TwoWay Parikh Automata with a Visibly Pushdown Stack
 6.8k Downloads
Abstract
In this paper, we investigate the complexity of the emptiness problem for Parikh automata equipped with a pushdown stack. Pushdown Parikh automata extend pushdown automata with counters which can only be incremented and an acceptance condition given as a semilinear set, which we represent as an existential Presburger formula over the final values of the counters. We show that the nonemptiness problem both in the deterministic and nondeterministic cases is NPc. If the input head can move in a twoway fashion, emptiness gets undecidable, even if the pushdown stack is visibly and the automaton deterministic. We define a restriction, called the singleuse restriction, to recover decidability in the presence of twowayness, when the stack is visibly. This syntactic restriction enforces that any transition which increments at least one dimension is triggered only a bounded number of times per input position. Our main contribution is to show that nonemptiness of twoway visibly Parikh automata which are singleuse is NExpTimec. We finally give applications to decision problems for expressive transducer models from nested words to words, including the equivalence problem.
1 Introduction
Parikh automata. Since the classical automatabased approach to modelchecking [28], finite automata have been extended in many ways to tackle the automatic verification of more realistic and powerful systems against more expressive specifications. For instance, they have been extended to pushdown systems [3, 26, 30], concurrent systems [5], and systems with counters or specifications with arithmetic constraints have been the focus of many works in verification [7, 11, 15, 16, 17, 18, 23].
Along this line of work, Parikh automata (or \(\mathsf {PA}\)), introduced in [22], are an important instance of automata extension with arithmetic constraints. They are automata on finite words whose transitions are equipped with counter operations. The counters can only be incremented, and do not influence the run (enabling a transition requires no test on counter values), but the acceptance of a run is defined by the membership of the final counter valuations to some semilinear set S. Expressivity of \(\mathsf {PA}\)s goes beyond regularity, as the language \(L=\{w\mid w_a=w_b\}\) of words having the same numbers of as and bs is realised by a simple automaton counting the numbers of as and bs in counters \(x_1\) and \(x_2\) respectively, and the accepting condition is given by the linearset \(\{ (i,i)\mid i\in \mathbb {N}\}\). Semilinear sets can be defined by formulas in existential Presburger arithmetic, ie firstorder formulas with equality and sum predicates over integers, whose free variables are evaluated by the counter values calculated by the run.
A central problem in automata theory is the nonemptiness problem: does the automaton accepts at least one input. Although \(\mathsf {PA}\)s go beyond regular languages, they retain relatively good algorithmic properties. The emptiness problem is decidable, and it is NPc [12]. The hardness holds even if the semilinear set is represented as a set of generator vectors. Motivated by applications in transducer theory for wellnested words, we investigate in this article extensions of Parikh automata with a pushdown stack.
First contribution: pushdown Parikh automata. As a first contribution, we study the complexity of the emptiness problem for Parikh automata with a pushdown store. Parikh automata extend finite automata with counter operations and an acceptance condition given as a semilinear set, pushdown Parikh automata extend pushdown automata in the same way. We show that adding a stack can be done for free with respect to the emptiness problem, which remains, as for stackfree Parikh automata, NPc. However in this case, we are able to strengthen the lower bound: it remains NPhard even if there are only two counters, the automaton is deterministic, and the Presburger formula only tests for equality of these two counters. In the stackfree setting, it is necessary to have an unfixed number of counters to get such a lower bound.
Contribution 1
The emptiness problem for pushdown Parikh automata (\(\mathsf {PPA}\)) is NPc. The lower bound holds even if the automaton is deterministic, has only two counters whose operations are encoded in unary, and they are eventually tested for equality.
Second contribution: adding twowayness. We investigate the complexity of pushdown Parikh automata when the input head is allowed to move in two directions. It is not difficult to see that in that case emptiness gets undecidable, since, already without counters, one can simulate the intersection of two deterministic pushdown automata, by performing two passes over the input (visiting each input position at most three times). We consider a first restriction on the stack behaviour, which is required to be visibly.
\(\mathsf {VPA}\) have been extended to twoway \(\mathsf {VPA}\) (\(\mathsf {2VPA}\)) [8] with the following stack constraints: in a backward reading mode, the role of the return and call symbols regarding the stack are inverted: when reading a call, exactly one symbol is popped from the stack and when reading a return, one symbol is pushed. It was shown in [8] that adding this visibly condition to twoway pushdown automata allows one to recover decidability for the emptiness problem. However, for Parikh acceptance, this restriction is not sufficient. Indeed, by encoding diophantine equations, we show the following undecidability result:
Contribution 2
The emptiness problem for twoway visibly pushdown Parikh automata (\(\mathsf {2VPPA}\)) is undecidable.
Singleuse property. The problem is that by using the combination of twowayness and a pushdown stack, it is possible to encode polynomially, and even exponentially large counter values, with respect to the length of the input word. We consider therefore the singleuse restriction, which appears in several transducer models [6, 8, 10], by which it is possible to keep a linear behaviour for the counters. Informally, a singleuse twoway machine bounds the size of the production per input positions. It is syntactically enforced by asking that transitions which strictly increment at least one counter are triggered at most once per input position. Our main result is the decidability of \(\mathsf {2VPPA}\) emptiness under the singleuse restriction, with tight complexity.
Contribution 3
(Main). The emptiness problem for twoway singleuse visibly pushdown Parikh automata (\(\mathsf {2VPPA_{su}}\)) is NExpTimec. The hardness holds even if the automaton is deterministic, has only two counters whose operations are encoded in unary, and they are eventually tested for equality.
Contribution 4
(Applications). As an application, we give an elementary upperbound (NExpTime) for the equivalence problem of functional singleuse twoway visibly pushdown transducers [8], while an ExpTime lower bound was known. This transducer model defines transductions from wellnested words to words and, as shown in [8], they are wellsuited to define XML transformations, have the same expressive power as Courcelle’s MSOtransducers [6] (casted to wellnested words), and admit a memoryefficient evaluation algorithm. We also provide two other new results on singleuse \(\mathsf {2VPT}\) (not necessarily functional). First, we show that given a positive integer k, it is decidable whether a singleuse \(\mathsf {2VPT}\) produces at most k different output words per input (kvaluedness problem). Then, we show the decidability of a typechecking problem: given a singleuse \(\mathsf {2VPT}\) T and a finite (stackfree) Parikh automaton P, it is decidable whether the codomain of T has a nonempty intersection with P. This allows for instance to decide whether a singleuse \(\mathsf {2VPT}\) produces only wellnested words and thus describes a wellnested words to wellnested words transformation, since the property of a word to be non wellnested is definable, as we show, by a Parikh automaton.
