The Effects of Adding Reachability Predicates in Propositional Separation Logic
Abstract
The list segment predicate \(\mathtt {ls}\) used in separation logic for verifying programs with pointers is wellsuited to express properties on singlylinked lists. We study the effects of adding \(\mathtt {ls}\) to the full propositional separation logic with the separating conjunction and implication, which is motivated by the recent design of new fragments in which all these ingredients are used indifferently and verification tools start to handle the magic wand connective. This is a very natural extension that has not been studied so far. We show that the restriction without the separating implication can be solved in polynomial space by using an appropriate abstraction for memory states whereas the full extension is shown undecidable by reduction from firstorder separation logic. Many variants of the logic and fragments are also investigated from the computational point of view when \(\mathtt {ls}\) is added, providing numerous results about adding reachability predicates to propositional separation logic.
1 Introduction
Separation logic [20, 25, 28] is a wellknown assertion logic for reasoning about programs with dynamic data structures. Since the implementation of Smallfoot and the evidence that the method is scalable [3, 33], many tools supporting separation logic as an assertion language have been developed [3, 8, 9, 16, 17, 33]. Even though the first tools could handle relatively limited fragments of separation logic, like symbolic heaps, there is a growing interest and demand to consider extensions with richer expressive power. We can point out three particular extensions of symbolic heaps (without list predicates) that have been proved decidable.

Symbolic heaps with generalised inductive predicates, adding a fixpoint combinator to the language, is a convenient logic for specifying data structures that are more advanced than lists or trees. The entailment problem is known to be decidable by means of tree automata techniques for the bounded treewidth fragment [1, 19], whereas satisfiability is ExpTimecomplete [6]. Other related results can be found in [21].

Listfree symbolic heaps with all classical Boolean connectives \(\wedge \) and \(\lnot \) (and with the separating conjunction \(*\)), called herein \(\mathrm {SL}(*)\), is a convenient extension when combinations of results of various analysis need to be expressed, or when the analysis requires a complementation. This extension already is PSpacecomplete [11].

Propositional separation logic with separating implication, a.k.a. magic wand Open image in new window , is a convenient fragment (called herein Open image in new window ) in which can be solved two problems of frame inference and abduction, that play an important role in static analysers and provers built on top of separation logic. Open image in new window can be decided in PSpace thanks to a small model property [32].
A natural question is how to combine these extensions, and which separation logic fragment that allows Boolean connectives, magic wand and generalised recursive predicates can be decided with some adequate restrictions. As already advocated in [7, 18, 24, 29, 31], dealing with the separating implication Open image in new window is a desirable feature for program verification and several semiautomated or automated verification tools support it in some way, see e.g. [18, 24, 29, 31].
Our Contribution. In this paper, we address the question of combining magic wand and inductive predicates in the extremely limited case where the only inductive predicate is the gentle list segment predicate \(\mathtt {ls}\). So the starting point of this work is this puzzling question: what is the complexity/decidability status of propositional separation logic Open image in new window enriched with the list segment predicate \(\mathtt {ls}\) (herein called Open image in new window )? More precisely, we study the decidability/complexity status of extensions of propositional separation logic Open image in new window by adding one of the reachability predicates among \(\mathtt {ls}\) (precise predicate as usual in separation logic), \(\mathtt {reach}\) (existence of a path, possibly empty) and \(\mathtt {reach}^{\scriptscriptstyle {+}}\) (existence of a nonempty path).
First, we establish that the satisfiability problem for the propositional separation logic Open image in new window is undecidable. Our proof is by reduction from the undecidability of firstorder separation logic [5, 14], using an encoding of the variables as heap cells (see Theorem 1). As a consequence, we also establish that Open image in new window is not finitely axiomatisable. Moreover, our reduction requires a rather limited expressive power of the list segment predicate, and we can strengthen our undecidability results to some fragments of Open image in new window . For instance, surprisingly, the extension of Open image in new window with the atomic formulae of the form \(\mathtt {reach}(\mathtt {x},\mathtt {y}) = 2\) and \(\mathtt {reach}(\mathtt {x},\mathtt {y}) = 3\) (existence of a path between \(\mathtt {x}\) and \(\mathtt {y}\) of respective length 2 or 3) is already undecidable, whereas the satisfiability problem for Open image in new window is known to be in PSpace [15].
Second, we show that the satisfiability problem for \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}})\) is PSpacecomplete, extending the wellknown result on \(\mathrm {SL}(*)\). The PSpace upper bound relies on a small heap property based on the techniques of test formulae, see e.g. [4, 15, 22, 23], and the PSpacehardness of \(\mathrm {SL}(*)\) is inherited from [11]. The PSpace upper bound can be extended to the fragment of Open image in new window made of Boolean combinations of formulae from Open image in new window (see the developments in Sect. 4). Even better, we show that the fragment of Open image in new window in which \(\mathtt {reach}^{\scriptscriptstyle {+}}\) is not in the scope of Open image in new window is decidable. As far as we know, this is the largest fragment including full Boolean expressivity, Open image in new window and \(\mathtt {ls}\) for which decidability is established.
2 Preliminaries
Let \(\mathrm PVAR= \{ \mathtt {x}, \mathtt {y}, \ldots \}\) be a countably infinite set of program variables and \(\mathrm{LOC}= \{ \ell _0,\ell _1, \ell _2, \ldots \}\) be a countable infinite set of locations. A memory state is a pair \((s,h)\) such that \(s: \mathrm PVAR\rightarrow \mathrm{LOC}\) is a variable valuation (known as the store) and \(h: \mathrm{LOC}\rightarrow _{\text {fin}} \mathrm{LOC}\) is a partial function with finite domain, known as the heap. We write \(\mathrm{dom}(h)\) to denote its domain and \(\mathrm{ran}(h)\) to denote its range. Given a heap \(h\) with \(\mathrm{dom}(h) = \{ \ell _1, \ldots , \ell _n \}\), we also write \(\{ \ell _1 \mapsto h(\ell _1), \ldots ,\ell _n \mapsto h(\ell _n) \}\) to denote \(h\). Each \(\ell _i \mapsto h(\ell _i)\) is understood as a memory cell of \(h\).
