Demo Data from SIGIR 2026 / reviewers in the wild / expert
Markus Siegle
dblp:99/126
· DBLP profile ↗
16ranked-venue papers
1as first author
1since 2021 · last 2025
0000-0001-7639-2280ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 7 · 1 first-author · 1 since 2021Software engineering, systems software and programming languages · 6 · 1 first-authorTheory of computation · 4Security and privacy · 2Applied, interdisciplinary, general and emerging computing · 2
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
2 papers |
Logic in computer science · 44% Automata and formal languages · 32% Automated reasoning and model checking · 24% | |
| Computer architecture, parallel and distributed computing, and storage systems
3 papers |
Performance modeling and evaluation · 85% Embedded and real-time systems · 12% High-performance computing · 4% |
Topics — the 10 heaviest of 11, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Automata and formal languages › probabilistic automata
markov automata |
0.2 | 1 | 2014 | Markov Automata: Deciding weak bisimulation by means of non-naïvely vanishing states · Inf. Comput. 2014 |
Logic in computer science › bisimulation
weak bisimulation |
0.2 | 1 | 2014 | Markov Automata: Deciding weak bisimulation by means of non-naïvely vanishing states · Inf. Comput. 2014 |
Automated reasoning and model checking › model checking › probabilistic model checking
markov chain model checking |
0.1 | 1 | 2007 | Model Checking Markov Chains with Actions and State Labels · IEEE Trans. Software Eng. 2007 |
Automated reasoning and model checking › model checking
probabilistic model checking |
0.1 | 1 | 2007 | Model Checking Markov Chains with Actions and State Labels · IEEE Trans. Software Eng. 2007 |
Logic in computer science
temporal logic |
0.1 | 1 | 2007 | Model Checking Markov Chains with Actions and State Labels · IEEE Trans. Software Eng. 2007 |
Performance modeling and evaluation
performance monitoring |
0.0 | 1 | 1994 | Distributed Performance Monitoring: Methods, Tools, and Applications · IEEE Trans. Parallel Distributed Syst. 1994 |
Performance modeling and evaluation › performance monitoring
parallel program monitoring |
0.0 | 1 | 1992 | Monitoring Program Behaviour on SUPRENUM · ISCA 1992 |
Embedded and real-time systems
runtime monitoring |
0.0 | 1 | 1992 | Monitoring Program Behaviour on SUPRENUM · ISCA 1992 |
Debugging and program repair
performance debugging |
0.0 | 1 | 1994 | Distributed Performance Monitoring: Methods, Tools, and Applications · IEEE Trans. Parallel Distributed Syst. 1994 |
High-performance computing › system monitoring
multiprocessor monitoring |
0.0 | 1 | 1992 | Monitoring Program Behaviour on SUPRENUM · ISCA 1992 |
Methods — techniques the papers use, named apart from their topics
reduction to CSL model checking · 0.1automaton-based product construction · 0.1trace analysis · 0.0markov chain · 0.0hybrid monitoring · 0.0profiling · 0.0event tracing · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Formal error bounds for the state space reduction of Markov chains
Fabian Michel, Markus Siegle |
Perform. Evaluation | 2 |
| 2019 | Markov chains with perturbed rates to absorption: Theory and application to model repair
Alexander Gouberman, Markus Siegle, Bharath Siva Kumar Tati |
Perform. Evaluation | 2 |
| 2014 | Markov Automata: Deciding weak bisimulation by means of non-naïvely vanishing states
Johann Schuster, Markus Siegle |
Inf. Comput. | 2 |
| 2010 | Partially-shared zero-suppressed multi-terminal BDDs: concept, algorithms and applications
Kai Lampka, Markus Siegle, Jörn Ossowski, Christel Baier |
Formal Methods Syst. Des. | 2 |
| 2009 | An Efficient Symbolic Elimination Algorithm for the Stochastic Process Algebra Tool CASPA
Jens Bachmann, Martin Riedl 0001, Johann Schuster, Markus Siegle |
SOFSEM | 4 |
| 2007 | Model Checking Markov Chains with Actions and State LabelsabstractIn the past, logics of several kinds have been proposed for reasoning about discrete-time or continuous-time Markov chains. Most of these logics rely on either state labels (atomic propositions) or on transition labels (actions). However, in several applications it is useful to reason about both state properties and action sequences. For this purpose, we introduce the logic as CSL which provides a powerful means to characterize execution paths of Markov chains with actions and state labels. asCSL can be regarded as an extension of the purely state-based logic CSL (continuous stochastic logic). In asCSL, path properties are characterized by regular expressions over actions and state formulas. Thus, the truth value of path formulas depends not only on the available actions in a given time interval, but also on the validity of certain state formulas in intermediate states. We compare the expressive power of CSL and asCSL and show that even the state-based fragment of asCSL is strictly more expressive than CSL if time intervals starting at zero are employed. Using an automaton-based technique, an asCSL formula and a Markov chain with actions and state labels are combined into a product Markov chain. For time intervals starting at zero, we establish a reduction of the model checking problem for asCSL to CSL model checking on this product Markov chain. The usefulness of our approach is illustrated with an elaborate model of a scalable cellular communication system, for which several properties are formalized by means of asCSL formulas and checked using the new procedure Christel Baier, Lucia Cloth, Boudewijn R. Haverkort, Matthias Kuntz, Markus Siegle |
IEEE Trans. Software Eng. | 5 |