Finitevisit vs singleuseness. The singleuse property is more general than the more classical finitevisit restriction, used for instance in [9, 19]: it requires to visit any input position a (machinedependent) constant number of times, while singleuseness only bounds the number of visits by producing transitions. Although, consequently to our results, \(\mathsf {2VPPA}\) singleuse and finitevisit have the same expressive power, this extra modelling feature is desirable, for instance when using \(\mathsf {2VPPA}\) to test properties of \(\mathsf {2VPT}\): singleuse \(\mathsf {2VPT}\) are strictly more expressive than finitevisit ones, and this relaxation is crucial to capture MSO transductions [8]. Moreover, we somehow get it for free: we show that the NExpTime lower bound also holds for finitevisit \(\mathsf {2VPPA}\). Finally, we note that as we deal with singleuse machines rather than finitevisit ones, the usual ingredient for going from twoway to oneway consisting of memorizing simply crossing sections of states, is not sufficient to get the result here, since we cannot bound the size of these crossing sections.
Related work. Parikh automata are closely related to reversalbounded counter machines [18]. In fact, both models have equivalent expressiveness in the nondeterministic case [22]. The difference of expressive power in the deterministic case is due to the fact that counter machines can perform tests on its counters that can influence the run, while counters in Parikh automata only matter at the end of the run. Several extensions of reversalbounded counter machines were studied, whether they are twoway or equipped with a (visibly) pushdown stack. However, to the best of our knowledge, the combination of the two features has never been studied (see [19] for a survey). It is possible to define a model of singleuse reversalbounded twoway visibly pushdown counter machines, where the singleuseness is put on transitions that modify the counters. This model is expressively equivalent to \(\mathsf {2VPPA_{su}}\) in the nondeterminstic case, and thanks to our result, has a decidable emptiness problem. The nonemptiness problem for reversalbounded (oneway) pushdown counter machines for fixed numbers of counters and reversals is known to be in NP [13] and NPhard [16]. Converting \(\mathsf {PPA}\) into reversalbounded counter machines would yield an unfixed number of counters. Our NP lowerbound for \(\mathsf {PPA}\) however follows ideas of [16] about encoding, using the stack, integers n with O(log(n)) states and stack symbols.
Twoway (stackfree) reversalbounded counter machines, even deterministic, are known to have undecidable emptiness problem [19]. Decidability is recovered by taking the finitevisit restriction [19]. Our result on \(\mathsf {2VPPA_{su}}\) entails the decidability of emptiness of twoway reversalbounded counter machines which are singleuse.
Finally, all the decidability results we prove on twoway visibly pushdown transducers were already known in the oneway case [13]. Twoway visibly pushdown transducers, which are strictly more expressive, can also be seen as a model of unranked treetoword transducers, modulo tree linearisation. To the best of our knowledge, this is the first model of unranked treetoword transducers for which kvaluedness and codomain wellnestedness is shown to be decidable. Another model, introduced in [1], is known to be expressively equivalent to \(\mathsf {2VPT_{su}}\) [8], and in the functional case, has decidable equivalence problem in NExpTime. However, translating \(\mathsf {2VPT_{su}}\) to this model requires an exponential blowup, yielding a worst complexity for equivalence testing.
Structure. Section 2 introduces the computing models used, the proof of the lower bound for \(\mathsf {2VPPA_{su}}\) is given in Sect. 3 and the upper bound in Sect. 4. Finally, some applications to the main theorem to transducers are given in Sect. 5.
2 TwoWay Visibly Pushdown (Parikh) Automata
In this section, we first recall the definition of twoway visibly pushdown automata and later on extend them to twoway visibly pushdown Parikh automata.
We consider a structured alphabet \(\varSigma \) defined as the disjoint union of call symbols \(\varSigma _c\), return symbols \(\varSigma _r\) and internal symbols \(\varSigma _i\). The set of words over \(\varSigma \) is \(\varSigma ^*\). As usual, \(\epsilon \) denotes the empty word. Amongst nested words, the set of wellnested words \(\varSigma ^*_{\textsf {wn}}\) is defined as the least set such that \(\varSigma _i \cup \{\epsilon \}\) is included into \(\varSigma ^*_{\textsf {wn}}\) and if \(w_1,w_2 \in \varSigma ^*_{\textsf {wn}}\) then both \(w_1w_2\) and \(cw_1r\) (for all \(c \in \varSigma _c\) and \(r \in \varSigma _r\)) belong to \(\varSigma ^*_{\textsf {wn}}\).
When dealing with twoway machines, we assume the structured alphabet \(\varSigma \) to be extended to \(\overline{\varSigma }\) by adding a left and right marker symbols \(\triangleright ,\triangleleft \) in \(\overline{\varSigma }_c\) and \(\overline{\varSigma }_r\) respectively, and we consider words in the language \(\triangleright \varSigma ^* \triangleleft \).
Definition 1

\(\delta ^{\text {push}} \subseteq ((Q \times \{\rightarrow \} \times \varSigma _c ) \cup (Q \times \{\leftarrow \} \times \varSigma _r)) \times ((Q \times \mathbb {D}) \times \varGamma )\)

\(\delta ^{\text {pop}} \subseteq ((Q \times \{\leftarrow \} \times \varSigma _c \times \varGamma ) \cup (Q \times \{\rightarrow \} \times \varSigma _r \times \varGamma )) \times (Q \times \mathbb {D})\)

\(\delta ^{\text {int}} \subseteq ((Q \times \mathbb {D}\times \varSigma _i) \times (Q \times \mathbb {D})\)
Additionally, we require that for any states \(q,q'\) and any stack symbol \(\gamma \), if \((q,\leftarrow ,\triangleright ,\gamma ,q',d) \in \delta ^{\text {pop}}\) then \(d=\rightarrow \) and if \((q,\rightarrow ,\triangleleft ,\gamma ,q',d) \in \delta ^{\text {pop}}\) then \(d=\leftarrow \) ensuring that the reading head stays within the bounds of the input word.