Variants with Other Reachability Predicates. We use two additional reachability predicates \(\mathtt {reach}(\mathtt {x},\mathtt {y})\) and \(\mathtt {reach}^{\scriptscriptstyle {+}}(\mathtt {x},\mathtt {y})\) and we write Open image in new window (resp. Open image in new window ) to denote the variant of Open image in new window in which \(\mathtt {ls}\) is replaced by \(\mathtt {reach}\) (resp. by \(\mathtt {reach}^{\scriptscriptstyle {+}}\)). The relation \(\models \) is extended as follows: \((s,h) \models \mathtt {reach}(\mathtt {x},\mathtt {y})\) holds when there is \(i \ge 0\) such that \(h^i(s(\mathtt {x})) = s(\mathtt {y})\) (i functional composition(s) of \(h\) is denoted by \(h^i\)) and \((s,h) \models \mathtt {reach}^{\scriptscriptstyle {+}}(\mathtt {x},\mathtt {y})\) holds when there is \(i \ge 1\) such that \(h^i(s(\mathtt {x})) = s(\mathtt {y})\). As Open image in new window and Open image in new window , the logics Open image in new window and Open image in new window have identical decidability status. As far as computational complexity is concerned, a similar analysis can be done as soon as \(*\), \(\lnot \), \(\wedge \) and \(\mathtt {emp}\) are parts of the fragments (the details are omitted here). Similarly, we have the equivalences: Open image in new window and Open image in new window . So clearly, \(\mathrm {SL}(*, \mathtt {reach})\) and \(\mathrm {SL}(*, \mathtt {ls})\) can be viewed as fragments of \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}})\) and, Open image in new window as a fragment of Open image in new window . It is therefore stronger to establish decidability or complexity upper bounds with \(\mathtt {reach}^{\scriptscriptstyle {+}}\) and to show undecidability or complexity lower bounds with \(\mathtt {ls}\) or \(\mathtt {reach}\). Herein, we provide the optimal results.
Decision Problems. Let \(\mathfrak {L}\) be a logic defined above. As usual, the satisfiability problem for \(\mathfrak {L}\) takes as input a formula \(\varphi \) from \(\mathfrak {L}\) and asks whether there is \((s,h)\) such that \((s,h) \models \varphi \). The validity problem is also defined as usual. The modelchecking problem for \(\mathfrak {L}\) takes as input a formula \(\varphi \) from \(\mathfrak {L}\), \((s,h)\) and asks whether \((s,h) \models \varphi \) (\(s\) is restricted to the variables occurring in \(\varphi \) and \(h\) is encoded as a finite and functional graph). Unless otherwise specified, the size of a formula \(\varphi \) is understood as its tree size, i.e. approximately its number of symbols.
The main purpose of this paper is to study the decidability/complexity status of Open image in new window and its fragments.
3 Undecidability of Open image in new window
In this section, we show that Open image in new window has an undecidable satisfiability problem even though it does not admit firstorder quantification.
Proposition 1
[5, 14] The satisfiability problem for Open image in new window is undecidable and the set of valid formulae for Open image in new window is not recursively enumerable.
In a nutshell, we establish the undecidability of Open image in new window by reduction from the satisfiability problem for Open image in new window . The reduction is nicely decomposed in two intermediate steps: (1) the undecidability of Open image in new window extended with a few atomic predicates, to be defined soon, and (2) a tour de force resulting in the encoding of these atomic predicates in Open image in new window .
3.1 Encoding Quantified Variables as Cells in the Heap

\((s,h)\!\models \mathtt {alloc}^{1}(\mathtt {x})\) holds whenever \(s(\mathtt {x}) \in \mathrm{ran}(h)\),

\((s,h)\!\models n(\mathtt {x})=n(\mathtt {y})\) holds iff \(\{s(\mathtt {x}),s(\mathtt {y})\} \subseteq \mathrm{dom}(h)\) and \(h(s(\mathtt {x}))=h(s(\mathtt {y}))\),

\((s,h)\!\models n(\mathtt {x})\!\hookrightarrow \!n(\mathtt {y})\) holds iff \(\{s(\mathtt {x}),s(\mathtt {y})\} \subseteq \mathrm{dom}(h)\) and \({h^2(s(\mathtt {x}))=h(s(\mathtt {y}))}\).
Let us first intuitively explain how the two last predicates will help encoding Open image in new window . By definition, the satisfaction of the quantified formula \(\forall \mathtt {x}\ \psi \) from Open image in new window requires the satisfaction of the formula \(\psi \) for all the values in \(\mathrm{LOC}\) assigned to \(\mathtt {x}\). The principle of the encoding is to use a set L of locations initially not in the domain or range of the heap to mimic the store by modifying how they are allocated. In this way, a variable will be interpreted by a location in the heap and, instead of checking whenever \(\mathtt {x}\hookrightarrow \mathtt {y}\) (or \(\mathtt {x}= \mathtt {y}\)) holds, we will check if \(n(\mathtt {x}) \hookrightarrow n(\mathtt {y})\) (or \(n(\mathtt {x}) = n(\mathtt {y})\)) holds, where \(\mathtt {x}\) and \(\mathtt {y}\) correspond, after the translation, to the locations in L that mimic the store for those variables. Let X be the set of variables needed for the translation. In order to properly encode the store, each location in L only mimics exactly one variable, i.e. there is a bijection between X and L, and cannot be reached by any location. As such, the formula \(\forall \mathtt {x}\ \psi \) will be encoded by the formula Open image in new window , where \(\text {OK}(X)\) (formally defined below) checks whenever the locations in L still satisfy the auxiliary conditions just described, whereas \(\mathrm {T}(\psi )\) is the translation of \(\psi \).
For technical convenience, we consider a slight alternative for the semantics of the logics Open image in new window and Open image in new window , which does not modify the notion of satisfiability/validity and such that the set of formulae and the definition of the satisfaction relation \(\models \) remain unchanged. So far, the memory states are pairs of the form \((s,h)\) with \(s: \mathrm PVAR\rightarrow \mathrm{LOC}\) and \(h: \mathrm{LOC}\rightarrow _{\text {fin}} \mathrm{LOC}\) for a fixed countably infinite set of locations \(\mathrm{LOC}\), say \(\mathrm{LOC}= \mathbb {N}\). Alternatively, the models for Open image in new window and Open image in new window can be defined as triples \((\mathrm{LOC}_1,s_1,h_1)\) such that \(\mathrm{LOC}_1\) is a countable infinite set, \(s_1: \mathrm PVAR\rightarrow \mathrm{LOC}_1\) and \(h_1: \mathrm{LOC}_1 \rightarrow _{\text {fin}} \mathrm{LOC}_1\). As shown below, this does not change the notion of satisfiability and validity, but this generalisation will be handy in a few places. Most of the time, a generalised memory state \((\mathrm{LOC}_1,s_1,h_1)\) shall be written \((s_1,h_1)\) when no confusion is possible.
