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Algebraic Process Verification
 Handbook of Process Algebra, chapter 17
"... This chapter addresses the question how to verify distributed and communicating systems in an e#ective way from an explicit process algebraic standpoint. This means that all calculations are based on the axioms and principles of the process algebras. ..."
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Cited by 62 (16 self)
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This chapter addresses the question how to verify distributed and communicating systems in an e#ective way from an explicit process algebraic standpoint. This means that all calculations are based on the axioms and principles of the process algebras.
µCRL: A toolset for analysing algebraic specifications
 Proc. 13th Conference on Computer Aided Verification, LNCS 2102
, 2001
"... µCRL [13] is a language for specifying and verifying distributed systems in an algebraic fashion. It targets the specification of system behaviour in a processalgebraic style and of data elements in the form of abstract data types. The µCRL toolset [21] (see ..."
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Cited by 35 (17 self)
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µCRL [13] is a language for specifying and verifying distributed systems in an algebraic fashion. It targets the specification of system behaviour in a processalgebraic style and of data elements in the form of abstract data types. The µCRL toolset [21] (see
Verification of Temporal Properties of Processes in a Setting with Data
 In A.M. Haeberer, editor, AMAST’98, volume 1548 of LNCS
, 1999
"... . We define a valuebased modal calculus, built from firstorder formulas, modalities, and fixed point operators parameterized by data variables, which allows to express temporal properties involving data. We interpret this logic over Crl terms defined by linear process equations. The satisfacti ..."
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Cited by 24 (8 self)
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. We define a valuebased modal calculus, built from firstorder formulas, modalities, and fixed point operators parameterized by data variables, which allows to express temporal properties involving data. We interpret this logic over Crl terms defined by linear process equations. The satisfaction of a temporal formula by a Crl term is translated to the satisfaction of a firstorder formula containing parameterized fixed point operators. We provide proof rules for these fixed point operators and show their applicability on various examples. 1 Introduction In recent years we have applied process algebra in numerous settings [4, 8, 12]. The first lesson we learned is that process algebra pur sang is not very handy, and we need an extension with data. This led to the language Crl (micro Common Representation Language) [13]. The next observation was that it is very convenient to eliminate the parallel operator from a process description and reduce it to a very restricted form, whi...
A timed verification of the IEEE 1394 leader election protocol
 FORMAL METHODS IN SYSTEM DESIGN
, 2001
"... ..."
Normed Simulations
 In Proceedings CAV'98
, 1998
"... . In existing simulation proof techniques, a single step in a lowlevel system may be simulated by an extended execution fragment in a highlevel system. As a result, it is undecidable whether a given relation is a simulation, even if tautology checking is decidable for the underlying specification l ..."
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Cited by 13 (1 self)
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. In existing simulation proof techniques, a single step in a lowlevel system may be simulated by an extended execution fragment in a highlevel system. As a result, it is undecidable whether a given relation is a simulation, even if tautology checking is decidable for the underlying specification logic. This paper introduces various types of normed simulations. In a normed simulation, each step in a lowlevel system can be simulated by at most one step in the high level system, for any related pair of states. We show that it is decidable whether a given relation is a normed simulation relation, given that tautology checking is decidable. We also prove that, at the semantic level, normed simulations form a complete proof method for establishing behavior inclusion, provided that the highlevel system has finite invisible nondeterminism. As an illustration of our method we discuss the verification in PVS of a leader election algorithm that is used within the IEEE 1394 protocol. 1 Introdu...
Cones and Foci for Protocol Verification Revisited
 In Proc. 6th Conference on Foundations of Software Science and Computation Structures, LNCS 2620
, 2003
"... Abstract. We define a cones and foci proof method, which rephrases the question whether two system specifications are branching bisimilar in terms of proof obligations on relations between data objects. Compared to the original cones and foci method from Groote and Springintveld [22], our method is ..."
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Cited by 9 (4 self)
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Abstract. We define a cones and foci proof method, which rephrases the question whether two system specifications are branching bisimilar in terms of proof obligations on relations between data objects. Compared to the original cones and foci method from Groote and Springintveld [22], our method is more generally applicable, and does not require a preprocessing step to eliminate τloops. We prove soundness of our approach and give an application. 1
The cones and foci proof technique for timed transition systems
 Information Processing Letters
"... ..."
Linearization of µCRL Specifications (Extended Abstract)
"... ... µCRL resemble symbolic representations of transition systems, that can be further transformed and analyzed by many of the existing toolsand techniques. We aim at proving the correctness of this linearization algorithm. To this end we use an equivalence relation on recursive specifications in µCR ..."
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Cited by 5 (0 self)
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... µCRL resemble symbolic representations of transition systems, that can be further transformed and analyzed by many of the existing toolsand techniques. We aim at proving the correctness of this linearization algorithm. To this end we use an equivalence relation on recursive specifications in µCRL that is model independent and does not involve an explicit notion of solution.
Algebraic Verification of a Distributed Summation Algorithm
, 1996
"... In this note we present an algebraic verification of Segall's Propagation of Information with Feedback (PIF) algorithm. This algorithm serves as a nice benchmark for verification exercises (see [2, 13, 8]). The verification is based on the methodology presented in [7] and demonstrates its ap ..."
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In this note we present an algebraic verification of Segall's Propagation of Information with Feedback (PIF) algorithm. This algorithm serves as a nice benchmark for verification exercises (see [2, 13, 8]). The verification is based on the methodology presented in [7] and demonstrates its applicability to distributed algorithms.