\({\text {move}}(d,i)\) the integer \(i1\) if \(d=\leftarrow \) and \(i+1\) if \(d=\rightarrow \).

\({\text {read}}(w,d,i)\) the symbol w(i) if \(d=\leftarrow \) and \(w(i+1)\) if \(d=\rightarrow \).
Note that when switching directions (i.e. when the direction of the first part of the transition is different from the second part), we read twice the same letter. This ensures the good behavior of the stack, as reading a call letter from left to right pushes a stack symbol, we need to pop it if we start moving from right to left.

either \(d_j=\rightarrow \) and \({\text {read}}(w,d_j,i_j) \in \varSigma _c\) or \(d_j=\leftarrow \) and \({\text {read}}(w,d_j,i_j) \in \varSigma _r\), \(\tau _{j+1}=(q_j,d_j,{\text {read}}(w,d_j,i_j),q_{j+1},d_{j+1},\gamma ) \in \delta ^{\text {push}}\), \(i_{j+1}={\text {move}}(i_j,d_j)\) and \(\sigma _{j+1}=\sigma _j\gamma \)

either \(d_j=\leftarrow \) and \({\text {read}}(w,d_j,i_j) \in \varSigma _c\) or \(d_j=\rightarrow \) and \({\text {read}}(w,d_j,i_j) \in \varSigma _r\), \(\tau _{j+1}=(q_j,d_j,{\text {read}}(w,d_j,i_j),\gamma ,q_{j+1},d_{j+1}) \in \delta ^{\text {pop}}\), \(i_{j+1}={\text {move}}(i_j,d_j)\) and \(\sigma _{j+1}\gamma =\sigma _j\)

\({\text {read}}(w,d_j,i_j)\in \varSigma _i\), \(\tau _{j+1}=(q_j,d_j,{\text {read}}(w,d_j,i_j),q_{j+1},d_{j+1})\in \delta ^{\text {int}}\), \(i_{j+1}=i_j\) and \(\sigma _{j+1}=\sigma _j\).

deterministic (denoted \(\mathsf {D2VPA}\)) if \(\delta ^{\text {push}}\) (resp. \(\delta ^{\text {pop}}\), \(\delta ^{\text {int}}\)) is a function from \(Q\times \mathbb {D}\times \varSigma \) (resp. \(Q\times \mathbb {D}\times \varSigma \times \varGamma \), \(Q\times \mathbb {D}\times \varSigma \)) to \(Q\times \mathbb {D}\times \varGamma \) (resp. \(Q\times \mathbb {D}\), \(Q\times \mathbb {D}\)).

oneway (denoted \(\mathsf {VPA}\)) if all transitions in A have \(\rightarrow \) for direction.

finitevisit if for some \(k\ge 0\), any run visits at most k times the same input position.
The size of a \(\mathsf {2VPA}\) is the number of states times the size of the stack alphabet. For A an automaton, we denote by L(A) the language recognized by A.
Lemma 1
([8]). Given a \(\mathsf {2VPA}\) A, deciding if L(A) is empty is ExpTimecomplete.
Parikh automata. Parikh automata were introduced in [22]. Informally, they are automata with counters that can only be incremented, and do not act on the transition relation. Acceptance of runs is done by evaluating a Presburger formula whose free variables are set to the counter values. In our setting, a Presburger formula is a positive formula \(\psi (x_1,\ldots ,x_n)=\exists y_1\ldots y_m \varphi (x_1,\ldots ,x_n,y_1,\ldots ,y_m)\) such that \(\varphi \) is a boolean combination of atoms \(s+s'\le t+t'\), for \(s,s',t,t'\in \{0,1,x_1,\ldots ,x_n,y_1,\ldots ,y_m\}\). For a set S and some positive number m, we denote by \(S^m\) the set of all mappings from \([1\ldots m]\) to S. If \((s_1,\ldots ,s_m)\) and \((t_1,\ldots ,t_m)\) are two tuples of \(S^m\) and \(+\) is an binary operation on S, we extend \(+\) to \(S^m\) by considering the operation elementwise, i.e. \((s_1,\ldots ,s_m)+(t_1,\ldots ,t_m)=(s_1+t_1,\ldots ,s_m+t_m)\).
Definition 2
A twoway visibly pushdown Parikh automaton (\(\mathsf {2VPPA}\) for short) is a tuple \(P = (A,\lambda ,\phi )\) where A is a \(\mathsf {2VPA}\) and for some natural \( dim \), \(\lambda \) is a mapping from \(\delta \) to \(\mathbb {N}^ dim \), the set of vectors of length \( dim \) of naturals and \(\phi (x_1, \ldots , x_ dim )\) is a Presburger formula with \( dim \) free variables.
It is deterministic (resp. oneway), denoted \(\mathsf {D2VPPA}\) (resp. \(\mathsf {VPPA}\)) if its underlying automaton is deterministic (resp. oneway). It is known from [4] that \(\mathsf {DPA}\) (i.e. deterministic oneway and stackfree Parikh automata in our setting) are strictly less expressive than their nondeterministic counterpart. As a counter example, they exhibit the language \(L=\{w\mid w_{\#_a(w)}=b\}\), ie all words w such that if n is the number of a in w, the letter at the nth position is a b. Note that even in the twoway case, a deterministic machine recognizing L needs to either have access, during the computation, to the number of a’s, or be able to store, in counters, the position of each b. As the first solution cannot be done since Parikh automata only access their counters at the end of the run, and the second is also impossible since there are only a finite number of counters, this language is also non definable by a \(\mathsf {D2VPPA}\), furthering the separation between deterministic and nondeterministic Parikh automata.