Given a bijection \(\mathfrak {f}: \mathrm{LOC}_1 \rightarrow \mathrm{LOC}_2\) and a heap \(h_1: \mathrm{LOC}_1 \rightarrow _{\text {fin}} \mathrm{LOC}_1\) equal to \(\{ \ell _1 \mapsto h_1(\ell _1), \ldots ,\ell _n \mapsto h_1(\ell _n) \}\), we write \(\mathfrak {f}(h_1)\) to denote the heap \(h_2: \mathrm{LOC}_2 \rightarrow _{\text {fin}} \mathrm{LOC}_2\) with \(h_2 = \{ \mathfrak {f}(\ell _1) \mapsto \mathfrak {f}(h_1(\ell _1)), \ldots , \mathfrak {f}(\ell _n) \mapsto \mathfrak {f}(h_1(\ell _n)) \}\).
Definition 1
Let \((\mathrm{LOC}_1,s_1,h_1)\) and \((\mathrm{LOC}_2,s_2,h_2)\) be generalised memory states and \(X\subseteq \mathrm PVAR\). A partial isomorphism with respect to \(X\) from \((\mathrm{LOC}_1,s_1,h_1)\) to \((\mathrm{LOC}_2,s_2,h_2)\) is a bijection \(\mathfrak {f}: \mathrm{LOC}_1 \rightarrow \mathrm{LOC}_2\) such that \(h_2 = \mathfrak {f}(h_1)\) and for all \(\mathtt {x}\in X\), \(\mathfrak {f}(s_1(\mathtt {x})) = s_2(\mathtt {x})\) (we write \((\mathrm{LOC}_1,s_1,h_1) \approx _{X} (\mathrm{LOC}_2,s_2,h_2)\)).
A folklore result states that isomorphic memory states satisfy the same formulae since the logics Open image in new window , Open image in new window can only perform equality tests.
Lemma 1
Let \((\mathrm{LOC}_1,s_1,h_1)\) and \((\mathrm{LOC}_2,s_2,h_2)\) be two generalised memory states such that \((\mathrm{LOC}_1,s_1,h_1) \approx _{X} (\mathrm{LOC}_2,s_2,h_2)\), for some \(X\subseteq \mathrm PVAR\). (I) For all formulae \(\varphi \) in Open image in new window whose free variables are among \(X\), we have \((\mathrm{LOC}_1,s_1,h_1) \models \varphi \) iff \((\mathrm{LOC}_2,s_2,h_2) \models \varphi \). (II) For all formulae \(\varphi \) in Open image in new window built on variables among \(X\), we have \((\mathrm{LOC}_1,s_1,h_1)\models \varphi \) iff \({(\mathrm{LOC}_2,s_2,h_2) \models \varphi }\).
As a direct consequence, satisfiability in Open image in new window as defined in Sect. 2, is equivalent to satisfiability with generalised memory states, the same holds for Open image in new window . Next, we define the encoding of a generalised memory state. This can be seen as the semantical counterpart of the syntactical translation process and, as such, formalise the intuition of using part of a heap to mimic the store.
Definition 2

\(\mathrm{LOC}_1=\mathrm{LOC}_2\setminus \{ s_2(\mathtt {x})\mid \mathtt {x}\in X \}\),

for all \(\mathtt {x}\ne \mathtt {y}\in X\), \(s_2(\mathtt {x})\ne s_2(\mathtt {y})\),

\(h_2=h_1 + \{ s_2(\mathtt {x})\mapsto s_1(\mathtt {x})\mid \mathtt {x}\in Y \}\).
3.2 The Translation
We are now ready to define the translation of a firstorder formula in propositional separation logic extended with the three predicates introduced at the beginning of the section. Let \(\varphi \) be a closed formula of Open image in new window with quantified variables \(\{\mathtt {x}_1,\dots ,\mathtt {x}_q\}\). W.l.o.g., we can assume that distinct quantifications involve distinct variables. Moreover, let \(X= \{\mathtt {x}_1,\dots ,\mathtt {x}_{2q}\}\) and \(\overline{(.)}\) be the involution on \(X\) such that for all \(i \in [1,q]\) Open image in new window .
Here is the main result of this section, which is essential for the correctness of \(\mathcal {T}_\mathrm{SAT}(\varphi )\), defined below.
Lemma 2
Let \(X= \{ \mathtt {x}_1, \ldots , \mathtt {x}_{2q} \}\), \(Y\subseteq \{\mathtt {x}_1, \ldots , \mathtt {x}_q\}\), \(\psi \) be a formula in Open image in new window with free variables among \(Y\) that does not contain any bound variable of \(\psi \) and \((\mathrm{LOC}_1,s_1,h_1) \rhd _q^{Y} \ (\mathrm{LOC}_2,s_2,h_2)\). We have \((s_1,h_1) \models \psi \) iff \((s_2,h_2) \models \mathrm {T}(\psi ,X)\).
Corollary 1
Let \(\varphi \) be a closed formula in Open image in new window using quantified variables among \(\{ \mathtt {x}_1, \ldots , \mathtt {x}_q \}\). (I) \(\varphi \) and \(\mathcal {T}_\mathrm{SAT}(\varphi )\) are equisatisfiable. (II) \(\varphi \) and \(\mathcal {T}_\mathrm{VAL}(\varphi )\) are equivalid.
3.3 Expressing the Auxiliary Atomic Predicates
To complete the reduction, we briefly explain how to express the formulae \(\mathtt {alloc}^{1}(\mathtt {x})\), \(n(\mathtt {x}) = n(\mathtt {y})\) and \(n(\mathtt {x}) \hookrightarrow n(\mathtt {y})\) within Open image in new window . Let us introduce a few macros that shall be helpful.

Given \(\varphi \) in Open image in new window and \(\gamma \ge 0\), we write \([\varphi ]_{\gamma }\) to denote the formula \({(\mathtt {size}= \gamma \wedge \varphi ) *\top }\). It is easy to show that for any memory state \((s,h)\), \((s,h) \models [\varphi ]_{\gamma }\) iff there is \(h' \sqsubseteq h\) such that \(\mathrm{card}(\mathrm{dom}(h')) = \gamma \) and \((s,h') \models \varphi \).

We write \(\mathtt {reach}(\mathtt {x},\mathtt {y}) = \gamma \) to denote the formula \([\mathtt {ls}(\mathtt {x},\mathtt {y})]_{\gamma }\), which is satisfied in any memory state \((s,h)\) where \(h^\gamma (s(\mathtt {x})) = s(\mathtt {y})\). Lastly, we write \(\mathtt {reach}(\mathtt {x},\mathtt {y}) \le \gamma \) to denote the formula \(\bigvee _{0 \le \gamma ' \le \gamma } \mathtt {reach}(\mathtt {x},\mathtt {y}) = \gamma '\).
