arXiv subjects

Marek Chalupa

Publications and source records attributed to Marek Chalupa.

9 recordsLinked to original sources

arXiv2026

Quantitative Monitoring of Signal First-Order Logic

Runtime monitoring checks, during execution, whether a partial signal produced by a hybrid system satisfies its specification. Signal First-Order Logic (SFO) offers expressive real-time specifications over such signals, but currently comes only with Boolean semantics and has no tool support. We provide the first robustness-based quantitative semantics for SFO, enabling the expression and evaluation of rich real-time properties beyond the scope of existing formalisms such as Signal Temporal Logic. To enable online monitoring, we identify a past-time fragment of SFO and give a pastification procedure that transforms bounded-response SFO formulas into equisatisfiable formulas in this fragment. We then develop an efficient runtime monitoring algorithm for this past-time fragment and evaluate its performance on a set of benchmarks, demonstrating the practicality and effectiveness of our approach. To the best of our knowledge, this is the first publicly available prototype for online quantitative monitoring of full SFO.

cs.LO↗

arXiv2025

Flavors of Quantifiers in Hyperlogics

Hypertrace logic is a sorted first-order logic with separate sorts for time and execution traces. Its formulas specify hyperproperties, which are properties relating multiple traces. In this work, we extend hypertrace logic by introducing trace quantifiers that range over the set of all possible traces. In this extended logic, formulas can quantify over two kinds of trace variables: constrained trace variables, which range over a fixed set of traces defined by the model, and unconstrained trace variables, which can be assigned to any trace. In comparison, hyperlogics such as HyperLTL have only constrained trace quantifiers. We use hypertrace logic to study how different quantifier patterns affect the decidability of the satisfiability problem. We prove that hypertrace logic without constrained trace quantifiers is equivalent to monadic second-order logic of one successor (S1S), and therefore satisfiable, and that the trace-prefixed fragment (all trace quantifiers precede all time quantifiers) is equivalent to HyperQPTL. Moreover, we show that all hypertrace formulas where the only alternation between constrained trace quantifiers is from an existential to a universal quantifier are equisatisfiable to formulas without constraints on their trace variables and, therefore, decidable as well. Our framework allows us to study also time-prefixed hyperlogics, for which we provide new decidability and undecidability results

cs.LO↗

arXiv2025

Monitoring Hyperproperties over Observed and Constructed Traces

We study the problem of monitoring at runtime whether a system fulfills a specification defined by a hyperproperty, such as linearizability or variants of non-interference. For this purpose, we introduce specifications with both passive and active quantification over traces. While passive trace quantifiers range over the traces that are observed, active trace quantifiers are instantiated with \emph{generator functions}, which are part of the specification. Generator functions enable the monitor to construct traces that may never be observed at runtime, such as the linearizations of a concurrent trace. As specification language, we extend hypernode logic with trace quantifiers over generator functions and interpret these hypernode formulas over possibly infinite domains. We present a corresponding monitoring algorithm, which we implemented and evaluated on a range of hyperproperties for concurrency and security applications. Our method enables, for the first time, the monitoring of asynchronous hyperproperties that contain alternating trace quantifiers.

cs.LO↗

arXiv2025

QuAK: Quantitative Automata Kit

System behaviors are traditionally evaluated through binary classifications of correctness, which do not suffice for properties involving quantitative aspects of systems and executions. Quantitative automata offer a more nuanced approach, mapping each execution to a real number by incorporating weighted transitions and value functions generalizing acceptance conditions. In this paper, we introduce QuAK, the first tool designed to automate the analysis of quantitative automata. QuAK currently supports a variety of quantitative automaton types, including Inf, Sup, LimInf, LimSup, LimInfAvg, and LimSupAvg automata, and implements decision procedures for problems such as emptiness, universality, inclusion, equivalence, as well as for checking whether an automaton is safe, live, or constant. Additionally, QuAK is able to compute extremal values when possible, construct safety-liveness decompositions, and monitor system behaviors. We demonstrate the effectiveness of QuAK through experiments focusing on the inclusion, constant-function check, and monitoring problems.