Example 1
As an example, we give a deterministic \(\mathsf {2VPPA}\) P that, given an input \( i^n c^k i^\ell r^k\) with c, i, r in \(\varSigma _c\), \(\varSigma _i\) and \(\varSigma _r\) respectively, accepts if \(k=\ell \) and \(n=k^2\). The \(\mathsf {2VPPA}\) P uses 4 variables \(x_n\), \(x_k\), \(x_\ell \) and y. The first 3 variables are used to count the number of the first block of is, the number of calls and the second block of is respectively. The handling of these 3 variables is straightforward and can be done in a single pass over the input. The fourth variables y counts the multiplication \(k\cdot \ell \) and doing so is more involved. The part of the underlying \(\mathsf {2VPA}\) of P handling y is given in Fig. 2. On this part, the mapping \(\lambda \) simply increments the counter on transitions going to state 2 (i.e. on reading the letters i from left to right). It makes as many passes on the set of internal symbols in state 2 as there are call symbols, and the state of the stack upon reading \(i^\ell \) for the jth time is \(1^j0^{kj}\). Finally, the accepting formula \(\phi \) of P is defined by \(x_n=y \wedge x_k=x_\ell \). Note that this widget allows us to compute the set \(\{(k^2,k,k,k^2)\mid k\in \mathbb {N}\}\) which is not semilinear.
As we have seen in the previous example, the set \( Val (P)\) is not necessarily semilinear, even with P a \(\mathsf {D2VPPA}\). We use this fact to encode diophantine equations, and get the following undecidability result:
Theorem 1
The emptiness problem of \(\mathsf {D2VPPA}\) is undecidable.
Singleuseness. In order to recover decidability, we adapt to Parikh Automata the notion of singleuseness introduced in [8]. Simply put, a \(\mathsf {2VPPA}\) is singleuse (denoted \(\mathsf {2VPPA_{su}}\)) if the transitions that affect the variables can only be taken once on any given input position, thus effectively bounding the size of variables linearly with respect to the size of the input. Formally, a state p of a \(\mathsf {2VPPA}\) P is producing if there exists a transition t from p on some symbol and \(\lambda (t)\ne 0^ dim \). A \(\mathsf {2VPPA}\) is singleuse if for every input w and every accepting run \(\rho \) over w, there do not exist two different configurations \((p,i,d,\sigma )\) and \((p,i,d,\sigma ')\) with p a producing state, meaning that \(\rho \) does not reach any position in the same direction twice in any given state of P. This property is a syntaxic restriction of the model. However, since this property is regular, it can equivalently be seen as a semantic one. Moreover, deciding the singleuseness of a \(\mathsf {2VPPA}\) is ExpTimec (see [8] for the same result but on transducers). Note that the Parikh automaton given in Example 1 is not singleuse, since it passes over the second subword of internal letters i in state 2 as many times as there are call symbols. In the following, we prove that \(\mathsf {2VPPA_{su}}\) have the same expressiveness as \(\mathsf {VPPA}\), while being exponentially more succinct. In particular, this equivalence implies by Parikh’s Theorem [24], semilinearity of \( Val (P)\) for any \(\mathsf {2VPPA_{su}}\) P.
3 Emptiness Complexity
We show that the nonemptiness problem for \(\mathsf {VPPA}\) is NPcomplete. We actually show the upperbound for the strictly more expressive Pushdown Parikh Automata (\(\mathsf {PPA}\)), i.e. \(\mathsf {VPPA}\) without the visibly restriction. While decidability was known [20, 21], the precise complexity was, to the best of our knowledge, unknown. Let us also remark that the model and the proof are similar to the proof of NPcompleteness of kreversal pushdown systems from [16]. However, it is adapted here to Parikh automata as well as deterministic machines, which was not the case in [16].
Theorem 2
The nonemptiness problem for \(\mathsf {VPPA}\) and \(\mathsf {PPA}\) is NPcomplete. The complexity bounds hold even if the automata are deterministic, with a fixed dimension 2, tuples of values in \(\{0,1\}^2\) and with a fixed Presburger formula \(\phi (x_1,x_2) \equiv x_1=x_2\).
From \(\mathsf {2VPPA_{su}}\) to \(\mathsf {VPPA}\) From a twoway visibly pushdown Parikh automaton satisfying the singleuseness restriction, one can build an equivalent oneway visibly pushdown Parikh automaton. The construction induces an exponential blowup, which cannot be avoided, as with most constructions from twoway to oneway machines.
Theorem 3
For any \(\mathsf {2VPPA_{su}}\) A, one can construct a \(\mathsf {VPPA}\) B whose size is at most exponential in the size of A and such that L(A)=L(B). Moreover, the procedure can be done in exponential time.
Proof
(Sketch). The goal is to be able to correctly guess all the transitions exactly taken by a run of the twoway machine at once. More precisely, the oneway machine guesses the behavior of the twoway machine on each wellnested subword of the input, i.e. a set of partial runs over a subword. A partial run is a pair from \(Q\times \{\leftarrow ,\rightarrow \}\). Informally, they describe a maximal subrun over a subword of the input. We call these sets of partial runs profiles, and we define relations C and \(N_{c,r}\) to describe compatible profiles. Formally, the relation \(C\subseteq \mathcal {P}^3\) is the concatenation relation, defined as set of triples \((P,P',P'')\) such that there exists a word \(u=u_1vv'u_2\) where v and \(v'\) are wellnested subwords of u, and a run r on u such that P (resp. \(P'\)) is the profile of v in r (resp. of \(v'\)) and \(P''\) is the profile of \(vv'\) in r. Similarly, the relation \(N_{c,r}\subseteq \mathcal {P}^2\) for c, r call and return letters respectively, is the crnesting relation, and defined as the set of pairs \((P,P')\) such that there exists a word \(u=u_1cvru_2\) where v is wellnested, and a run r of A on u such that P is the profile of v in r and \(P'\) is the profile of cvr in r. We prove that these relations are computable in exponential time.
Given these relations, we can compute a \(\mathsf {VPPA}\) B whose runs are bijective to the runs of A. Moreover, we can recover from a run of B which transitions are effectively taken at each positions by its bijective run of A. Then, the increment function simply does all the increments done by the run at a given position at once. Since the operation is the addition on integers, it is commutative and the variables are updated in the same way they were by the run of A. Note that we only recover which transitions are taken, and not how many times they are taken, which can depend on the size of the input. However, since A is singleuse, we only have to add each non zero transition once, which gives the result.
As a direct corollary of Theorems 3 and 2, we get the following.
Corollary 1
The emptiness of \(\mathsf {2VPPA_{su}}\) can be decided in NExpTime.
