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On induction vs. *continuity
 Proc. Workshop on Logics of Programs 1981, SpringVerlag Lect. Notes in Comput
, 1981
"... Abstract. In this paper we study the relative expressibility of the infinitary *continuity condition (*cant) <a*>X ~ V n <an>x and the equational but weaker induction axiom Ond) X ^ [a*](X =[alX) [a*]X in Propositional Dynamic Logic. We show: (1) under ind only, there is a firstord ..."
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Abstract. In this paper we study the relative expressibility of the infinitary *continuity condition (*cant) <a*>X ~ V n <an>x and the equational but weaker induction axiom Ond) X ^ [a*](X =[alX) [a*]X in Propositional Dynamic Logic. We show: (1) under ind only, there is a firstorder sentence distinguishing separable dynamic algebras from standard Kripke models; whereas (2) under the stronger axiom *cant, the class of separable dynamic algebras and the class of standard Kripke models are indistinguishable by any sentence of infinitary firstorder logic. I.
Rewriting Extended Regular Expressions
, 1993
"... We concider an extened algebra of regular events (languages) with intersection besides the usual operations. This algebra has the structure of a distributive lattice with monotonic operations; the latter property is crucial for some applications. We give a new complete Horn equational axiomatiztion ..."
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We concider an extened algebra of regular events (languages) with intersection besides the usual operations. This algebra has the structure of a distributive lattice with monotonic operations; the latter property is crucial for some applications. We give a new complete Horn equational axiomatiztion of the algebra and develop some termrewriting techniques for constructing logical inferences of valid equations. A shorter version of this paper is to appear in the proceedings of Developments in Language Theory, Univ. of Turku, July 1993, published by World Scientific. The present version has been submitted for publication elsewhere. 1 Introduction In this paper we consider an extended algebra of regular events (languages) on a given alphabet with intersection besides the usual operations (union, concatenation, Kleene star, empty, and the regular unit). This algebra has the structure of a distributive lattice (join is union, meet is intersection) with only monotonic operations. The latte...
Dynamic Algebras: Examples, Constructions, Applications
 Studia Logica
, 1991
"... Dynamic algebras combine the classes of Boolean (B 0 0) and regular (R [ ; ) algebras into a single finitely axiomatized variety (B R 3) resembling an Rmodule with "scalar" multiplication 3. The basic result is that is reflexive transitive closure, contrary to the intuition tha ..."
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Cited by 19 (1 self)
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Dynamic algebras combine the classes of Boolean (B 0 0) and regular (R [ ; ) algebras into a single finitely axiomatized variety (B R 3) resembling an Rmodule with "scalar" multiplication 3. The basic result is that is reflexive transitive closure, contrary to the intuition that this concept should require quantifiers for its definition. Using this result we give several examples of dynamic algebras arising naturally in connection with additive functions, binary relations, state trajectories, languages, and flowcharts. The main result is that free dynamic algebras are residually finite (i.e. factor as a subdirect product of finite dynamic algebras), important because finite separable dynamic algebras are isomorphic to Kripke structures. Applications include a new completeness proof for the Segerberg axiomatization of propositional dynamic logic, and yet another notion of regular algebra. Key words: Dynamic algebra, logic, program verification, regular algebra. This paper or...
Equational axioms for probabilistic bisimilarity
 IN PROCEEDINGS OF 9TH AMAST, LECTURE NOTES IN COMPUTER SCIENCE
, 2002
"... This paper gives an equational axiomatization of probabilistic bisimulation equivalence for a class of finitestate agents previously studied by Stark and Smolka ((2000) Proof, Language, and Interaction: Essays in Honour of Robin Milner, pp. 571595). The axiomatization is obtained by extending ..."
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This paper gives an equational axiomatization of probabilistic bisimulation equivalence for a class of finitestate agents previously studied by Stark and Smolka ((2000) Proof, Language, and Interaction: Essays in Honour of Robin Milner, pp. 571595). The axiomatization is obtained by extending the general axioms of iteration theories (or iteration algebras), which characterize the equational properties of the fixed point operator on (#)continuous or monotonic functions, with three axiom schemas that express laws that are specific to probabilistic bisimilarity.
Simplifying XML Schema: Effortless Handling of Nondeterministic Regular Expressions
, 2009
"... Whether beloved or despised, XML Schema is momentarily the only industrially accepted schema language for XML and is unlikely to become obsolete any time soon. Nevertheless, many nontransparent restrictions unnecessarily complicate the design of XSDs. For instance, complex content models in XML Sche ..."
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Cited by 17 (11 self)
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Whether beloved or despised, XML Schema is momentarily the only industrially accepted schema language for XML and is unlikely to become obsolete any time soon. Nevertheless, many nontransparent restrictions unnecessarily complicate the design of XSDs. For instance, complex content models in XML Schema are constrained by the infamous unique particle attribution (UPA) constraint. In formal language theoretic terms, this constraint restricts content models to deterministic regular expressions. As the latter constitute a semantic notion and no simple corresponding syntactical characterization is known, it is very difficult for nonexpert users to understand exactly when and why content models do or do not violate UPA. In the present paper, we therefore investigate solutions to relieve users from the burden of UPA by automatically transforming nondeterministic expressions into concise deterministic ones defining the same language or constituting good approximations. The presented techniques facilitate XSD construction by reducing the design task at hand more towards the complexity of the modeling task. In addition, our algorithms can serve as a plugin for
Bisimulation is not Finitely (First Order) Equationally Axiomatisable
 in Proceedings 9 th Annual Symposium on Logic in Computer Science
, 1994
"... This paper considers the existence of finite equational axiomatisations of bisimulation over a calculus of finite state processes. To express even simple properties such as ¯XE = ¯XE[E=X] equationally it is necessary to use some notation for substitutions. Accordingly the calculus is embedded in a s ..."