Lemma 3
Let \(\mathtt {x},\mathtt {y}\in \mathrm PVAR\). (I) For all memory states \((s,h)\) such that \(s(\mathtt {x}) \ne s(\mathtt {y})\), we have \((s,h) \models \mathtt {alloc}_{\mathtt {y}}^{1}(\mathtt {x})\) iff \(s(\mathtt {x}) \in \mathrm{ran}(h)\). (II) In the translation, \(\mathtt {alloc}^{1}(\mathtt {x})\) can be replaced with \(\mathtt {alloc}_{\overline{\mathtt {x}}}^{1}(\mathtt {x})\).
As stated in Lemma 3(II), we can exploit the fact that in the translation of a formula with variables in \(\{ \mathtt {x}_1,\dots ,\mathtt {x}_q \}\), we use 2q variables that correspond to 2q distinguished locations in the heap in order to retain the soundness of the translation while using \(\mathtt {alloc}_{\overline{\mathtt {x}}}^{1}(\mathtt {x})\) as \(\mathtt {alloc}^{1}(\mathtt {x})\). Moreover, \(\mathtt {alloc}_{\mathtt {y}}^{1}(\mathtt {x})\) allows to express in Open image in new window whenever a location corresponding to a program variable reaches itself in exactly two steps (we use this property in the definition of \(n(\mathtt {x}) \hookrightarrow n(\mathtt {y})\)). We write \(\mathtt {x}\hookrightarrow _\mathtt {y}^2 \mathtt {x}\) to denote the formula Open image in new window . For any memory state \((s,h)\) such that \(s(\mathtt {x}) \ne s(\mathtt {y})\), we have \((s,h) \models \mathtt {x}\hookrightarrow _\mathtt {y}^2 \mathtt {x}\) if and only if \(h^2(s(\mathtt {x})) = s(\mathtt {x})\) and \(h(s(\mathtt {x})) \ne s(\mathtt {x})\).
Lemma 4
Let \(\mathtt {x},\mathtt {y}\in \mathrm PVAR\). For all memory states \((s,h)\), we have \((s,h) \models n(\mathtt {x}) = n(\mathtt {y})\) iff \(h(s(\mathtt {x})) = h(s(\mathtt {y}))\).
Lemma 5
Let \(\mathtt {x}, \mathtt {y}, \mathtt {z}\in \mathrm PVAR\). (I) For all memory states \((s,h)\) such that \({s(\mathtt {x}) \ne s(\mathtt {z})}\) and \(s(\mathtt {y}) \ne s(\mathtt {z})\), we have \((s,h) \models \varphi _{\hookrightarrow }(\mathtt {x},\mathtt {y}, \mathtt {z})\) iff \(\{s(\mathtt {x}),s(\mathtt {y})\} \subseteq \mathrm{dom}(h)\) and \(h(h(s(\mathtt {x}))) = h(s(\mathtt {y}))\); (II) In the translation, \(n(\mathtt {x}) \hookrightarrow n(\mathtt {y})\) can be replaced by \(\varphi _{\hookrightarrow }(\mathtt {x},\mathtt {y},\overline{\mathtt {x}})\).
As for \(\mathtt {alloc}_{\mathtt {y}}^{1}(\mathtt {x})\), the properties of the translation imply the equivalence between \(n(\mathtt {x}) \hookrightarrow n(\mathtt {y})\) and \(\varphi _{\hookrightarrow }(\mathtt {x},\mathtt {y},\overline{\mathtt {x}})\) (as stated in Lemma 5(II)). By looking at the formulae herein defined, the predicate \(\mathtt {reach}\) only appears bounded, i.e. in the form of \(\mathtt {reach}(\mathtt {x},\mathtt {y}) = 2\) and \(\mathtt {reach}(\mathtt {x},\mathtt {y})=3\). The three new predicates can therefore be defined in Open image in new window enriched with \(\mathtt {reach}(\mathtt {x},\mathtt {y}) = 2\) and \(\mathtt {reach}(\mathtt {x},\mathtt {y}) = 3\).
3.4 Undecidability Results and Nonfinite Axiomatization
It is time to collect the fruits of all our efforts and to conclude this part about undecidability. As a direct consequence of Corollary 1 and the undecidability of Open image in new window , here is one of the main results of the paper.
Theorem 1
The satisfiability problem for Open image in new window is undecidable.
As a byproduct, the set of valid formulae for Open image in new window is not recursively enumerable. Indeed, suppose that the set of valid formulae for Open image in new window were r.e., then one can enumerate the valid formulae of the form \(\mathcal {T}_\mathrm{VAL}(\varphi )\) as it is decidable in PTime whether \(\psi \) in Open image in new window is syntactically equal to \(\mathcal {T}_\mathrm{VAL}(\varphi )\) for some Open image in new window formula \(\varphi \). This leads to a contradiction since this would allow the enumeration of valid formulae in Open image in new window .
The essential ingredients to establish the undecidability of Open image in new window are the fact that the following properties \(n(\mathtt {x}) = n(\mathtt {y})\), \(n(\mathtt {x}) \hookrightarrow n(\mathtt {y})\) and \(\mathtt {alloc}^{1}(\mathtt {x})\) are expressible in the logic.
Corollary 2
Open image in new window augmented with builtin formulae of the form \(n(\mathtt {x}) = n(\mathtt {y})\), \(n(\mathtt {x}) \hookrightarrow n(\mathtt {y})\) and \(\mathtt {alloc}^{1}(\mathtt {x})\) (resp. of the form \(\mathtt {reach}(\mathtt {x},\mathtt {y}) = 2\) and \(\mathtt {reach}(\mathtt {x},\mathtt {y}) = 3\)) admits an undecidable satisfiability problem.
This is the addition of \(\mathtt {reach}(\mathtt {x},\mathtt {y}) = 3\) that is crucial for undecidability since the satisfiability problem for Open image in new window is in PSpace [15]. Following a similar analysis, let SL1( Open image in new window ) be the restriction of Open image in new window (i.e. Open image in new window plus \(*\)) to formulae of the form \( \exists \mathtt {x}_1 \ \cdots \ \exists \mathtt {x}_q \ \varphi \), where \(q \ge 1\), the variables in \(\varphi \) are among \(\{ \mathtt {x}_1, \ldots , \mathtt {x}_{q+1} \}\) and the only quantified variable in \(\varphi \) is \(\mathtt {x}_{q+1}\). The satisfiability problem for SL1( Open image in new window ) is PSpacecomplete [15]. Note that SL1( Open image in new window ) can easily express \(n(\mathtt {x}) = n(\mathtt {y})\) and \(\mathtt {alloc}^{1}(\mathtt {x})\). The distance between the decidability for SL1( Open image in new window ) and the undecidability for Open image in new window , is best witnessed by the corollary below, which solves an open problem [15, Sect. 6].
