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The Concurrency Workbench is an automated tool for analyzing networks of finite-state processes expressed in Milner's Calculus of Communicating Systems. Its key feature is its breadth: a variety of different verification methods, including equivalence checking, preorder checking, and model checking, are supported for several different process semantics. One(More)
12a. DISTRIBUTION / AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE 13. ABSTRACT (Maximum 200 words) We introduce three models of probabilistic processes, namely, reactive, generative and stratified. These models are investigated within the context of PCCS, an extension of Milner's SCCS in which each summand of a process summation expression is guarded by a(More)
An implementation-oriented algorithm for <italic>lazy code motion</italic> is presented that minimizes the number of computations in programs while suppressing any unnecessary code motion in order to avoid superfluous register pressure. In particular, this variant of the original algorithm for lazy code motion works on flowgraphs whose nodes are basic(More)
In this paper, we present a constraint-oriented state-based proof methodology for concurrent software systems which exploits compositionality and abstraction for the reduction of the veriication problem under investigation. Formal basis for this methodology are Modal Transition Systems allowing loose state-based speciications, which can be reened by(More)
We develop a model-checking algorithm for a logic that permits propositions to be deened using greatest and least xed points of mutually recursive systems of equations. This logic is as expressive as the alternation-free fragment of the modal mu-calculus identiied by Emerson and Lei, and it may therefore be used to encode a number of temporal logics and(More)
In this paper we present the LearnLib, a library for automata learning and experimentation. Its modular structure allows users to configure their tailored learning scenarios, which exploit specific properties of the envisioned applications. As has been shown earlier, exploiting application-specific structural features enables optimizations that may lead to(More)
In this paper, we present the LearnLib, a library of tools for automata learning, which is explicitly designed for the systematic experimental analysis of the profile of available learning algorithms and corresponding optimizations. Its modular structure allows users to configure their own tailored learning scenarios, which exploit specific properties of(More)