4 NExpTimeHardness
In this section, we show that the problem of deciding whether the language of a \(\mathsf {2VPPA_{su}}\) is nonempty is hard for NExpTime. Moreover, we show that this hardness does not depend on the fact that we have taken existential Presburger formulas, nor on the vector dimensions, and nor on the fact that the values in the tuples are encoded in binary.
Theorem 4
The nonemptiness problem for \(\mathsf {2VPPA_{su}}\) is NExpTimehard. The result holds even if the automaton is deterministic, of dimension 2, with counter updates in \(\{0,1\}\), the Presburger formula is \(\phi (x_1,x_2)\equiv x_1=x_2\), and it is finitevisit.
Overview of the construction and encoding the values \(a_i\). Given an instance of SSSP \(\mathcal {I}\), our goal is to construct a \(\mathsf {D2VPPA_{su}}\) \(\mathcal {P} = (C,\rho ,\phi )\) of dimension 2 such that \(\mathcal {P}\) is polynomial in \(\theta  + k + m\) and \(\mathcal {L}(\mathcal {P})\ne \varnothing \) iff \(\mathcal {I}\) has a solution.
The main idea is to ensure that \(\mathcal {L}(C) = \{ X_1e_{1}\dots X_{2^k1}e_{2^k1}\#e_{2^k}\mid X_i\in \{0,1\}\}\) where the \(X_i\) are internal symbols which are used to encode a subset \(J\subseteq \{1,\dots ,2^k1\}\), and each \(e_{i}\) is an encoding of \(a_i\), defined later, over some alphabet containing the symbol \(\mathbb {1}\), and such that the number of occurrences of \(\mathbb {1}\) in \(e_{i}\) is \(a_i\). In other words, \(e_{i}\) somehow encodes \(a_i\) in unary. For the vector part, the machine \(\mathcal {P}\), when running over \(X_ie_i\), updates its dimensions depending on two cases: (1) if \(X_i = 1\) (“put value \(a_i\) in J”), then any transition reading \(\mathbb {1}\) has weight (1, 0) and any other transition has weight (0, 0), (2) if \(X_i = 0\), then every transition has weight (0, 0). So, if \(X_i = 1\), the value in the first dimension after processing \(X_ie_i\) has been incremented by \(a_i\). Similarly, when processing \(\#e_{2^k}\), any transition reading \(\mathbb {1}\) increments the 2nd dimension by 1, so that after processing \(\#e_{2^k}\), this dimension has value \(a_{2^k}\). The formula \(\phi (x_1,x_2)\) then only requires equality of \(x_1\) and \(x_2\), i.e. \(\phi (x_1,x_2) \equiv x_1=x_2\).
Lemma 2
The word \(u_m\) has length \(2^m\), and there exist m reversible finite automata \(A_0,\dots ,A_m\) (Fig. 3) such that (i) each \(A_i\) has O(1) states, and (ii) \(\bigcap _{i=1}^m L(A_i) = \{ u_m \}\).
Encoding of the values \(a_i\). The idea is to define a wellnested word \(e_{i}\) over an alphabet of call symbols \(\varSigma _c = \{ c_1,\dots ,c_m\}\), an alphabet of return symbols \(\varSigma _r = \{ r_1,\dots ,r_m\}\) and an alphabet of internal symbols Open image in new window . The number of occurrences of \(\mathbb {1}\) in \(e_{i}\) will be exactly \(a_i\), i.e. \(\#_\mathbb {1}(e_{i}) = a_i\) and hence, the Parikh automaton will just have to count the number of \(\mathbb {1}\) occurrences. Let us remind the reader that \(a_i\) is actually given by \(\theta \), and therefore, the automaton \(\mathcal {P}\) will somehow have to evaluate \(\theta \) for valuations of its variables that will be contained in \(e_{i}\). Let us now define the words \(e_{i}\). For that, we call a binary tree either an internal symbol Open image in new window , or a wellnested word of the form \(c_j t_1 t_2 r_j\) where \(t_1,t_2\) are themselves binary trees. For a wellnested word of the form cwr, a roottoleaf branch \(\pi \) is a sequence of calls \(x_1\dots x_n\) such that \(cwr = x_1 w_1 x_2 w_2 \dots x_n w_n r_n w'_n r_{n1} w'_{n1}\dots r_2 w'_2 r_1\) where \(x_1=c\), \(r_1=r\) and for some \(w_i,w'_i\) wellnested words such that \(w_n\) contains only internal symbols. The height of a binary tree t is the maximal length of a roottoleaf branch, and it is complete if all roottoleaf branches have the same length. Note that the number of internal symbols of a complete binary tree of height n is \(2^n\).
 1.
the words \(t_i\) are binary trees
 2.
every roottoleaf branch \(\pi = c_{i_1}\dots c_{i_\ell }\) of \(e_{i}\) satisfies \(i_1\dots i_\ell = u_m\)
 3.
\(b_i \in \{0,1\}^k\) and \(d_1,\dots ,d_{2^m}\) is a lexicographic enumeration of \(\{0,1\}^m\) (starting from \(0^m\))
 4.
for all j, all internal symbols occurring in \(t_j\) are \(\mathbb {1}\) if \(\theta [b_id_j]=1\), Open image in new window otherwise.
Our goal is now to prove that \(e_{i}\) is a correct encoding of \(a_i\).
Lemma 3
For all \(i\in \{1,\dots ,2^k\}\), \(\#_\mathbb {1}(e_{i}) = a_i\), where \(\#_\mathbb {1}(e_i)\) denotes the number of occurrences of \(\mathbb {1}\) in \(e_i\).
Proof
By Condition 2, every roottoleaf branch of \(e_{i}\) has length \(2^m\). Therefore, for all \(j\in \{1,\dots ,2^m\}\), every roottoleaf branch in \(t_j\) has length \(2^{m}j\). In particular, \(t_{2^m}\) does not contain any call symbol. Hence all the trees \(t_j\) are complete binary trees of height \(2^{m}j\). So, every \(t_j\) has \(2^{2^mj}\) internal symbols and by Condition 4, we get \(\#_\mathbb {1}(t_j) = \theta [b_id_j].2^{2^mj}\). Therefore, \( \#_\mathbb {1}(e_i) = \sum _{j=1}^{2^m} \#_\mathbb {1}(t_j) = \sum _{j=1}^{2^m} \theta [b_id_j].2^{2^mj} = a_i \).