Corollary 3
SL1( Open image in new window ) augmented with \(n(\mathtt {x}) \hookrightarrow n(\mathtt {y})\) (resp. SL1( Open image in new window ) augmented with \(\mathtt {ls}\)) admits an undecidable satisfiability problem.
4 \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}})\) and Other PSpace Variants
As already seen in Sect. 2, \(\mathrm {SL}(*, \mathtt {ls})\) can be understood as a fragment of \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}})\). Below, we show that the satisfiability problem for \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}})\) can be solved in polynomial space. Refining the arguments used in our proof, we also show the decidability of the fragment of Open image in new window where \(\mathtt {reach}^{\scriptscriptstyle {+}}\) is constrained not to occur in the scope of Open image in new window , i.e. \(\varphi \) belongs to that fragment iff for any subformula \(\psi \) of \(\varphi \) of the form Open image in new window , \(\mathtt {reach}^{\scriptscriptstyle {+}}\) does not occur in \(\psi _1\) and in \(\psi _2\).
The proof relies on a small heap property: a formula \(\varphi \) is satisfiable if and only if it admits a model with a polynomial amount of memory cells. The PSpace upper bound then follows by establishing that the modelchecking problem for \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}})\) is in PSpace too. To establish the small heap property, an equivalence relation on memory states with finite index is designed, following the standard approach in [10, 32] and using test formulae as in [4, 15, 22, 23].
4.1 Introduction to Test Formulae
Before presenting the test formulae for \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}})\), let us recall the standard result for Open image in new window (that will be also used at some point later on).
Proposition 2
[22, 32] Any formula \(\varphi \) in Open image in new window built over variables in \(\mathtt {x}_1\), ...,\(\mathtt {x}_q\) is logically equivalent to a Boolean combination of formulae among \({\mathtt {x}_i\! =\!\mathtt {x}_j}\), \(\mathtt {alloc}(\mathtt {x}_i)\), Open image in new window and \({\mathtt {size}\ge \beta }\) (\(i,j \in \{ 1,\ldots ,q \}\), \(\beta \in \mathbb {N}\)).
By way of example, Open image in new window is equivalent to \({\mathtt {size}\ge 2} \wedge \mathtt {alloc}(\mathtt {x}_1)\). As a corollary of the proof of Proposition 2, in \(\mathtt {size}\ge \beta \) we can enforce that \(\beta \le 2 \times \varphi \) (rough upper bound) where \(\varphi \) is the size of \(\varphi \). Similar results will be shown for \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}})\) and for some of its extensions.
The fragment memory states \((s_1,h_1)\) and \((s_2,h_2)\) can be distinguished by the formula \(\top *(\mathtt {reach}(\mathtt {x}_i,\mathtt {x}_j) \wedge \mathtt {reach}(\mathtt {x}_j,\mathtt {x}_k) \wedge \lnot \mathtt {reach}(\mathtt {x}_k,\mathtt {x}_i))\). Indeed, \((s_1,h_1)\) satisfies this formula by considering a subheap that does not contain a path from \(s(\mathtt {x}_k)\) to \(s(\mathtt {x}_i)\), whereas it is impossible to find a subheap for \((s_2,h_2)\) that retains the path from \(s(\mathtt {x}_i)\) to \(s(\mathtt {x}_j)\), the one from \(s(\mathtt {x}_j)\) to \(s(\mathtt {x}_k)\) but where the path from \(s(\mathtt {x}_k)\) to \(s(\mathtt {x}_i)\) is lost. This suggests that \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}})\) can express whether, for example, any path from \(s(\mathtt {x}_i)\) to \(s(\mathtt {x}_j)\) also contains \(s(\mathtt {x}_k)\). We will introduce the test formula \(\mathtt {sees}_q(\mathtt {x}_i,\mathtt {x}_j) \ge \beta \) to capture this property.
Similarly, the memory states \((s_3,h_3)\) and \((s_4,h_4)\) can be distinguished by the formula \((\mathtt {size}= 1) *\big (\mathtt {reach}(\mathtt {x}_j,\mathtt {x}_k) \wedge \lnot \mathtt {reach}(\mathtt {x}_i,\mathtt {x}_k) \wedge \lnot \mathtt {reach}^+(\mathtt {x}_k,\mathtt {x}_k)\big )\). The memory state \((s_3,h_3)\) satisfies this formula by separating \(\{ \ell \mapsto \ell '\}\) from the rest of the heap, whereas the formula is not satisfied by \((s_4,h_4)\). Indeed, there is no way to break the loop from \(s(\mathtt {x}_k)\) to itself by removing just one location from the heap while retaining the path from \(s(\mathtt {x}_j)\) to \(s(\mathtt {x}_k)\) and loosing the path from \(s(\mathtt {x}_i)\) to \(s(\mathtt {x}_k)\). This suggests that the two locations \(\ell \) and \(\ell '\) are particularly interesting since they are reachable from several locations corresponding to program variables. Therefore by separating them from the rest of the heap, several paths are lost. In order to capture this, we introduce the notion of meetpoints.

there are \(L_1, L_2\ge 0\) such that \(h^{L_1}(s(\mathtt {x}_i)) = h^{L_2}(s(\mathtt {x}_j)) = \ell \), and

for all \(L_1' < L_1\) and for all \(L_2'\ge 0\), \(h^{L_1'}\big (s(\mathtt {x}_i)\big ) \not = h^{L_2'}\big (s(\mathtt {x}_j)\big )\), and

there exist \(k \in [1,q]\) and \(L\ge 0\) such that \(h^L(\ell ) = s(\mathtt {x}_k)\).
Notice how the asymmetrical definition of meetpoints is captured in the two rightmost heaps. Consider the memory states from Fig. 1, \((s_3,h_3)\) and \((s_4,h_4)\) can be seen as an instance of the third case of the taxonomy and, as such, it holds that \([\![m_q(\mathtt {x}_i,\mathtt {x}_j)]\!]^q_{s_3,h_3} = \ell \) and \([\![m_q(\mathtt {x}_j,\mathtt {x}_i)]\!]^q_{s_3,h_3} = \ell '\).
Lemma 6
Given \(\alpha , q \ge 1\), \(i,j \in [1,q]\), for any atomic formula among \(\mathtt {ls}(\mathtt {x}_i, \mathtt {x}_j)\), \(\mathtt {reach}(\mathtt {x}_i, \mathtt {x}_j)\), \(\mathtt {reach}^{\scriptscriptstyle {+}}(\mathtt {x}_i, \mathtt {x}_j)\), \(\mathtt {emp}\) and \(\mathtt {size}\ge \beta \) with \(\beta \le \alpha \), there is a Boolean combination of test formulae from \(\text {Test}(q, \alpha )\) logically equivalent to it.
