24 citations · 32 across the 16 of their papers we have counts for
19 papers
Implicit Computation of Filtered Prime Implicants
Edward Liem, Clemens Dubslaff
Prime implicants (PIs) are central in computer science, with applications in logic minimization, diagnosis, explainable formal methods and AI. Algorithms for the computation of PIs…
Property-driven Causal Abstractions for Markov Decision Processes
Jule Schmidt, Maximilian Weininger, Clemens Dubslaff +2
Markov Decision Processes (MDPs) are widely used as decision-making models, commonly specified over factored state spaces through state variables and their valuations. The exponent…
Explaining Control Policies through Predicate Decision Diagrams
Debraj Chakraborty, Clemens Dubslaff, Sudeep Kanav +2
Safety-critical controllers of complex systems are hard to construct manually. Automated approaches such as controller synthesis or learning provide a tempting alternative but usua…
Configuration Monitor Synthesis
Maximilian A. Köhl, Clemens Dubslaff, Holger Hermanns
The observable behavior of a system usually carries useful information about its internal state, properties, and potential future behaviors. In this paper, we introduce configurati…
Proceedings of the First Workshop on Trends in Configurable Systems Analysis
Maurice H. ter Beek, Clemens Dubslaff
The analysis of configurable systems, i.e., systems those behaviors depend on parameters or support various features, is challenging due to the exponential blowup arising in the nu…
A Unifying Formal Approach to Importance Values in Boolean Functions
Hans Harder, Simon Jantsch, Christel Baier +1
Boolean functions and their representation through logics, circuits, machine learning classifiers, or binary decision diagrams (BDDs) play a central role in the design and analysis…
More for Less: Safe Policy Improvement With Stronger Performance Guarantees
Patrick Wienhöft, Marnix Suilen, Thiago D. Simão +3
In an offline reinforcement learning setting, the safe policy improvement (SPI) problem aims to improve the performance of a behavior policy according to which sample data has been…
Strategy Synthesis in Markov Decision Processes Under Limited Sampling Access
Christel Baier, Clemens Dubslaff, Patrick Wienhöft +1
A central task in control theory, artificial intelligence, and formal methods is to synthesize reward-maximizing strategies for agents that operate in partially unknown environment…
On the Foundations of Cycles in Bayesian Networks
Christel Baier, Clemens Dubslaff, Holger Hermanns +1
Bayesian networks (BNs) are a probabilistic graphical model widely used for representing expert knowledge and reasoning under uncertainty. Traditionally, they are based on directed…
Proceedings Fifth Workshop on Models for Formal Analysis of Real Systems
Clemens Dubslaff, Bas Luttik
This volume contains the proceedings of MARS 2022, the fifth workshop on Models for Formal Analysis of Real Systems, held as part of ETAPS 2022, the European Joint Conferences on T…
Causality in Configurable Software Systems
Clemens Dubslaff, Kallistos Weis, Christel Baier +1
Detecting and understanding reasons for defects and inadvertent behavior in software is challenging due to their increasing complexity. In configurable software systems, the combin…
From Verification to Causality-based Explications
Christel Baier, Clemens Dubslaff, Florian Funke +4
In view of the growing complexity of modern software architectures, formal models are increasingly used to understand why a system works the way it does, opposed to simply verifyin…
Iterative Variable Reordering: Taming Huge System Families
Clemens Dubslaff, Andrey Morozov, Christel Baier +1
For the verification of systems using model-checking techniques, symbolic representations based on binary decision diagrams (BDDs) often help to tackle the well-known state-space e…
Reduction Methods on Probabilistic Control-flow Programs for Reliability Analysis
Clemens Dubslaff, Andrey Morozov, Christel Baier +1
Modern safety-critical systems are heterogeneous, complex, and highly dynamic. They require reliability evaluation methods that go beyond the classical static methods such as fault…
Breaking the Limits of Redundancy Systems Analysis
Clemens Dubslaff, Kai Ding, Andrey Morozov +2
Redundancy mechanisms such as triple modular redundancy protect safety-critical components by replication and thus improve systems fault tolerance. However, the gained fault tolera…
Stochastic Shortest Paths and Weight-Bounded Properties in Markov Decision Processes
Christel Baier, Nathalie Bertrand, Clemens Dubslaff +2
The paper deals with finite-state Markov decision processes (MDPs) with integer weights assigned to each state-action pair. New algorithms are presented to classify end components…
Synthesis of Optimal Resilient Control Strategies
Christel Baier, Clemens Dubslaff, Ľuboš Korenčiak +1
Repair mechanisms are important within resilient systems to maintain the system in an operational state after an error occurred. Usually, constraints on the repair mechanisms are i…
Mean-Payoff Optimization in Continuous-Time Markov Chains with Parametric Alarms
Christel Baier, Clemens Dubslaff, Ľuboš Korenčiak +2
Continuous-time Markov chains with alarms (ACTMCs) allow for alarm events that can be non-exponentially distributed. Within parametric ACTMCs, the parameters of alarm-event distrib…
Probabilistic Model Checking for Energy Analysis in Software Product Lines
Clemens Dubslaff, Sascha Klüppelholz, Christel Baier
In a software product line (SPL), a collection of software products is defined by their commonalities in terms of features rather than explicitly specifying all products one-by-one…