Note that Condition 3 was not used in the previous proof, but it will be useful to define a succinct \(\mathsf {D2VPA}\) recognising \(e_i\). The key result is the following. It states the existence of a succinct \(\mathsf {D2VPA}\) which recognises exactly the candidate solutions to SSSP.
Lemma 4
One can construct a \(\mathsf {D2VPA}\) \(\mathcal {B}\) such that \(\mathcal {B}\) has polynomially many states in \(\theta +k+m\) and \( L(\mathcal {B}) = \{ X_1e_1\dots X_{2^k1}e_{2^k1}\#e_{2^k}\mid X_i\in \{0,1\}\} \).
Proof
(Sketch). First, we show the existence of a \(\mathsf {D2VPA}\) \(\mathcal {A}\) with polynomially many states in \(\theta +k+m\) such that \(L(\mathcal {A}) = \{ e_i\mid i\in \{1,\dots ,2^k\}\}\) (Proposition ?? in Appendix). The main idea is to construct succinct \(\mathsf {D2VPA}\) which check each of the conditions 1 to 4 of the definition of the encoding independently, and then to take their intersection (by running the first, then the second, etc.). Condition 1 is easy to check. For condition 2, we rely on Lemma 2, and run sequentially the automata \(A_i\) (in m passes) to check independently that for all i, each roottoleaf branch has a sequence of indices that belongs to \(A_i\). Thanks to the reversibility of \(A_i\), it is possible when going upward in the tree, to recover the previous state of \(A_i\). For condition 3, we rely on the twowayness to check that a sequence of m bits is a successor of another sequence succinctly, by doing O(m) passes over the two successor vectors. The stack is not necessary there. For condition 4, we rely on the existence of a succinct 2DFA which accepts all the valuations that satisfy a given Boolean formula.
We can finally construct the \(\mathsf {D2VPPA_{su}}\) \(\mathcal {P} = (\mathcal {C},\rho ,\phi )\) of dimension 2 whose language is nonempty iff the SSSP instance \(\mathcal {I}\) has a solution. The automaton \(\mathcal {C}\) performs a first pass on the whole word by running the automaton \(\mathcal {B}\) of Lemma 4, to check that the input is of the form \(X_1e_1\dots X_{2^k1}e_{2^k1}\#e_{2^k}\). During this pass, no vector dimension is incremented. During a second pass, \(\mathcal {C}\), when reading some \(X_i = 1\), it goes to some state \(q_1\) from which it increments the 1st dimension whenever \(\mathbb {1}\) is read (all other transitions have value (0, 0)). When reading some \(X_{i+1}\), it stays in \(q_1\) if \(X_{i+1}=1\) or to \(q_0\) otherwise, from which no transition touches the counters. When reading \(\#\), it goes to a state from which it increments only the 2nd dimension on reading \(\mathbb {1}\). Note that this automaton is singleuse: any symbol \(\mathbb {1}\) occurring in the whole input word is counted at most once. It is even finitevisit (each position is visited \(O(m+k+\theta )\) times). Finally, one only needs to check whether the first dimension equals the second one, using a formula \(\phi (x_1,x_2)\equiv x_1=x_2\). Note that the following lemma proves Theorem 4, since SSSP is NExpTimec.
Lemma 5
Given an instance \(X,Y,\theta \) of SSSP, one can construct a \(\mathsf {D2VPPA_{su}}\) \(\mathcal {P}\) of polynomial size in \(\theta +X+Y\) such that \(L(\mathcal {P})\ne \varnothing \) iff SSSP has a solution.
5 Applications to Decision Problems for Nested Word Transducers
In this section, we give two applications of \(\mathsf {2VPPA}\), namely on decision problems for twoway visibly pushdown transducers (\(\mathsf {2VPT}\)). \(\mathsf {2VPT}\) were introduced in [8] as a model to define transductions from wellnested words to words, or, modulo tree linearisation, from tree to words. It was shown that they can express, even in their deterministic and singleuse version, all functions from wellnested words to words definable in MSOT, in the sense of Courcelle [6], while having decidable equivalence problem. No upper bound was provided however. Using \(\mathsf {2VPPA}\), we show that the equivalence of \(\mathsf {2VPT_{su}}\) defining functions can be tested in NExpTime. We also consider other standard problems from transducer theory and show, again using \(\mathsf {2VPPA}\), their decidability. First, let us define formally \(\mathsf {2VPT}\).
A twoway visibly pushdown transducer (\(\mathsf {2VPT}\) for short) is a pair \((A,\mu )\) where A is a \(\mathsf {2VPA}\) and \(\mu \) is a morphism from the sequences of transitions \(\delta ^*\) to some output alphabet \(\varGamma ^*\). A run of a \(\mathsf {2VPT}\) is a run of its underlying \(\mathsf {2VPA}\). The output of a run \(\rho \) of the form \((q_0,i_0,d_0,\sigma _0) \tau _1 (q_1,i_1,d_1,\sigma _1) \tau _2 \ldots \tau _\ell (q_\ell ,i_\ell ,d_\ell ,\sigma _\ell )\) is \(\mu (\tau _1...\tau _\ell )\). A run is accepted if it is accepted by its underlying automaton. The transduction defined by a \(\mathsf {2VPT}\) is the set of pairs (u, v) such that v is the output of some accepting run on u. A state p of a \(\mathsf {2VPT}\) is producing if there exists a transition \(\tau \) such that p is the first component of \(\tau \) and \(\mu (\tau )\ne \epsilon \). Similarly to Parikh automata, a \(\mathsf {2VPT}\) T is singleuse (denoted \(\mathsf {2VPT_{su}}\)) if for any valid run of T, we do not reach the same position twice in the same producing state. It is deterministic, denoted \(\mathsf {D2VPT}\), if its underlying automaton is deterministic.
Deciding the kvaluedness and equivalence problems. For any positive integer k, we say that a transducer is kvalued if all input word have at most k different outputs. In particular, it is 1valued if it defines a (partial) function, and also called functional in that case.
Theorem 5
Let T be a \(\mathsf {2VPT_{su}}\), and k an integer. Then the kvaluedness of T can be decided in NExpTime. It is also ExpTimehard.