| 2004 | Model Checking Action- and State-Labelled Markov ChainsabstractIn this paper we introduce the logic asCSL, an extension of continuous stochastic logic (CSL), which provides powerful means to characterise execution paths of action- and state-labelled Markov chains. In asCSL, path properties are characterised by regular expressions over actions and state-formulas. Thus, the executability of a path not only depends on the available actions but also on the validity of certain state formulas in intermediate states. Our main result is that the model checking problem for asCSL can be reduced to CSL model checking on a modified Markov chain, which is obtained through a product automaton construction. We provide a case study of a scalable cellular phone system which shows how the logic asCSL and the model checking procedure can be applied in practice. Christel Baier, Lucia Cloth, Boudewijn R. Haverkort, Matthias Kuntz, Markus Siegle |
DSN | 5 |
| 2003 | ETMCC: Model Checking Performability Properties of Markov Chainsabstractanalysis and/or numerical engine. The Analysis engine supports standard model checking algorithms for CTL-style until-formulas, as well as graph algorithms, for instance to compute the bottom strongly connected components of a Markov chain. The former algorithms are used in a pre-processing phase during the checking of probabilistic until-formulas while the latter is needed when calculating steady state properties. The Numerical engine provides several methods for the numerical analysis of the CTMC such as linear solvers, methods for numerical integration and uniformisation. These are used to solve sytems of linear or integral equations. The State space manager represents the model in sparse matrix format. It maintains information about the validity of atomic propositions and of sub-formulas for each state. Status and Availability ETMCC has been used successfully in several non-trivial case studies, e.g. a cyclic server polling system and a multiprocessor mainframe with software failures. Its efficient numerical analysis methods enable users to check performability properties for models of up to several millions of states. The tool is available free of charge for academia, see http://www7.informatik.uni-erlangen.de/etmcc/ ,t he current download being version 1.4. A detailed description of ETMCC can be found in [4]. Holger Hermanns, Joost-Pieter Katoen, Joachim Meyer-Kayser, Markus Siegle |
DSN | 4 |
| 2003 | A tool for model-checking Markov chains
Holger Hermanns, Joost-Pieter Katoen, Joachim Meyer-Kayser, Markus Siegle |
Int. J. Softw. Tools Technol. Transf. | 4 |
| 2000 | Towards Model Checking Stochastic Process Algebra
Holger Hermanns, Joost-Pieter Katoen, Joachim Meyer-Kayser, Markus Siegle |
IFM | 4 |
| 2000 | A Markov Chain Model Checker
Holger Hermanns, Joost-Pieter Katoen, Joachim Meyer-Kayser, Markus Siegle |
TACAS | 4 |
| 2000 | Compositional performance modelling with the TIPPtool
Holger Hermanns, Ulrich Herzog, Ulrich Klehmet, Vassilis Mertsiotakis, Markus Siegle |
Perform. Evaluation | 5 |
| 1999 | TIPPtool: Compositional Specification and Analysis of Markovian Performance Models
Holger Hermanns, Vassilis Mertsiotakis, Markus Siegle |
CAV | 3 |
| 1996 | Combining gprof and event-driven monitoring for analyzing distributed programs: a rough view of NCSA mosaic
Chenglian Peng, Rainer Klar, Richard Hofmann, Peter Dauphin, Markus Siegle |
J. Comput. Sci. Technol. | 5 |
| 1994 | Distributed Performance Monitoring: Methods, Tools, and ApplicationsabstractA method for analyzing the functional behavior and the performance of programs in distributed systems is presented. We use hybrid monitoring, a technique which combines advantages of both software monitoring and hardware monitoring. The paper contains a description of a hardware monitor and a software package (ZM4/SIMPLE) which make our concepts available to programmers, assisting them in debugging and tuning of their code. A short survey of related monitor systems highlights the distinguishing features of our implementation. As an application of our monitoring and evaluation system, the analysis of a parallel ray tracing program running on the SUPRENUM multiprocessor is described. It is shown that monitoring and modeling both rely on a common abstraction of a system's dynamic behavior and therefore can be integrated to one comprehensive methodology. This methodology is supported by a set of tools.> Richard Hofmann, Rainer Klar, Bernd Mohr, Andreas Quick, Markus Siegle |
IEEE Trans. Parallel Distributed Syst. | 5 |
| 1992 | Monitoring Program Behaviour on SUPRENUMabstractIt is often very difficult for programmers of parallel computers to understand how their parallel programs behave at execution time, because there is not enough insight into the interactions between concurrent activities in the parallel machine. Programmers do not only wish to obtain statistical information that can be supplied by profiling, for example. They need to have detailed knowledge about the functional behaviour of their programs. Considering performance aspects, they need timing information as well. Monitoring is a technique well suited to obtain information about both functional behaviour and timing. Global time information is essential for determining the chronological order of events on different nodes of a multiprocessor or of a distributed system, and for determining the duration of time intervals between events from different nodes. A major problem on multiprocessors is the absence of a global clock with high resolution. This problem can be overcome if a monitor system capable of supplying globally valid time stamps is used. Markus Siegle, Richard Hofmann |
ISCA | 1 |