4.2 Expressive Power and Small Model Property
The sets of test formulae \(\text {Test}(q,\alpha )\) are sufficient to capture the expressive power of \(\mathrm {SL}(*,\mathtt {reach}^{\scriptscriptstyle {+}})\) (as shown below, Theorem 2) and deduce the small heap property of this logic (Theorem 3). We introduce an indistinguishability relation between memory states based on test formulae, see analogous relations in [13, 15, 22].
Definition 3
Given \(q,\alpha \ge 1\), we write \((s,h) \approx _\alpha ^q (s',h')\) Open image in new window for all \(\psi \in \text {Test}(q,\alpha )\), we have \((s,h) \models \psi \) iff \((s',h') \models \psi \).
Theorem 2(I) states that if \((s,h) \approx _\alpha ^q (s',h')\), then the two memory states cannot be distinguished by formulae whose syntactic resources are bounded in some way by q and \(\alpha \) (details will follow, see the definition for \(\texttt {msize}(\varphi )\)).
Below, we state the key intermediate result of the section that can be viewed as a distributivity lemma. The expressive power of the test formulae allows us to mimic the separation between two equivalent memory states with respect to the relation \(\approx ^q_\alpha \), which is essential in the proof of Theorem 2(I).
Lemma 7
Let \(q,\alpha ,\alpha _1,\alpha _2 \ge 1\) with \(\alpha = \alpha _1 + \alpha _2\) and \((s,h)\), \((s',h')\) be such that \((s,h) \approx ^q_\alpha (s',h')\). For all heaps \(h_1\), \(h_2\) such that \(h= h_1 + h_2\) there are heaps \(h'_1\), \(h'_2\) such that \(h= h'_1 + h'_2\), \((s,h_1) \approx ^q_{\alpha _1} (s',h'_1)\) and \((s,h_2) \approx ^q_{\alpha _2} (s',h'_2)\).
Theorem 2
Let \(\varphi \) be in \(\mathrm {SL}(*,\mathtt {reach}^{\scriptscriptstyle {+}})\) built over the variables in \(\mathtt {x}_1\), ..., \(\mathtt {x}_q\). (I) For all \(\alpha \ge 1\) such that \(\texttt {msize}(\varphi ) \le \alpha \) and for all memory states \((s,h)\), \((s',h') \) such that \((s,h) \approx ^q_\alpha (s',h')\), we have \((s,h) \models \varphi \) iff \((s',h') \models \varphi \). (II) \(\varphi \) is logically equivalent to a Boolean combination of test formulae from \(\text {Test}(q,\texttt {msize}(\varphi ))\).
The proof of Theorem 2(I) is by structural induction on \(\varphi \). The basic cases for atomic formulae follow from Lemma 6 whereas the inductive cases for Boolean connectives are immediate. For the separating conjunction, suppose \((s,h) \models \varphi _1 *\varphi _2\) and \(\texttt {msize}(\varphi _1*\varphi _2) \le \alpha \). There are heaps \(h_1\) and \(h_2\) such that \(h= h_1 + h_2\), \((s,h_1) \models \psi _1\) and \((s,h_2) \models \psi _2\). As \(\alpha \ge \texttt {msize}(\psi _1 *\psi _2) = \texttt {msize}(\psi _1) + \texttt {msize}(\psi _2)\), there exist \(\alpha _1\) and \(\alpha _2\) such that \(\alpha = \alpha _1 + \alpha _2\), \(\alpha _1 \ge \texttt {msize}(\psi _1)\) and \(\alpha _2 \ge \texttt {msize}(\psi _2)\). By Lemma 7, there exist heaps \(h'_1\) and \(h'_2\) such that \(h'=h'_1 + h'_2\), \((s,h_1) \approx ^q_{\alpha _1} (s',h'_1)\) and \((s,h_2) \approx ^q_{\alpha _2} (s',h'_2)\). By the induction hypothesis, we get \((s',h_1') \models \psi _1\) and \((s',h_2') \models \psi _2\). Consequently, we obtain \((s',h') \models \psi _1 *\psi _2\).
As an example, we can apply this result to the memory states from Fig. 1. We have already shown how we can distinguish \((s_1,h_1)\) from \((s_2,h_2)\) using a formula with only one separating conjunction. Theorem 2 ensures that these two memory states do not satisfy the same set of test formulae for \(\alpha \ge 2\). Indeed, only \((s_1,h_1)\) satisfies \(\mathtt {sees}_q(\mathtt {x}_i,\mathtt {x}_j) \ge 2\). The same argument can be used with \((s_3,h_3)\) and \((s_4,h_4)\): only \((s_3,h_3)\) satisfies the test formula \(m_q(\mathtt {x}_i,\mathtt {x}_j) \hookrightarrow m_q(\mathtt {x}_j,\mathtt {x}_i)\). Clearly, Theorem 2(II) relates separation logic with classical logic as advocated also in the works [10, 23]. Now, it is possible to establish a small heap property.
Theorem 3
Let \(\varphi \) be a satisfiable \(\mathrm {SL}(*,\mathtt {reach}^{\scriptscriptstyle {+}})\) formula built over \(\mathtt {x}_1\), ..., \(\mathtt {x}_q\). There is \((s,h)\) such that \((s,h) \models \varphi \) and \(\mathrm{card}(\mathrm{dom}(h)) \le (q^2 + q) \cdot (\varphi  + 1) + \varphi \).
The small heap property for \(\mathrm {SL}(*,\mathtt {reach}^{\scriptscriptstyle {+}})\) is inherited from the small heap property for the Boolean combinations of test formulae, which is analogous to the small model property for other theories of singly linked lists, see e.g. [13, 27].
4.3 Complexity Upper Bounds
Let us draw some consequences of Theorem 3. First, for the logic \(\mathrm {SL}(*,\mathtt {reach}^{\scriptscriptstyle {+}})\), we get a PSpace upper, which matches the lower bound for \(\mathrm {SL}(*)\) [11].
Theorem 4
The satisfiability problem for \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}})\) is PSpacecomplete.
Besides, we may consider restricting the usage of Boolean connectives. We note \(\mathsf {Bool(SHF)}\) for the Boolean combinations of formulae from the symbolic heap fragment [2]. A PTime upper bound for the entailment/satisfiability problem for the symbolic heap fragment is successfully solved in [12, 17], whereas the satisfiability problem for a slight variant of \(\mathsf {Bool(SHF)}\) is shown in NP in [26, Theorem 4]. Theorem 3 allows us to conclude this NP upper bound result as a byproduct (we conjecture that our quadratic upper bound on the number of cells could be improved to a linear one in that case).