The theorem is proved by reducing the kvaluedness of T to the emptiness of a \(\mathsf {2VPPA_{su}}\) \(\mathcal {P}\) that guesses \(k+1\) runs of T that produce \(k+1\) different outputs. To ensure that the output are different, during each run \(\mathcal {P}\) guesses, and stores in counters, k output positions and the letters produced at these positions. The formula of \(\mathcal {P}\) at the end simply checks, for each pairs of runs, that the same positions were guessed by both runs, and that the letters were different, ensuring that the guessed runs have different output pairwise. As two functional transducers are equivalent if they have the same domain and their union is 1valued, we get the following corollary.
Corollary 2
The equivalence of two functional \(\mathsf {2VPT_{su}}\) T and \(T'\) can be decided in NExpTime. It is also ExpTimehard.
The NexpTime complexity of equivalence of tree to string transducers was already established for Streaming Tree to string transducers (STST), introduced in [1]. However, the conversion between the \(\mathsf {2VPT_{su}}\) and STST yields an exponential blowup.
We can generalize Corollary 2 to strictly kvalued transducers. We say that a transducer T is strictly kvalued if each input word in the domain of T has exactly k different images. Then similarly to the previous corollary, two strictly kvalued transducers are equivalent if, and only if, they have same domain and their union is kvalued.
Corollary 3
The equivalence of two strictly kvalued \(\mathsf {2VPT_{su}}\) T and \(T'\) can be decided in NExpTime. It is also ExpTimehard.
Strict kvaluedness is however an undecidable property (this can be shown by using the Post correspondence problem), even for \(k=2\). Deciding the equivalence problem for kvalued \(\mathsf {2VPT_{su}}\) (which are not necessarily strictly kvalued) is open already in the stackless case, and a (very) particular case has been solved in [14].
Typechecking against Parikh properties. Given a \(\mathsf {2VPT}\) T, it might be desirable to check some properties of the output words it produces, i.e., for a language L, whether the codomain of T is included in L. Formally, the typechecking problem asks, given a transducer T and a language L, whether \(T(\varSigma ^*)\subseteq L\). Unfortunately, this problem is undecidable when L is given by a visibly pushdown automaton (and T is a \(\mathsf {VPT}\)) [13]. Nevertheless, we show that the typechecking problem is decidable when T is a \(\mathsf {2VPT_{su}} \) and L is the complement of the language given by a (stackless) Parikh Automaton. As a consequence, we are able to decide whether a \(\mathsf {2VPT_{su}}\) T produces only wellnested words, i.e. if the output alphabet of T is structured and for every input word u and any \(v\in T(u)\), v is a wellnested word.
Theorem 6
Let T be a \(\mathsf {2VPT_{su}}\) and P be a (stackfree) Parikh Automaton over the output alphabet of T. Then we can decide whether \(T(\varSigma ^*)\cap L(P)=\emptyset \) in NExpTime. It is also ExpTimehard.
This is done by constructing a \(\mathsf {2VPPA_{su}}\) \(P'\) which simulates T, and instead of producing letters, simulates P on the output of T. A word w on a structured alphabet \(\varSigma \) is not wellnested if either \(w_c\ne w_r\), i.e. the number of call letters is not equal to the number of return letters, or if there exists a prefix u of w such that \(u_c < u_r\). As this can be checked by a (nondeterministic) Parikh automata, we get the following corollary.
Corollary 4
Let T be a \(\mathsf {2VPT_{su}}\) whose output alphabet is structured. It can be decided in CoNExpTime whether T only produces wellnested words.
Notes
Acknowledgements
This work was supported by the Belgian FNRS CDR project Flare (J013116), the ARC project Transform (Fédération Wallonie Bruxelles) and by the ANR Project DELTA, ANR16CE400007. Emmanuel Filiot is an FNRS research associate (Chercheur Qualifié).
References
 1.Alur, R., D’Antoni, L.: Streaming tree transducers. In: Czumaj, A., Mehlhorn, K., Pitts, A., Wattenhofer, R. (eds.) ICALP 2012. LNCS, vol. 7392, pp. 42–53. Springer, Heidelberg (2012). https://doi.org/10.1007/9783642315855_8CrossRefGoogle Scholar
 2.Alur, R., Madhusudan, P.: Adding nesting structure to words. J. ACM 56(3), 16:1–16:43 (2009)MathSciNetCrossRefGoogle Scholar
 3.Burkart, O., Steffen, B.: Model checking the full modal mucalculus for infinite sequential processes. In: Degano, P., Gorrieri, R., MarchettiSpaccamela, A. (eds.) ICALP 1997. LNCS, vol. 1256, pp. 419–429. Springer, Heidelberg (1997). https://doi.org/10.1007/3540631658_198CrossRefGoogle Scholar
 4.Cadilhac, M., Finkel, A., McKenzie, P.: On the expressiveness of Parikh automata and related models. In: Proceedings of the Third Workshop on NonClassical Models for Automata and Applications  NCMA 2011, Milan, Italy, 18 July–19 July 2011, pp. 103–119 (2011)Google Scholar
 5.Clarke, E.M., Emerson, E.A., Sistla, A.P.: Automatic verification of finite state concurrent systems using temporal logic specifications. In: Conference Record of the Tenth Annual ACM Symposium on Principles of Programming Languages, pp. 117–126. ACM, January 1983Google Scholar
 6.Courcelle, B., Engelfriet, J.: Graph Structure and Monadic SecondOrder Logic  A LanguageTheoretic Approach. Encyclopedia of Mathematics and its Applications, vol. 138. Cambridge University Press (2012). http://www.cambridge.org/fr/knowledge/isbn/item5758776/?site_locale=fr_FR
