Electronic Notes in Theoretical Computer Science 18 (1998) URL: 8 pages Towards characterizing bisim

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Electronic Notes in Theoretical Computer Science 18 (1998) URL: http://www.elsevier.nl/locate/entcs/volume18.html 8 pages Towards characterizing bisimilarity of value-passing processes with context-free control Pawe Paczkowski Institute of Mathematics University of Gda sk ul. Wita Stwosza 57 8952 Gda sk, Poland matpmp@univ.gda.pl Abstract A value-passing version of normed context-free processes is considered, where process behaviours depend on a global state of data variables. The problem of characterizing bisimilarity of such processes is posed. A solution of the formulated problem is presented for a restricted class of processes and possibilities of extending the result are discussed. The presented solution exploits a tableau decision method for pure, normed, context-free processes: based on a tableau, a system of implications is formulated, solution of which characterizes bisimulation equivalence for a pair of value-passing processes. 1 Introduction We consider a value-passing version of normed context-free processes, where process behaviours depend on a global state of data variables. Accordingly, the semantics and bisimulation depend on valuations of data variables. In this work we search for a formula characterizing those valuations of data variables for which two given processes are bisimilar. We aim at extending the results of [2,4,6], where regular processes were dealt with. The techniques used in these references cannot be directly applied to processes with context-free control. Here we exploit a tableau based decision procedure for bisimilarity for pure (that is, without value-passing), normed, context-free processes [3]. Weobtain a preliminary result for a restricted class of processes. The paper is organised as follows. In Section 2 value-passing processes with context-free control are dened. Section 3 contains the precise statement of the problem of characterizing bisimilarity of value-pasing processes and a rst attempt at a solution for a signicantly restricted class of processes. An c1998 Published by Elsevier Science B. V. Open access under CC BY-NC-ND license.

illustrative example is provided. In the nal section possible approaches to extending the presented result are briey discussed. This note presents an ongoing work. 2 Processes The class of processes we consider is obtained by extending normed contextfree processes, as dened in [3], with value-passing primitives. Let X Y Z : : : be a nite set of process variables. A value-passing process with context-free control is dened by a nite set of equations of the form (1) def X i = n X i j=1 a ij ij i =1:::m where X i are process variables, a ij are actions described below and ij are process variable sequences of length at most two (that is, we take processes expressed in 3-Greibach normal form). For every equation we assume some nite set of data variables ranged over by x. The actions a ij can have two forms: (2) (b c?x s) or (b c!e s) where b is a boolean expression, c is a channel name drawn from a xed set of channel names, x is adatavariable, e is an expression from a presupposed set of data expressions, and s is a simultaneous assignment: (x 1 ::: x k ):=(e 1 ::: e k ) Intuitively, an action (b c?x s) should be interpreted as an input of a value from channel c, under the condition that boolean b holds (before the new value of x has been received), after which the data variables are updated by performing assignment s. value of expression e is output to channel c. The output action (b c!e s) diers in that the In processes dened above, data variables can appear in data expressions and in boolean expressions. Thus, behaviours of processes depend on a global state, i.e. a valuation of data variables. The actions can modify the state by performing inputs and assignments the output values depend on the current valuation of data variables. The set of equations describes the context-free control of the process execution. The semantics of processes is dened formally by the following two-step procedure. Given a set of equations, we dene rst transitions of the form a where are sequences of process variables and a is an action as described by (2). The following rule is used to derive these transitions: X a j j if contains X def = 2 nx j=1 a j j

This denitions, essentially, follows [3] if our actions are treated just as symbols, disregarding their structure. We call these transitions symbolic. Next, we interpret the symbolic transitions with respect to valuations of data variables to derive semantic transitions of the form h i c?v h i or h i c!v h i where are valuations of data variables, i.e. functions from data variables to a presupposed set of data values, c is a channel name and v ranges over data values. The actions c?v and c!v that label semantic transitions represent, respectively, an input of value v from channel c and output of value v on channel c. The following two rules are used to derive semantic transitions. We use the notation [s] for a valuation obtained from by performing assignment s and we denote by [e ] the value of expression e under valuation. As usually, j= b stands for `boolean b is satised under valuation '. b c!e s j= b h i c![[e]] h[s] i b c?x s j= b c?v h i h[x := v][s] i for any value v In this paper we consider only normed processes. Following the denition of this notion for pure processes [1], we call the process dened by (1) normed if for every variable X in there is a nite sequence of symbolic transitions that starts from X and ends on ". 3 Characterizing Bisimilarity We adopt the standard denition of (strong) bisimulation equivalence between labelled transition systems (see e.g. [5]), denoting it by. 3.1 Statement of the problem Let and be two sets of equations dening value-passing context-free processes. Assume that process and data variables of are disjoint from process and data variables of. This can be always achieved by renaming variables. Let X and X be two process variables appearing, respectively, in and. The problem we consider is to characterize those valuations of data variables for which h Xi is bisimilar to h X i. More precisely, we look for a formula B X X of the rst order logic built on top of assumed sets booleans and data expressions such that (3) j= B X X i h Xih X i: 3