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This paper considers the existence of finite equational axiomatisations of bisimulation over a calculus of finite state processes. To express even simple properties such as ¯XE = ¯XE[E=X] equationally it is necessary to use some notation for substitutions. Accordingly the calculus is embedded in a simply typed lambda calculus, allowing axioms such as the above to be written as equations of higher type rather than as equation schemes. Notions of higher order transition system and bisimulation are then defined and using them the nonexistence of finite axiomatisations containing at most first order variables is shown. The same technique is then applied to calculi of star expressions containing a zero process  in contrast to the positive result given in [FZ93] for BPA ? , which differs only in that it does not contain a zero. 1 Introduction In this paper we consider the existence of finite equational axiomatisations for bisimulation over finite state processes. Such questions of axio...
Process Algebra with Recursive Operations
"... ing from just the two atomic actions in I def = fthrow; tailg, FIR b 1 yields I ((throw tail) throw head) = head: First, observe I (throw tail) = . Then, using (4), it easily follows that I ((throw tail) throw head) = head: This expresses that head eventually comes up, and thus ex ..."
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Cited by 13 (5 self)
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ing from just the two atomic actions in I def = fthrow; tailg, FIR b 1 yields I ((throw tail) throw head) = head: First, observe I (throw tail) = . Then, using (4), it easily follows that I ((throw tail) throw head) = head: This expresses that head eventually comes up, and thus excludes the infinite sequence of steps present in I ((throw tail) throw head). 7.2 Empty Process Let the symbol " denote the empty process, introduced as a unit for sequential composition by Koymans and Vrancken in [58] (see also [28, 74]). Obvious as " may be (being a unit for \Delta), its introduction is nontrivial because at the same time it must be a unit for k as well. In the design of BPA, PA, ACP and related axiom systems, it has proved useful to study versions of the theory, both with and without ". Just for this reason the star operation with its (original) defining equation as given by Kleene in [54] was introduced in process algebra. Taking y = " in x y, one obtains x ...
On the Complexity of Reasoning in Kleene Algebra
 Information and Computation
, 1997
"... We study the complexity of reasoning in Kleene algebra and *continuous Kleene algebra in the presence of extra equational assumptions E; that is, the complexity of deciding the validity of universal Horn formulas E ! s = t, where E is a finite set of equations. We obtain various levels of complexi ..."
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We study the complexity of reasoning in Kleene algebra and *continuous Kleene algebra in the presence of extra equational assumptions E; that is, the complexity of deciding the validity of universal Horn formulas E ! s = t, where E is a finite set of equations. We obtain various levels of complexity based on the form of the assumptions E. Our main results are: for * continuous Kleene algebra, ffl if E contains only commutativity assumptions pq = qp, the problem is \Pi 0 1 complete; ffl if E contains only monoid equations, the problem is \Pi 0 2 complete; ffl for arbitrary equations E, the problem is \Pi 1 1  complete. The last problem is the universal Horn theory of the *continuous Kleene algebras. This resolves an open question of Kozen (1994). 1 Introduction Kleene algebra (KA) is fundamental and ubiquitous in computer science. Since its invention by Kleene in 1956, it has arisen in various forms in program logic and semantics [17, 28], relational algebra [27, 32], aut...
Expressive Completeness of an EventPattern Reactive Programming Language
 In Proc. Int. Conf. on Formal Techniques for Networked and Distrib. Systems
, 2005
"... Abstract. Eventpattern reactive programs serve reactive components by preprocessing the input event stream and generating notifications according to temporal patterns. The declarative language PAR allows the expression of complex eventpattern reactions. Despite its simplicity and deterministic na ..."
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Abstract. Eventpattern reactive programs serve reactive components by preprocessing the input event stream and generating notifications according to temporal patterns. The declarative language PAR allows the expression of complex eventpattern reactions. Despite its simplicity and deterministic nature, PAR is expressively complete in the following sense: every eventpattern reactive system that can be described and implemented using finite memory can also be expressed in PAR. 1
Optimal Lower bounds on Regular Expression Size using Communication Complexity
 In: Proceedings of FoSSaCS: 273–286, LNCS 4962
, 2008
"... Abstract. The problem of converting deterministic finite automata into (short) regular expressions is considered. It is known that the required expression size is 2 Θ(n) in the worst case for infinite languages, and for finite languages it is n Ω(log log n) and n O(log n) , if the alphabet size grow ..."
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Abstract. The problem of converting deterministic finite automata into (short) regular expressions is considered. It is known that the required expression size is 2 Θ(n) in the worst case for infinite languages, and for finite languages it is n Ω(log log n) and n O(log n) , if the alphabet size grows with the number of states n of the given automaton. A new lower bound method based on communication complexity for regular expression size is developed to show that the required size is indeed n Θ(log n). For constant alphabet size the best lower bound known to date is Ω(n 2), even when allowing infinite languages and nondeterministic finite automata. As the technique developed here works equally well for deterministic finite automata over binary alphabets, the lower bound is improved to n Ω(log n). 1