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Computing reachability probabilities is at the heart of probabilistic model checking. All model checkers compute these probabilities in an iterative fashion using value iteration. This technique approximates a fixed point from below by…

Logic in Computer Science · Computer Science 2018-04-16 Tim Quatmann , Joost-Pieter Katoen

Multi-objective probabilistic model checking is a powerful technique for verifying stochastic systems against multiple (potentially conflicting) properties. To enhance the trustworthiness and explainability of model checking tools, we…

Logic in Computer Science · Computer Science 2025-08-26 Christel Baier , Calvin Chau , Volodymyr Drobitko , Simon Jantsch , Sascha Klüppelholz

The weakest pre-expectation calculus has been proved to be a mature theory to analyze quantitative properties of probabilistic and nondeterministic programs. We present an automatic method for proving quantitative linear properties on any…

Logic in Computer Science · Computer Science 2010-06-29 Damián Barsotti , Nicolás Wolovick

Register pushdown automata (RPDA) is an extension of classical pushdown automata to handle data values in a restricted way. RPDA attracts attention as a model of a query language for structured documents with data values. The membership and…

Formal Languages and Automata Theory · Computer Science 2019-10-24 Ryoma Senda , Yoshiaki Takata , Hiroyuki Seki

Global polynomial optimization methods typically rely on compactness of the feasible region in order to find solutions. These methods can incur considerable computational expense and most commercially available solvers do not verify the…

Optimization and Control · Mathematics 2026-05-12 Rohan Rele , Angelia Nedich

Traditionally, robust statistics has focused on designing estimators tolerant to a minority of contaminated data. Robust list-decodable learning focuses on the more challenging regime where only a minority $\frac 1 k$ fraction of the…

Data Structures and Algorithms · Computer Science 2020-11-20 Ilias Diakonikolas , Daniel M. Kane , Daniel Kongsgaard , Jerry Li , Kevin Tian

Probabilistic programs encode stochastic models as ordinary-looking programs with primitives for sampling numbers from predefined distributions and conditioning. Their applications include, among many others, machine learning and modeling…

Formal Languages and Automata Theory · Computer Science 2025-12-16 Dominik Geißler , Tobias Winkler

This paper introduces Farkas certificates for lower and upper bounds on minimal and maximal reachability probabilities in Markov decision processes (MDP), which we derive using an MDP-variant of Farkas' Lemma. The set of all such…

Logic in Computer Science · Computer Science 2020-02-06 Florian Funke , Simon Jantsch , Christel Baier

This paper presents a probabilistic model validation methodology for nonlinear systems in time-domain. The proposed formulation is simple, intuitive, and accounts both deterministic and stochastic nonlinear systems with parametric and…

Systems and Control · Computer Science 2014-02-04 Abhishek Halder , Raktim Bhattacharya

We consider decision problems for deterministic pushdown automata over a unary alphabet (udpda, for short). Udpda are a simple computation model that accept exactly the unary regular languages, but can be exponentially more succinct than…

Formal Languages and Automata Theory · Computer Science 2014-03-04 Dmitry Chistikov , Rupak Majumdar

Methods to certify the robustness of neural networks in the presence of input uncertainty are vital in safety-critical settings. Most certification methods in the literature are designed for adversarial or worst-case inputs, but researchers…

Machine Learning · Computer Science 2023-01-26 Brendon G. Anderson , Somayeh Sojoudi

In this work, we consider the fundamental problem of deriving quantitative bounds on the probability that a given assertion is violated in a probabilistic program. We provide automated algorithms that obtain both lower and upper bounds on…

Programming Languages · Computer Science 2020-12-02 Jinyi Wang , Yican Sun , Hongfei Fu , Krishnendu Chatterjee , Amir Kafshdar Goharshady

Many quantitative properties of probabilistic programs can be characterized as least fixed points, but verifying their lower bounds remains a challenging problem. We present a new approach to lower-bound verification that exploits and…

Logic in Computer Science · Computer Science 2026-04-21 Satoshi Kura , Hiroshi Unno , Takeshi Tsukada

Property-Directed Reachability (PDR/IC3) is a standard workhorse for hardware safety verification, but most implementations are tuned primarily for time-to-answer and treat the produced invariant or counterexample as a secondary byproduct.…

Logic in Computer Science · Computer Science 2026-05-19 Arman Ferdowsi , Laura Kovacs

We propose a data-driven method to establish probabilistic performance guarantees for parametric optimization problems solved via iterative algorithms. Our approach addresses two key challenges: providing convergence guarantees to…

Optimization and Control · Mathematics 2025-10-31 Jingyi Huang , Paul Goulart , Kostas Margellos

Probabilistic timed automata (PTAs) are timed automata (TAs) extended with discrete probability distributions.They serve as a mathematical model for a wide range of applications that involve both stochastic and timed behaviours. In this…

Formal Languages and Automata Theory · Computer Science 2018-06-14 Hongfei Fu , Yi Li , Jianlin Li , Lijun Zhang

We introduce efficient algorithms for finding the $k$ shortest paths of a weighted pushdown automaton (WPDA), a compact representation of a weighted set of strings with potential applications in parsing and machine translation. Both of our…

Computation and Language · Computer Science 2013-02-06 Ke Wu , Philip Resnik

We study (bi)simulation-like preorder/equivalence checking on the class of visibly pushdown automata and its natural subclasses visibly BPA (Basic Process Algebra) and visibly one-counter automata. We describe generic methods for proving…

Computational Complexity · Computer Science 2015-07-01 Jiří Srba

We consider pushdown timed automata (PTAs) that are timed automata (with dense clocks) augmented with a pushdown stack. A configuration of a PTA includes a control state, dense clock values and a stack word. By using the pattern technique,…

Logic in Computer Science · Computer Science 2007-05-23 Zhe Dang

The strength or weakness of an algorithm is ultimately governed by the confidence of its result. When the domain of the problem is large (e.g. traversal of a high-dimensional space), a perfect solution cannot be obtained, so approximations…

Biomolecules · Quantitative Biology 2019-06-26 Nathan Clement