Corollary 4
The satisfiability problem for \(\mathsf {Bool(SHF)}\) is NPcomplete.
It is possible to push further the PSpace upper bound by allowing occurrences of Open image in new window in a controlled way. Let \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}}, \bigcup _{q,\alpha } \text {Test}(q,\alpha ))\) be the extension of \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}})\) augmented with the test formulae. The memory size function is also extended: Open image in new window , Open image in new window , Open image in new window and Open image in new window . When formulae are encoded as trees, we have \(1 \le \texttt {msize}(\varphi ) \le \varphi  \alpha _{\varphi }\) where \(\alpha _{\varphi }\) is the maximal constant in \(\varphi \). Theorem 2(I) admits a counterpart for \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}}, \bigcup _{q,\alpha } \text {Test}(q,\alpha ))\) and consequently, any formula built over \(\mathtt {x}_1\), ..., \(\mathtt {x}_q\) can be shown equivalent to a Boolean combination of test formulae from \(\text {Test}(q, \varphi  \alpha _{\varphi })\). By Theorem 3, any satisfiable formula has therefore a model with \( \mathrm{card}(\mathrm{dom}(h)) \le (q^2 + q)\cdot (\varphi  \alpha _{\varphi } + 1) + \varphi  \alpha _{\varphi }\). Hence, the satisfiability problem for \(\mathrm {SL}(*, \mathtt {reach}^{\scriptscriptstyle {+}}, \bigcup _{q,\alpha } \text {Test}(q,\alpha ))\) is in PSpace when the constants are encoded in unary. Now, we can state the new PSpace upper bound for Boolean combinations of formulae from Open image in new window .
Theorem 5
The satisfiability problem for Boolean combinations of formulae from Open image in new window is PSpacecomplete.
To conclude, let us introduce the largest fragment including Open image in new window and \(\mathtt {ls}\) for which decidability can be established so far.
Theorem 6
The satisfiability problem for the fragment of Open image in new window in which \(\mathtt {reach}^{\scriptscriptstyle {+}}\) is not in the scope of Open image in new window is decidable.
5 Conclusion
We studied the effects of adding \(\mathtt {ls}\) to Open image in new window and variants. Open image in new window is shown undecidable (Theorem 1) and nonfinitely axiomatisable, which remains quite unexpected since there are no firstorder quantifications. This result is strengthened to even weaker extensions of Open image in new window such as the one augmented with \(n(\mathtt {x}) = n(\mathtt {y})\), \(n(\mathtt {x}) \hookrightarrow n(\mathtt {y})\) and \(\mathtt {alloc}^{1}(\mathtt {x})\), or the one augmented with \(\mathtt {reach}(\mathtt {x},\mathtt {y}) = 2\) and \(\mathtt {reach}(\mathtt {x},\mathtt {y}) = 3\). If the magic wand is discarded, we have established that the satisfiability problem for \(\mathrm {SL}(*,\mathtt {ls})\) is PSpacecomplete by introducing a class of test formulae that captures the expressive power of \(\mathrm {SL}(*,\mathtt {ls})\) and that leads to a small heap property. Such a logic contains the Boolean combinations of symbolic heaps and our proof technique allows us to get an NP upper bound for such formulae. Moreover, we show that the satisfiability problem for Open image in new window restricted to formulae in which \(\mathtt {reach}^{\scriptscriptstyle {+}}\) is not in the scope of Open image in new window is decidable, leading to the largest known decidable fragment for which Open image in new window and \(\mathtt {reach}^{\scriptscriptstyle {+}}\) (or \(\mathtt {ls}\)) cohabit. So, we have provided proof techniques to establish undecidability when \(*\), Open image in new window and \(\mathtt {ls}\) are present and to establish decidability based on test formulae. This paves the way to investigate the decidability status of Open image in new window as well as of the positive fragment of Open image in new window from [30, 31].
References
 1.Antonopoulos, T., Gorogiannis, N., Haase, C., Kanovich, M., Ouaknine, J.: Foundations for decision problems in separation logic with general inductive predicates. In: Muscholl, A. (ed.) FoSSaCS 2014. LNCS, vol. 8412, pp. 411–425. Springer, Heidelberg (2014). https://doi.org/10.1007/9783642548307_27CrossRefzbMATHGoogle Scholar
 2.Berdine, J., Calcagno, C., O’Hearn, P.W.: A decidable fragment of separation logic. In: Lodaya, K., Mahajan, M. (eds.) FSTTCS 2004. LNCS, vol. 3328, pp. 97–109. Springer, Heidelberg (2004). https://doi.org/10.1007/9783540305385_9CrossRefzbMATHGoogle Scholar
 3.Berdine, J., Calcagno, C., O’Hearn, P.W.: Smallfoot: modular automatic assertion checking with separation logic. In: de Boer, F.S., Bonsangue, M.M., Graf, S., de Roever, W.P. (eds.) FMCO 2005. LNCS, vol. 4111, pp. 115–137. Springer, Heidelberg (2006). https://doi.org/10.1007/11804192_6CrossRefGoogle Scholar
 4.Brochenin, R., Demri, S., Lozes, E.: Reasoning about sequences of memory states. APAL 161(3), 305–323 (2009)MathSciNetzbMATHGoogle Scholar
 5.Brochenin, R., Demri, S., Lozes, E.: On the almighty wand. IC 211, 106–137 (2012)MathSciNetzbMATHGoogle Scholar
 6.Brotherston, J., Fuhs, C., Gorogiannis, N., Navarro Perez, J.: A decision procedure for satisfiability in separation logic with inductive predicates. In: CSLLICS 2014 (2014)Google Scholar
 7.Brotherston, J., Villard, J.: Parametric completeness for separation theories. In: POPL 2014, pp. 453–464. ACM (2014)Google Scholar
 8.Calcagno, C., Distefano, D.: Infer: an automatic program verifier for memory safety of C programs. In: Bobaru, M., Havelund, K., Holzmann, G.J., Joshi, R. (eds.) NFM 2011. LNCS, vol. 6617, pp. 459–465. Springer, Heidelberg (2011). https://doi.org/10.1007/9783642203985_33CrossRefGoogle Scholar