In [4,6], formulas characterizing bisimilarity in the sense above have been studied for regular processes. Such formulaswere found as solutions to systems of equivalences in a rst order logic extended with explicit substitutions. A system of equivalences, in the sense of [6], consists of a nite set of equivalences of the form (4) Pi, i(p 1 ::: Pm) i =1:::m where Pi are predicate variables and i(p 1 ::: Pm) are formulas of a rst order logic extended with explicit substitutions. The techniques used in [4,6] do not apply immediately to processes with context-free control as innite sets of equivalences could arise. For example, the approach used in [6] would require that a predicate variable is associated with every pair of congurations ( ), where is reachable by symbolic transitions from X and is reachable by symbolic transitions from X. There can be innitely many such pairs for context-free processes considered here and, consequently, innitely many predicate variables and equivalences would arise. In this work, we make rst steps towards extending the results of [4,6] to processes with context-free control. We adopt the following approach. In [3] a tableau decision method for bisimulation equivalence for pure, normed, context-free processes is presented. This method provides a nite structurea tableauwhich is a witness to bisimilarity. We exploit the possibility of using the nite tableau as a basis for formulating a nite system of equivalences solution of which would characterize bisimilarity. Below weshow that the proposed approach is successful for a signicantly restricted class of value-passing processes with context-free control: we consider processes with output actions only, whose boolean-parts are true and whose assignments are neutral, that is, cause no state change. Thus, the actions appearing in dening equations (1) can be abbreviated as c!e. Additionally,we assume that processes are deterministic, i.e. such that for every i in the dening equation (1), channels names appearing in actions faij j j =1:::nig are mutually dierent. In the next section we discuss the possibilities of releasing some of these restrictions. 3.2 Tableau construction Let and be two sets of equations dening normed value-passing processes and satisfying the above restrictions. Let X and X be two process variables appearing in and, respectively. Let us apply the method described in [3] to construct a tableau for X = X, where we take into account onlychannelparts of actions, that is, for the purpose of constructing tableau we consider actions c!e and c!e to be equal (we keep the actions unchanged though, as the expression-parts e and e will be needed later). Assume a successful tableau, in the sense of [3] has been constructed for X = X. Such a tableau is constructed by performing two kinds of steps summarized briey below. 4

Basic steps have the form shown below, where we assumed that the dening equations for X and X are X def = Pn a j=1 j j, X def = Pn. In the basic j=1 a j j step, every action a j of X is matched by an unique action a ij of X that uses the same channel as a j. There is at most one such action by the assumption that processes are deterministic there is at least one if the tableau is to be successful, which we assumed. Note, that there are n summands in both the sum dening X and the one dening X : again, this must be the case as we assumed that the tableau is successful and processes are deterministic. (5) ( nx j=1 a 1 1 = a i1 i1 X = X a j j ) =( 1 = i1 ::: nx j=1 a j j ) a n n = a in in n = in Substitution/reduction steps have two symmetric forms given below. Before a step of this kind can be performed, a residual has to be selected among the leaves of the tableaus resulting from preceding basic steps see [3] for details. (SubL) i = j i = j where = is the residual (SubR) i = j i = j where = is the residual A successful tableau is built using the steps above. Moreover, all the leaves of a successful tableau have one of two forms: (i) =, where there is a tableau node above it also labelled =,which is a root of a basic step (ii) = The intuition behind the tableau is that in order to show bisimulation equivalence between the pair of processes given above each line it is sucient to show the bisimulation(s) given below the line. 3.3 System of implications Based on a successful tableau we form a system of implications supposed to characterize bisimilarity. A system of implications diers from a system of equivalences (4) in that implications from left to right are used instead of equivalences. In order to construct the system of implications we associate predicate variables with nodes of the tableau: B = will denote the predicate variable associated with node =. The implications correspond to the steps in the tableau construction. For each basic step of the form (5) above, we include the following impli- 5