 7.Dang, Z., Ibarra, O.H., Bultan, T., Kemmerer, R.A., Su, J.: Binary reachability analysis of discrete pushdown timed automata. In: Emerson, E.A., Sistla, A.P. (eds.) CAV 2000. LNCS, vol. 1855, pp. 69–84. Springer, Heidelberg (2000). https://doi.org/10.1007/10722167_9CrossRefGoogle Scholar
 8.Dartois, L., Filiot, E., Reynier, P.A., Talbot, J.M.: Twoway visibly pushdown automata and transducers. In: Proceedings of the 31st Annual ACM/IEEE Symposium on Logic in Computer Science, LICS 2016, New York, NY, USA, 5–8 July 2016, pp. 217–226 (2016). https://doi.org/10.1145/2933575.2935315
 9.Engelfriet, J., Hoogeboom, H.J.: MSO definable string transductions and twoway finitestate transducers. ACM Trans. Comput. Logic 2(2), 216–254 (2001)MathSciNetCrossRefGoogle Scholar
 10.Engelfriet, J., Maneth, S.: Macro tree transducers, attribute grammars, and MSO definable tree translations. Inf. Comput. 154(1), 34–91 (1999). https://doi.org/10.1006/inco.1999.2807. http://www.sciencedirect.com/science/article/pii/S0890540199928079MathSciNetCrossRefzbMATHGoogle Scholar
 11.Esparza, J., Ganty, P.: Complexity of patternbased verification for multithreaded programs. ACM SIGPLAN Not.  POPL 2011 46(1), 499–510 (2011). https://doi.org/10.1145/1925844.1926443CrossRefzbMATHGoogle Scholar
 12.Figueira, D., Libkin, L.: Path logics for querying graphs: combining expressiveness and efficiency. In: 30th Annual ACM/IEEE Symposium on Logic in Computer Science, LICS 2015, Kyoto, Japan, 6–10 July 2015, pp. 329–340 (2015). https://doi.org/10.1109/LICS.2015.39
 13.Filiot, E., Raskin, J.F., Reynier, P.A., Servais, F., Talbot, J.M.: Properties of visibly pushdown transducers. In: Hliněný, P., Kučera, A. (eds.) MFCS 2010. LNCS, vol. 6281, pp. 355–367. Springer, Heidelberg (2010). https://doi.org/10.1007/9783642151552_32CrossRefzbMATHGoogle Scholar
 14.Gallot, P., Muscholl, A., Puppis, G., Salvati, S.: On the decomposition of finitevalued streaming string transducers. In: STACS 2017. LIPIcs, vol. 66, pp. 34:1–34:14 (2017). https://doi.org/10.4230/LIPIcs.STACS.2017.34. http://drops.dagstuhl.de/opus/volltexte/2017/6999
 15.Haase, C.: On the complexity of model checking counter automata. Ph.D. thesis, University of Oxford, UK (2012). http://ora.ox.ac.uk/objects/uuid:f43bf043de934b5c826f88f1bd4c191d
 16.Hague, M., Lin, A.W.: Model checking recursive programs with numeric data types. In: Gopalakrishnan, G., Qadeer, S. (eds.) CAV 2011. LNCS, vol. 6806, pp. 743–759. Springer, Heidelberg (2011). https://doi.org/10.1007/9783642221101_60CrossRefGoogle Scholar
 17.Hague, M., Lin, A.W.: Synchronisation and reversalbounded analysis of multithreaded programs with counters. In: Madhusudan, P., Seshia, S.A. (eds.) CAV 2012. LNCS, vol. 7358, pp. 260–276. Springer, Heidelberg (2012). https://doi.org/10.1007/9783642314247_22CrossRefGoogle Scholar
 18.Ibarra, O.H.: Reversalbounded multicounter machines and their decision problems. J. ACM 25(1), 116–133 (1978). http://doi.acm.org/10.1145/322047.322058MathSciNetCrossRefGoogle Scholar
 19.Ibarra, O.H.: Automata with reversalbounded counters: a survey. In: Jürgensen, H., Karhumäki, J., Okhotin, A. (eds.) DCFS 2014. LNCS, vol. 8614, pp. 5–22. Springer, Cham (2014). https://doi.org/10.1007/9783319097046_2CrossRefGoogle Scholar
 20.Karianto, W.: Parikh automata with pushdown stack. Technical report (2004)Google Scholar
 21.Klaedtke, F.: Parikh automata and monadic secondorder logics with linear cardinality constraints. Technical report, 30 July 2002Google Scholar
 22.Klaedtke, F., Rueß, H.: Monadic secondorder logics with cardinalities. In: Baeten, J.C.M., Lenstra, J.K., Parrow, J., Woeginger, G.J. (eds.) ICALP 2003. LNCS, vol. 2719, pp. 681–696. Springer, Heidelberg (2003). https://doi.org/10.1007/3540450610_54. http://dl.acm.org/citation.cfm?id=1759210.1759277CrossRefGoogle Scholar
 23.König, B., Esparza, J.: Verification of graph transformation systems with contextfree specifications. In: Ehrig, H., Rensink, A., Rozenberg, G., Schürr, A. (eds.) ICGT 2010. LNCS, vol. 6372, pp. 107–122. Springer, Heidelberg (2010). https://doi.org/10.1007/9783642159282_8CrossRefzbMATHGoogle Scholar
 24.Parikh, R.J.: On contextfree languages. J. ACM 13(4), 570–581 (1966). https://doi.org/10.1145/321356.321364CrossRefzbMATHGoogle Scholar
 25.Scarpellini, B.: Complexity of subcases of Presburger arithmetic. Trans. Am. Math. Soc. 284(1), 203–218 (1984)MathSciNetCrossRefGoogle Scholar
 26.Schwoon, S.: Model checking pushdown systems. Ph.D. thesis, Technical University Munich, Germany (2002). http://tumb1.biblio.tumuenchen.de/publ/diss/in/2002/schwoon.html
 27.Shepherdson, J.C.: The reduction of twoway automata to oneway automata. IBM J. Res. Dev. 3(2), 198–200 (1959)MathSciNetCrossRefGoogle Scholar
 28.Vardi, M.Y., Wolper, P.: An automatatheoretic approach to automatic program verification (preliminary report). In: LICS, pp. 332–344. IEEE Computer Society (1986)Google Scholar
 29.Verma, K.N., Seidl, H., Schwentick, T.: On the complexity of equational horn clauses. In: Nieuwenhuis, R. (ed.) CADE 2005. LNCS (LNAI), vol. 3632, pp. 337–352. Springer, Heidelberg (2005). https://doi.org/10.1007/11532231_25CrossRefGoogle Scholar
 30.Walukiewicz, I.: Pushdown processes: games and modelchecking. Inf. Comput. 164(2), 234–263 (2001). https://doi.org/10.1006/inco.2000.2894. http://www.sciencedirect.com/science/article/pii/S0890540100928943MathSciNetCrossRefzbMATHGoogle Scholar
Copyright information
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.