188 research outputs found
ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΠΎ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΌΠΈΠΊΡΠΎΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΉ Π²ΠΈΡΠΌΡΡΠ° Π² ΠΎΠ»ΠΎΠ²Π΅ Π²ΡΡΠΎΠΊΠΎΠΉ ΡΠΈΡΡΠΎΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ Π°ΠΌΠ°Π»ΡΠ³Π°ΠΌΠ½ΠΎΠΉ ΠΏΠΎΠ»ΡΡΠΎΠ³ΡΠ°ΡΠΈΠΈ Ρ Π½Π°ΠΊΠΎΠΏΠ»Π΅Π½ΠΈΠ΅ΠΌ
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ΠΡΠΎΡΠΈΠ»Ρ ΡΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π±Π΅Π΄Π½ΠΎΡΡΠΈ: ΡΠ°ΠΊΡΠΎΡΡ ΠΈ ΡΠΈΡΠΊΠΈ Π΄Π»Ρ ΡΠ°Π±ΠΎΡΠ°ΡΡΠ΅Π³ΠΎ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ
ΠΡΡΠ²Π»Π΅Π½Ρ ΡΠ°ΠΊΡΠΎΡΡ ΠΈ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΡΡΠΈΠ΅ ΠΈΠΌ ΡΠΈΡΠΊΠΈ Π²ΠΎΠ·Π½ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΡ Π±Π΅Π΄Π½ΠΎΡΡΠΈ ΡΡΠ΅Π΄ΠΈ ΡΠ°Π±ΠΎΡΠ°ΡΡΠ΅Π³ΠΎ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ Π ΠΎΡΡΠΈΠΈ. ΠΠΎΠΊΠ°Π·ΡΠ²Π°Π΅ΡΡΡ, ΡΡΠΎ ΠΏΡΠΈΡΠΈΠ½Ρ Π²ΠΎΠ·Π½ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΡ Π±Π΅Π΄Π½ΠΎΡΡΠΈ Π»Π΅ΠΆΠ°Ρ Π² ΠΏΠ»ΠΎΡΠΊΠΎΡΡΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΡΡΠ°Π½Ρ: ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠ΅ΠΉ ΠΏΡΠΎΡ
ΠΎΠΆΠ΄Π΅Π½ΠΈΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠΈΠΊΠ»ΠΎΠ² Π½Π° Π²ΠΎΠ»Π½Π΅ ΡΠΏΠ°Π΄Π° ΠΈ ΠΊΡΠΈΠ·ΠΈΡΠ°, ΠΊΠ°ΡΠ΅ΡΡΠ²Π° ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠΎΡΡΠ° Π½Π° Π²ΠΎΠ»Π½Π΅ ΠΏΠΎΠ΄ΡΠ΅ΠΌΠ°. ΠΡΡΠ°Π±ΠΎΡΠ°Π½Ρ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΡΡΠ°ΡΠ΅Π³ΠΈΠΈ ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠΎΡΡΠ° ΡΡΡΠ°Π½Ρ Π΄Π»Ρ ΠΏΡΠ΅ΠΎΠ΄ΠΎΠ»Π΅Π½ΠΈΡ Π±Π΅Π΄Π½ΠΎΡΡΠΈ ΡΠ°Π±ΠΎΡΠ°ΡΡΠ΅Π³ΠΎ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ
High-level Counterexamples for Probabilistic Automata
Providing compact and understandable counterexamples for violated system
properties is an essential task in model checking. Existing works on
counterexamples for probabilistic systems so far computed either a large set of
system runs or a subset of the system's states, both of which are of limited
use in manual debugging. Many probabilistic systems are described in a guarded
command language like the one used by the popular model checker PRISM. In this
paper we describe how a smallest possible subset of the commands can be
identified which together make the system erroneous. We additionally show how
the selected commands can be further simplified to obtain a well-understandable
counterexample
ΠΡΡΡΠ΅ΡΡΠ²Π»Π΅Π½ΠΈΠ΅ ΡΠ²ΡΠ·ΠΈ Π²ΡΠ·ΠΎΠ²ΡΠΊΠΎΠΉ Π½Π°ΡΠΊΠΈ Π‘ΠΈΠ±ΠΈΡΠΈ Ρ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²ΠΎΠΌ ΠΈ ΠΈΠ½Π½ΠΎΠ²Π°ΡΠΈΠΎΠ½Π½ΡΡ ΠΌΠ΅ΡΠΎΠΏΡΠΈΡΡΠΈΠΉ Π² 70-80-Π΅ Π³Π³. Π₯Π₯ Π².
