We describe a novel method for verifying programs that manipulate linked lists, based on two new predicates that characterize reachability of heap cells. These predicates allow reasoning about both acyclic and cyclic lists uniformly with equal ease. The crucial insight behind our approach is that a circular list invariably contains a distinguished head cell that provides a handle on the list. This observation suggests a programming methodology that requires the heap of the program at each step to be well-founded, i.e., for any field f in the program, every sequence u.f,u.f.f,... contains at least one head cell. We believe that our methodology captures the most common idiom of programming with linked data structures. We enforce our methodology by automatically instrumenting the program with updates to two auxiliary variables representing these predicates and adding assertions in terms of these auxiliary variables. To prove program properties and the instrumented assertions, we provide a first-order axiomatization of our two predicates. We also introduce a novel induction principle made possible by the well-foundedness of the heap. We use our induction principle to derive from two basic axioms a small set of additional first-order axioms that are useful for proving the correctness of several programs. We have implemented our method in a tool and used it to verify the correctness of a variety of nontrivial programs manipulating both acyclic and cyclic singly-linked lists and doubly-linked lists. We also demonstrate the use of indexed predicate abstraction to automatically synthesize loop invariants for these examples.

This dissertation describes an approach for automatically verifying data structures, focusing on techniques for automatically proving formulas that arise in such verification. I have implemented this approach with my colleagues in a verification system called Jahob. Jahob verifies properties of Java programs with dynamically allocated data structures. Developers write Jahob specifications in classical higher-order logic (HOL); Jahob reduces the verification problem to deciding the validity of HOL formulas. I present a new method for proving HOL formulas by combining automated reasoning techniques. My method consists of 1) splitting formulas into individual HOL conjuncts, 2) soundly approximating each HOL conjunct with a formula in a more tractable fragment and 3) proving the resulting approximation using a decision procedure or a theorem prover. I present three concrete logics; for each logic I show how to use it to approximate HOL formulas, and how to decide the validity of formulas in this logic. First, I present an approximation of HOL based on a translation to first-order logic, which enables the use of existing resolution-based theorem provers. Second, I present an approximation of HOL based on field constraint analysis, a new technique that enables

Abstract. We show that the idea of predicates on heap objects can be cast in the framework of predicate abstraction. This leads to an alternative view on the underlying concepts of three-valued shape analysis by Sagiv, Reps and Wilhelm. Our construction of the abstract post operator is analogous to the corresponding construction for classical predicate abstraction, except that predicates over objects on the heap take the place of state predicates, and boolean heaps (sets of bitvectors) take the place of boolean states (bitvectors). A program is abstracted to a program over boolean heaps. For each command of the program, the corresponding abstract command is effectively constructed by deductive reasoning, namely by the application of the weakest precondition operator and an entailment test. We thus obtain a symbolic framework for shape analysis. 1

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Predicate abstraction is a popular abstraction technique employed in formal software verification. A crucial requirement to make predicate abstraction effective is to use as few predicates as possible, since the abstraction process is in the worst case exponential (in both time and memory requirements) in the number of predicates involved. If a property can be proven to hold or not hold based on a given finite set of predicates P, the procedure we propose in this paper finds automatically a minimal subset of P that is sufficient for the proof. We explain how our technique can be used for more efficient verification of C programs. Our experiments show that predicate minimization can result in a significant reduction of both verification time and memory usage compared to earlier methods.

There has been considerable progress in the domain of software veri cation over the last few years. This advancement has been driven, to a large extent, by the emergence of powerful yet automated abstraction techniques like predicate abstraction. However, the state space explosion problem in model checking remains the chief obstacle to the practical veri cation of real-world distributed systems. Even in the case of purely sequential programs, a crucial requirement to make predicate abstraction eective is to use as few predicates as possible. This is because, in the worst case, the state space of the abstraction generated (and consequently the time and memory complexity of the abstraction process) is exponential in the number of predicates involved. In addition, for concurrent programs, the number of reachable states could grow exponentially with the number of components.

Abstract. We present a technique for using infeasible program paths to automatically infer Range Predicates that describe properties of unbounded array segments. First, we build proofs showing the infeasibility of the paths, using axioms that precisely encode the high-level (but informal) rules with which programmers reason about arrays. Next, we mine the proofs for Craig Interpolants which correspond to predicates that refute the particular counterexample path. By embedding the predicate inference technique within a Counterexample-Guided Abstraction-Refinement (CEGAR) loop, we obtain a method for verifying datasensitive safety properties whose precision is tailored in a program- and property-sensitive manner. Though the axioms used are simple, we show that the method suffices to prove a variety of array-manipulating programs that were previously beyond automatic model checkers. 1

Abstract. An important and ubiquitous class of programs are heap-manipulating programs (HMP), which manipulate unbounded linked data structures by following pointers and updating links. Predicate abstraction hasprovedtobeaninvaluable technique in the field of software model checking; this technique relies on an efficient decision procedure for the underlying logic. The expression and proof of many interesting HMP safety properties require transitive closure predicates; such predicates express that some node can be reached from another node by following a sequence of (zero or more) links in the data structure. Unfortunately, adding support for transitive closure often yields undecidability, so one must be careful in defining such a logic. Our primary contributions are the definition of a simple transitive closure logic for use in predicate abstraction of HMPs, and a decision procedure for this logic. Through several experimental examples, we demonstrate that our logic is expressive enough to prove interesting properties with predicate abstraction, and that our decision procedure provides us with both a time and space advantage over previous approaches. 1

Shape analysis is a promising technique for statically verifying and extracting properties of programs that manipulate complex data structures. We introduce a new characterization of constraints that arise in parametric shape analysis based on manipulation of three-valued structures as dataflow facts. We identify an interesting syntactic class of first-order logic formulas that captures the meaning of three-valued structures under concretization. This class is broader than previously introduced classes, allowing for a greater flexibility in the formulation of shape analysis constraints in program annotations and internal analysis representations. Three-valued structures can be viewed as one possible normal form of the formulas in our class. Moreover, we characterize the meaning of three-valued structures under "tight concretization". We show that the seemingly minor change from concretization to tight concretization increases the expressive power of three-valued structures in such a way that the resulting constraints are closed under all boolean operations. We call the resulting constraints boolean shape analysis constraints. The main technical contribution of this paper is a natural syntactic characterization of boolean shape analysis constraints as arbitrary boolean combinations of first-order sentences of certain form, and an algorithm for transforming such boolean combinations into the normal form that corresponds directly to three-valued structures.

The state space explosion problem in model checking remains the chief obstacle to the practical verification of real-world distributed systems. We attempt to address this problem in the context of verifying concurrent (message-passing) C programs against safety specifications. More specifically, we present a fully automated compositional framework which combines two orthogonal abstraction techniques (operating respectively on data and events) within a counterexample-guided abstraction refinement (CEGAR) scheme. In this way, our algorithm incrementally increases the granularity of the abstractions until the specification is either established or refuted. Our explicit use of compositionality delays the onset of state space explosion for as long as possible. To our knowledge, this is the first compositional use of CEGAR in the context of model checking concurrent C programs. We describe our approach in detail, and report on some very encouraging preliminary experimental results obtained with our tool MAGIC.