 9.Calcagno, C., Distefano, D., O’Hearn, P., Yang, H.: Compositional shape analysis by means of biabduction. JACM 58(6), 26:1–26:66 (2011)MathSciNetCrossRefGoogle Scholar
 10.Calcagno, C., Gardner, P., Hague, M.: From separation logic to firstorder logic. In: Sassone, V. (ed.) FoSSaCS 2005. LNCS, vol. 3441, pp. 395–409. Springer, Heidelberg (2005). https://doi.org/10.1007/9783540319825_25CrossRefGoogle Scholar
 11.Calcagno, C., Yang, H., O’Hearn, P.W.: Computability and complexity results for a spatial assertion language for data structures. In: Hariharan, R., Vinay, V., Mukund, M. (eds.) FSTTCS 2001. LNCS, vol. 2245, pp. 108–119. Springer, Heidelberg (2001). https://doi.org/10.1007/354045294X_10CrossRefGoogle Scholar
 12.Cook, B., Haase, C., Ouaknine, J., Parkinson, M., Worrell, J.: Tractable reasoning in a fragment of separation logic. In: Katoen, J.P., König, B. (eds.) CONCUR 2011. LNCS, vol. 6901, pp. 235–249. Springer, Heidelberg (2011). https://doi.org/10.1007/9783642232176_16CrossRefGoogle Scholar
 13.David, C., Kroening, D., Lewis, M.: Propositional reasoning about safety and termination of heapmanipulating programs. In: Vitek, J. (ed.) ESOP 2015. LNCS, vol. 9032, pp. 661–684. Springer, Heidelberg (2015). https://doi.org/10.1007/9783662466698_27CrossRefzbMATHGoogle Scholar
 14.Demri, S., Deters, M.: Expressive completeness of separation logic with two variables and no separating conjunction. ACM ToCL 17(2), 12 (2016)MathSciNetCrossRefGoogle Scholar
 15.Demri, S., Galmiche, D., LarcheyWendling, D., Mery, D.: Separation logic with one quantified variable. Theory Comput. Syst. 61, 371–461 (2017)MathSciNetCrossRefGoogle Scholar
 16.Distefano, D., O’Hearn, P.W., Yang, H.: A local shape analysis based on separation logic. In: Hermanns, H., Palsberg, J. (eds.) TACAS 2006. LNCS, vol. 3920, pp. 287–302. Springer, Heidelberg (2006). https://doi.org/10.1007/11691372_19CrossRefzbMATHGoogle Scholar
 17.Haase, C., Ishtiaq, S., Ouaknine, J., Parkinson, M.J.: SeLoger: a tool for graphbased reasoning in separation logic. In: Sharygina, N., Veith, H. (eds.) CAV 2013. LNCS, vol. 8044, pp. 790–795. Springer, Heidelberg (2013). https://doi.org/10.1007/9783642397998_55CrossRefGoogle Scholar
 18.Hóu, Z., Goré, R., Tiu, A.: Automated theorem proving for assertions in separation logic with all connectives. In: Felty, A.P., Middeldorp, A. (eds.) CADE 2015. LNCS (LNAI), vol. 9195, pp. 501–516. Springer, Cham (2015). https://doi.org/10.1007/9783319214016_34CrossRefzbMATHGoogle Scholar
 19.Iosif, R., Rogalewicz, A., Simacek, J.: The tree width of separation logic with recursive definitions. In: Bonacina, M.P. (ed.) CADE 2013. LNCS (LNAI), vol. 7898, pp. 21–38. Springer, Heidelberg (2013). https://doi.org/10.1007/9783642385742_2CrossRefGoogle Scholar
 20.Ishtiaq, S., O’Hearn, P.: BI as an assertion language for mutable data structures. In: POPL 2001, pp. 14–26. ACM (2001)CrossRefGoogle Scholar
 21.Le, Q.L., Tatsuta, M., Sun, J., Chin, W.N.: A decidable fragment in separation logic with inductive predicates and arithmetic. In: Majumdar, R., Kunčak, V. (eds.) CAV 2017. LNCS, vol. 10427, pp. 495–517. Springer, Cham (2017). https://doi.org/10.1007/9783319633909_26CrossRefGoogle Scholar
 22.Lozes, E.: Expressivité des Logiques Spatiales. Ph.D. thesis, ENS Lyon (2004)Google Scholar
 23.Lozes, E.: Separation logic preserves the expressive power of classical logic. In: SPACE 2004 (2004)Google Scholar
 24.Müller, P., Schwerhoff, M., Summers, A.J.: Viper: a verification infrastructure for permissionbased reasoning. In: Jobstmann, B., Leino, K.R.M. (eds.) VMCAI 2016. LNCS, vol. 9583, pp. 41–62. Springer, Heidelberg (2016). https://doi.org/10.1007/9783662491225_2CrossRefzbMATHGoogle Scholar
 25.O’Hearn, P., Reynolds, J., Yang, H.: Local reasoning about programs that alter data structures. In: Fribourg, L. (ed.) CSL 2001. LNCS, vol. 2142, pp. 1–19. Springer, Heidelberg (2001). https://doi.org/10.1007/3540448020_1CrossRefGoogle Scholar
 26.Piskac, R., Wies, T., Zufferey, D.: Automating separation logic using SMT. In: Sharygina, N., Veith, H. (eds.) CAV 2013. LNCS, vol. 8044, pp. 773–789. Springer, Heidelberg (2013). https://doi.org/10.1007/9783642397998_54CrossRefGoogle Scholar
 27.Ranise, S., Zarba, C.: A theory of singlylinked lists and its extensible decision procedure. In: SEFM 2006, pp. 206–215. IEEE (2006)Google Scholar
 28.Reynolds, J.: Separation logic: a logic for shared mutable data structures. In: LICS 2002, pp. 55–74. IEEE (2002)Google Scholar
 29.Schwerhoff, M., Summers, A.: Lightweight support for magic wands in an automatic verifier. In: ECOOP 2015, pp. 999–1023. LeibnizZentrum für Informatik, LIPICS (2015)Google Scholar
 30.Thakur, A.: Symbolic Abstraction: Algorithms and Applications. Ph.D. thesis, University of WisconsinMadison (2014)Google Scholar
 31.Thakur, A., Breck, J., Reps, T.: Satisfiability modulo abstraction for separation logic with linkedlists. In: SPIN 2014, pp. 58–67. ACM (2014)Google Scholar
 32.Yang, H.: Local Reasoning for Stateful Programs. Ph.D. thesis, University of Illinois, UrbanaChampaign (2001)Google Scholar
 33.Yang, H., Lee, O., Berdine, J., Calcagno, C., Cook, B., Distefano, D., O’Hearn, P.: Scalable shape analysis for systems code. In: Gupta, A., Malik, S. (eds.) CAV 2008. LNCS, vol. 5123, pp. 385–398. Springer, Heidelberg (2008). https://doi.org/10.1007/9783540705451_36CrossRefGoogle Scholar
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