ΠΡΡΠ°ΠΆΠ°ΡΡΡΡ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ, ΠΊΠ°ΡΠ°ΡΡΠΈΠ΅ΡΡ ΠΈΠ½ΡΠ΅Π³ΡΠ°ΡΠΈΠΈ Π²ΡΠ·ΠΎΠ²ΡΠΊΠΎΠΉ Π½Π°ΡΠΊΠΈ Π‘ΠΈΠ±ΠΈΡΠΈ Ρ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²ΠΎΠΌ Π² 70-80-Π΅ Π³Π³. Π₯Π₯ Π². ΠΠ½Π°Π»ΠΈΠ·ΠΈΡΡΠ΅ΡΡΡ Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΡ ΠΈΠ½ΡΡΠΈΡΡΡΠΎΠ² ΠΈ ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠΎΠ² ΡΠ΅Π³ΠΈΠΎΠ½Π° ΠΏΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΈ ΡΠΊΡΠ΅ΠΏΠ»Π΅Π½ΠΈΡ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠΎΡΠΌ ΡΠΎΠ΄ΡΡΠΆΠ΅ΡΡΠ²Π° Π½Π°ΡΠΊΠΈ Ρ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²ΠΎΠΌ: Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΡΡ
Π΄ΠΎΠ³ΠΎΠ²ΠΎΡΠΎΠ², ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΡΡ
ΡΠ²ΠΎΡΡΠ΅ΡΠΊΠΈΡ
Π±ΡΠΈΠ³Π°Π΄, ΡΠ΅ΡΡΡΠ²Π° ΡΡΠ΅Π½ΡΡ
ΠΈ ΠΈΠ½ΠΆΠ΅Π½Π΅ΡΠΎΠ² Π½Π°Π΄ ΡΠ°Π±ΠΎΡΠΈΠΌΠΈ, ΡΡΠ°ΡΡΠΈΡ Π½Π°ΡΡΠ½ΠΎ-ΠΏΠ΅Π΄Π°Π³ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊΠΎΠ² Π² ΠΊΠΎΠ½ΡΡΠ»ΡΡΠ°ΡΠΈΡΡ
Π½Π° ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΡΡ
ΠΈ Π½Π°ΡΡΠ½ΠΎ-ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΡΠΎΠΏΠ°Π³Π°Π½Π΄Π΅
Extending Neural Network Verification to a Larger Family of Piece-wise Linear Activation Functions
In this paper, we extend an available neural network verification technique
to support a wider class of piece-wise linear activation functions.
Furthermore, we extend the algorithms, which provide in their original form
exact respectively over-approximative results for bounded input sets
represented as start sets, to allow also unbounded input set. We implemented
our algorithms and demonstrated their effectiveness in some case studies.Comment: In Proceedings FMAS 2023, arXiv:2311.0898
An open structural operational semantics for an object-oriented calculus with thread classes
In this report we present a multithreaded class-calculus featuring \emph{thread classes.} From an observational point of view, considering classes as part of a component makes instantiation a possible interaction between component and environment or observer. For thread classes it means that a component may create external activity, which influences what can be observed. The fact that cross-border instantiation is possible requires that the \emph{connectivity} of the objects needs to be incorporated into the semantics. We extend our prior work not only by adding thread classes, but also in that thread names may be \emph{communicated,} which means that the semantics needs explicitly account for the possible acquaintance of objects with threads. This report formalizes a calculus featuring thread classes, i.e., its syntax, type system, and operational semantics. We furthermore discuss observational aspects of thread classes
Comparing Two Approaches to Include Stochasticity in Hybrid Automata
Different stochastic extensions of hybrid automata have been proposed in the
past, with unclear expressivity relations between them. To structure and relate
these modeling languages, in this paper we formalize two alternative approaches
to extend hybrid automata with stochastic choices of discrete events and their
time points. The first approach, which we call decomposed scheduling, adds
stochasticity via stochastic races, choosing random time points for the
possible discrete events and executing a winner with an earliest time. In
contrast, composed scheduling first samples the time point of the next event
and then the event to be executed at the sampled time point. We relate the two
approaches regarding their expressivity and categorize available stochastic
extensions of hybrid automata from the literature.Comment: This paper is accepted for publication (without appendix) in the
Proceedings of the 2023 International Conference on Quantitative Evaluation
of Systems (QEST). The appendix was part of the submission and provides
additional material which is not included in the QEST publicatio
Accelerating Parametric Probabilistic Verification
We present a novel method for computing reachability probabilities of
parametric discrete-time Markov chains whose transition probabilities are
fractions of polynomials over a set of parameters. Our algorithm is based on
two key ingredients: a graph decomposition into strongly connected subgraphs
combined with a novel factorization strategy for polynomials. Experimental
evaluations show that these approaches can lead to a speed-up of up to several
orders of magnitude in comparison to existing approache
FMplex: A Novel Method for Solving Linear Real Arithmetic Problems
In this paper we introduce a novel quantifier elimination method for
conjunctions of linear real arithmetic constraints. Our algorithm is based on
the Fourier-Motzkin variable elimination procedure, but by case splitting we
are able to reduce the worst-case complexity from doubly to singly exponential.
The adaption of the procedure for SMT solving has strong correspondence to the
simplex algorithm, therefore we name it FMplex. Besides the theoretical
foundations, we provide an experimental evaluation in the context of SMT
solving
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