cation, where we assumed that each action a j appearing in (5) is c j!e j, and each a i j is c j!e i j : ^ (6) B X=X ) (e j = e i j ) ^ B j = i j j=1:::n For each instance of the rules (SubL) and (SubR) we include, respectively, the following implications into the system of implications: (7) B i = ) B j i = ^ B = j (8) ) B Bi= j i = ^ j B = Finally, for the successful terminal nodes of the form (ii) we formulate the trivial implication (9) B = ) true Proposition below explains in which sense the constructed system of implications characterizes bisimilarity. The property we obtain is weaker than (3) but nevertheless sucient for showing bisimulation equivalence of processes. Proposition 3.1 Let T be a successful tableau constructed for X = X. a set of formulas fb = g, where = ranges over the nodes of tableau T, satises the system of implications associated with T then j= B = h ih i. If implies Proof (sketch) The structure of the proof follows closely the soundness proof for the tableau decision method of [3]. We check that the relation R = f(h i h i) j j= B = g gives rise to a bisimulation containing R, similarly as self-bisimulations used in [3]. 2 The system of implications associated with a tableau can be converted into a system of equivalences if equivalences instead of implications are used in (6)(9). We conjecture that if a set of formulas fb = g is a solution to this system of equivalences then j= B = i h ih i thus providing the complete characterization of bisimilarity asin (3). 3.4 Example We end this section with an example. Consider the following sets, dening equations of : X def = (c!x)xx + d!( x) : X def = (c!y)y X + d!( y) Y def = (c!( z))x Y + d!z 6

X = X axx + b = ay X + b axx = a Y X b = b XX = Y X " = " XX = Y X (axx + b)x =(a X Y + b )X axxx = a X Y X bx = b X XXX = X Y X X = X XX = X Y (axx + b)x =(a Y X + b )Y axxx = a Y X Y bx = b Y XXX = Y X Y X = Y XX = Y X axx + b = a X Y + b axx = a X Y b = b XX = X Y " = " Table 1 A successful tableau for X = X is shown in Table 1, where we abbreviated the actions as follows a c!x b d!( x) a c!y b d!( y) a c!( z) b d!z The tableau allows us to formulate the following set of implications: B X=X ) (x = y) ^ B XX=Y X ^ ( x = y) ^ B "=" B "=" ) true B XX=Y X ) (x = z) ^ B XXX=X Y X ^ ( x = z) ^ B X=X B XXX=X Y X ) B XX=X Y ^ B X=X B XX=X Y ) (x = y) ^ B XXX=Y X Y ^ ( x = y) ^ B X=Y B XXX=Y X Y ) B XX=Y X ^ B X=Y B X=Y ) (x = z) ^ B XX=X Y ^ ( x = z) ^ B "=" It is easy to check that if we put formula x = y = z for every predicate variable appearing above we get a solution to this system of implications. By Proposition 3.1 we conclude that for every valuation which makes x = y = z we have h Xih X i 4 Discussion The purpose of this paper is to demonstrate that nite tableaus provided by the tableau decision method [3] can serve as a basis for formulating systems of 7

implications (and equivalences), solutions of which can be used to show (and, presumably, characterize precisely) bisimulation equivalence for value-passing processes with context-free control. Although the system of implications constructed in the previous section and Proposition 3.1 have been obtained for a severely restricted class of processes, we believe that most of these restrictions can be removed by appropriately adjusting the construction of the implications. In fact, for the restricted class of processes we could provide a simpler and more direct method of characterizing bisimilarity than via systems of implications, however, the method presented here was so designed as to serve as a basis for further extensions. The assumption that processes are deterministic was made to avoid technical complications, but there does not seem to be any essential diculty with handling nondeterministic processes. Reference [6] demonstrates techniques for handling input actions and assignments by allowing quantiers and explicit substitutions in the constructed systems of implications. The structure of the set of implications we formulated here is suitable for adopting these techniques, although providing implications corresponding to substitution/reduction steps presents some problems unresolved so far. Even more challenging is the combination of booleans and assignments in the actions. Another issue is the completeness of the presented approach: assuming h Xi h X i, can we always nd a tableau-based system of implications, solution of which proves the bisimilarity, i.e. such that j= B X=X? References [1] J.C.M. Baeten, J.A. Bergstra, and J.W. Klop, Decidability of bisimulation equivalence for processes generating context-free languages, in: J.W. de Bakker, A.J. Nijman, and P.C. Treleaven (Eds.), Proceedings of PARLE 87, LNCS 259, pp. 93114, Springer-Verlag, 1987. [2] M. Hennessy and H. Lin, Symbolic bisimulations, Theoretical Computer Science 138, pp. 353389, 1995. [3] H. H ttel and C. Stirling, Actions speak louder than words: proving bisimilarity for context-free processes, J. Logic Computat. 8 (4), pp. 485-59, 1998. [4] H. Lin, Symbolic transition graph with assignment, in: Proceedings of CONCUR'96, LNCS 1119, Springer-Verlag, 1996. [5] R. Milner, Communication and Concurrency, Prentice Hall, 1989. [6] P. Paczkowski, Characterizing bisimilarity of value-passing parametrised processes, in: B. Steen and T. Margaria (Eds.), Proceedings of INFINITY, International Workshop on Verication of Innite State Systems, Electronic Notes of Theoretical Computer Science 5, 1997. 8