cs.FL↗

arXiv2025

Automating the Analysis of Quantitative Automata with QuAK

Quantitative automata model beyond-boolean aspects of systems: every execution is mapped to a real number by incorporating weighted transitions and value functions that generalize acceptance conditions of boolean $ω$-automata. Despite the theoretical advances in systems analysis through quantitative automata, the first comprehensive software tool for quantitative automata (Quantitative Automata Kit, or QuAK) was developed only recently. QuAK implements algorithms for solving standard decision problems, e.g., emptiness and universality, as well as constructions for safety and liveness of quantitative automata. We present the architecture of QuAK, which reflects that all of these problems reduce to either checking inclusion between two quantitative automata or computing the highest value achievable by an automaton -- its so-called top value. We improve QuAK by extending these two algorithms with an option to return, alongside their results, an ultimately periodic word witnessing the algorithm's output, as well as implementing a new safety-liveness decomposition algorithm that can handle nondeterministic automata, making QuAK more informative and capable.

cs.FL↗

arXiv2023

Monitoring Hyperproperties With Prefix Transducers

Hyperproperties are properties that relate multiple execution traces. Previous work on monitoring hyperproperties focused on synchronous hyperproperties, usually specified in HyperLTL. When monitoring synchronous hyperproperties, all traces are assumed to proceed at the same speed. We introduce (multi-trace) prefix transducers and show how to use them for monitoring synchronous as well as, for the first time, asynchronous hyperproperties. Prefix transducers map multiple input traces into one or more output traces, by incrementally matching prefixes of the input traces against expressions similar to regular expressions. The prefixes of different traces which are consumed by a single matching step of the monitor may have different lengths. The deterministic and executable nature of prefix transducers makes them more suitable as an intermediate formalism for runtime verification than logical specifications, which tend to be highly nondeterministic, especially in the case of asynchronous hyperproperties. We report on a set of experiments about monitoring asynchronous version of observational determinism.

cs.PL↗

arXiv2020

Fast Computation of Strong Control Dependencies

We introduce new algorithms for computing non-termination sensitive control dependence (NTSCD) and decisive order dependence (DOD). These relations on control flow graph vertices have many applications including program slicing and compiler optimizations. Our algorithms are asymptotically faster than the current algorithms. We also show that the original algorithms for computing NTSCD and DOD may produce incorrect results. We implemented the new as well as fixed versions of the original algorithms for the computation of NTSCD and DOD and we experimentally compare their performance and outcome. Our algorithms dramatically outperform the original ones.

cs.DS↗

arXiv2019

Data-centric Dynamic Partial Order Reduction

We present a new dynamic partial-order reduction method for stateless model checking of concurrent programs. A common approach for exploring program behaviors relies on enumerating the traces of the program, without storing the visited states (aka stateless exploration). As the number of distinct traces grows exponentially, dynamic partial-order reduction (DPOR) techniques have been successfully used to partition the space of traces into equivalence classes (Mazurkiewicz partitioning), with the goal of exploring only few representative traces from each class. We introduce a new equivalence on traces under sequential consistency semantics, which we call the observation equivalence. Two traces are observationally equivalent if every read event observes the same write event in both traces. While the traditional Mazurkiewicz equivalence is control-centric, our new definition is data-centric. We show that our observation equivalence is coarser than the Mazurkiewicz equivalence, and in many cases even exponentially coarser. We devise a DPOR exploration of the trace space, called data-centric DPOR, based on the observation equivalence. For acyclic architectures, our algorithm is guaranteed to explore exactly one representative trace from each observation class, while spending polynomial time per class. Hence, our algorithm is optimal wrt the observation equivalence, and in several cases explores exponentially fewer traces than any enumerative method based on the Mazurkiewicz equivalence. For cyclic architectures, we consider an equivalence between traces which is finer than the observation equivalence; but coarser than the Mazurkiewicz equivalence, and in some cases is exponentially coarser. Our data-centric DPOR algorithm remains optimal under this trace equivalence.

cs.PL↗

arXiv2018

SBT-instrumentation: A Tool for Configurable Instrumentation of LLVM Bitcode

The paper describes a member of the Symbiotic toolbox called sbt-instrumentation, which is a tool for configurable instrumentation of LLVM bitcode. The tool enables a user to specify patterns of instructions and to define functions whose calls will be inserted before or after instructions that match the patterns. Moreover, the tool offers additional functionality. First, the instrumentation can be divided into phases in order to pass information acquired in an earlier phase to the later phases. Second, it can utilize results of some external static analysis by connecting it as a plugin. The sbt-instrumentation tool has been developed as the part of Symbiotic responsible for inserting memory safety checks. However, its configurability opens the way to use it for many various purposes.

cs.SE↗