kleene theorems. We introduce four concrete instances of LT-PDR, derive their implementation from a generic Haskell implementation of LT-PDR, and experimentally evaluate them. We also present a categorical structural theory that derives these instances.

cs.LO↗

arXiv2022

Dynamic Shielding for Reinforcement Learning in Black-Box Environments

It is challenging to use reinforcement learning (RL) in cyber-physical systems due to the lack of safety guarantees during learning. Although there have been various proposals to reduce undesired behaviors during learning, most of these techniques require prior system knowledge, and their applicability is limited. This paper aims to reduce undesired behaviors during learning without requiring any prior system knowledge. We propose dynamic shielding: an extension of a model-based safe RL technique called shielding using automata learning. The dynamic shielding technique constructs an approximate system model in parallel with RL using a variant of the RPNI algorithm and suppresses undesired explorations due to the shield constructed from the learned model. Through this combination, potentially unsafe actions can be foreseen before the agent experiences them. Experiments show that our dynamic shield significantly decreases the number of undesired events during training.

cs.LG↗

arXiv2022

Time-Staging Enhancement of Hybrid System Falsification

Optimization-based falsification employs stochastic optimization algorithms to search for error input of hybrid systems. In this paper we introduce a simple idea to enhance falsification, namely time staging, that allows the time-causal structure of time-dependent signals to be exploited by the optimizers. Time staging consists of running a falsification solver multiple times, from one interval to another, incrementally constructing an input signal candidate. Our experiments show that time staging can dramatically increase performance in some realistic examples. We also present theoretical results that suggest the kinds of models and specifications for which time staging is likely to be effective.

eess.SY↗

arXiv2022

Goal-Aware RSS for Complex Scenarios via Program Logic

We introduce a goal-aware extension of responsibility-sensitive safety (RSS), a recent methodology for rule-based safety guarantee for automated driving systems (ADS). Making RSS rules guarantee goal achievement -- in addition to collision avoidance as in the original RSS -- requires complex planning over long sequences of manoeuvres. To deal with the complexity, we introduce a compositional reasoning framework based on program logic, in which one can systematically develop RSS rules for smaller subscenarios and combine them to obtain RSS rules for bigger scenarios. As the basis of the framework, we introduce a program logic dFHL that accommodates continuous dynamics and safety conditions. Our framework presents a dFHL-based workflow for deriving goal-aware RSS rules; we discuss its software support, too. We conducted experimental evaluation using RSS rules in a safety architecture. Its results show that goal-aware RSS is indeed effective in realising both collision avoidance and goal achievement.

cs.RO↗

arXiv2022

Responsibility-Sensitive Safety: an Introduction with an Eye to Logical Foundations and Formalization

Responsibility-sensitive safety (RSS) is an approach to the safety of automated driving systems (ADS). It aims to introduce mathematically formulated safety rules, compliance with which guarantees collision avoidance as a mathematical theorem. However, despite the emphasis on mathematical and logical guarantees, the logical foundations and formalization of RSS are largely an unexplored topic of study. In this paper, we present an introduction to RSS, one that we expect will bridge between different research communities and pave the way to a logical theory of RSS, its mathematical formalization, and software tools of practical use.

cs.RO↗

arXiv2022

Exemplifying parametric timed specifications over signals with bounded behavior

Specifying properties can be challenging work. In this paper, we propose an automated approach to exemplify properties given in the form of automata extended with timing constraints and timing parameters, and that can also encode constraints over real-valued signals. That is, given such a specification and given an admissible automaton for each signal, we output concrete runs exemplifying real (or impossible) runs for this specification. Specifically, our method takes as input a specification, and a set of admissible behaviors, all given as a subclass of rectangular hybrid automata, namely timed automata extended with arbitrary clock rates, signal constraints, and timing parameters. Our method then generates concrete runs exemplifying the specification.

cs.FL↗

arXiv2021

A Compositional Approach to Parity Games

In this paper, we introduce open parity games, which is a compositional approach to parity games. This is achieved by adding open ends to the usual notion of parity games. We introduce the category of open parity games, which is defined using standard definitions for graph games. We also define a graphical language for open parity games as a prop, which have recently been used in many applications as graphical languages. We introduce a suitable semantic category inspired by the work by Grellois and Melliès on the semantics of higher-order model checking. Computing the set of winning positions in open parity games yields a functor to the semantic category. Finally, by interpreting the graphical language in the semantic category, we show that this computation can be carried out compositionally.

cs.GT↗

arXiv2021

Fibrational Initial Algebra-Final Coalgebra Coincidence over Initial Algebras: Turning Verification Witnesses Upside Down

The coincidence between initial algebras (IAs) and final coalgebras (FCs) is a phenomenon that underpins various important results in theoretical computer science. In this paper, we identify a general fibrational condition for the IA-FC coincidence, namely in the fiber over an initial algebra in the base category. Identifying (co)algebras in a fiber as (co)inductive predicates, our fibrational IA-FC coincidence allows one to use coinductive witnesses (such as invariants) for verifying inductive properties (such as liveness). Our general fibrational theory features the technical condition of stability of chain colimits; we extend the framework to the presence of a monadic effect, too, restricting to fibrations of complete lattice-valued predicates. Practical benefits of our categorical theory are exemplified by new "upside-down" witness notions for three verification problems: probabilistic liveness, and acceptance and model-checking with respect to bottom-up tree automata.

cs.LO↗