Automatic Termination Proofs for Programs with Shape-Shifting Heaps

Berdine, Josh; Cook, Byron; Distefano, Dino; O’Hearn, Peter W.

doi:10.1007/11817963_35

Cited by 80 publications

(80 citation statements)

References 18 publications

(33 reference statements)

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“…For pointer systems, qualitative properties (absence of memory violation like invalid pointer dereferencing, memory leak) are difficult to analyze, and may drastically rely on quantitative properties (lists of equal length, finitely increasing memory allocation,...). Some recent works illustrate this relation between quantitative and qualitative aspects in pointer systems for the purpose of verifying termination [7] or safety [11].…”

Section: Introductionmentioning

confidence: 91%

Towards Model-Checking Programs with Lists

Finkel

Lozes

2009

Infinity in Logic and Computation

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Abstract. We aim at checking safety and temporal properties over models representing the behavior of programs manipulating dynamic singly-linked lists. The properties we consider not only allow to perform a classical shape analysis, but we also want to check quantitative aspect on the manipulated memory heap. We first explain how a translation of programs into counter systems can be used to check safety problems and temporal properties. We then study the decidability of these two problems considering some restricted classes of programs, namely flat programs without destructive update. We obtain the following results : (1) the model-checking problem is decidable if the considered program works over acyclic lists (2) the safety problem is decidable for programs without alias test. We finally explain the limit of our decidability results, showing that relaxing one of the hypothesis leads to undecidability results.

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Section: Introductionmentioning

confidence: 91%

Towards Model-Checking Programs with Lists

Finkel

Lozes

2009

Infinity in Logic and Computation

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“…Our analysis conservatively verifies the first requirement in situ. The second requirement can be proved using termination analysis, e.g., [6]. Once the above requirements are established, the soundness of the abstract interpretation follows from the soundness of [5]'s framework for program analysis, in which our analysis is encoded.…”

Section: Soundnessmentioning

confidence: 99%

Comparison Under Abstraction for Verifying Linearizability

Amit

Rinetzky

Reps³

et al.

Computer Aided Verification

115

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Abstract. Linearizability is one of the main correctness criteria for implementations of concurrent data structures. A data structure is linearizable if its operations appear to execute atomically. Verifying linearizability of concurrent unbounded linked data structures is a challenging problem because it requires correlating executions that manipulate (unbounded-size) memory states. We present a static analysis for verifying linearizability of concurrent unbounded linked data structures. The novel aspect of our approach is the ability to prove that two (unboundedsize) memory layouts of two programs are isomorphic in the presence of abstraction. A prototype implementation of the analysis verified the linearizability of several published concurrent data structures implemented by singly-linked lists.

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“…Hence, A is the initial state when calling the method with such an input list. 4 From A, the termination graph in Fig. 4 is constructed by symbolic evaluation.…”

Section: Constructing the Termination Graphmentioning

confidence: 99%

“…Such techniques are for instance used in the tools Terminator [4,12] and LoopFrog [22,31] to analyze termination of C programs. To handle the heap, one can use an abstraction [13] to integers based on separation logic [24].…”

Section: Introductionmentioning

confidence: 99%

“…Up to now, transformational approaches could not deal with such programs. Similar to related approaches based on separation logic [4,5,9,10,28,32], our technique relies on suitable predicates describing properties of the heap. Like [28], but in contrast to several previous works, our technique derives these heap predicates automatically from the input program and it works automatically for arbitrary data structures (i.e., not only for lists).…”

Section: Introductionmentioning

confidence: 99%

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Automated Termination Proofs for Java Programs with Cyclic Data

Brockschmidt

Musiol

Otto

et al. 2012

Computer Aided Verification

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Abstract. In earlier work, we developed a technique to prove termination of Java programs automatically: first, Java programs are automatically transformed to term rewrite systems (TRSs) and then, existing methods and tools are used to prove termination of the resulting TRSs. In this paper, we extend our technique in order to prove termination of algorithms on cyclic data such as cyclic lists or graphs automatically. We implemented our technique in the tool AProVE and performed extensive experiments to evaluate its practical applicability.

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Automatic Termination Proofs for Programs with Shape-Shifting Heaps

Cited by 80 publications

References 18 publications

Towards Model-Checking Programs with Lists

Towards Model-Checking Programs with Lists

Comparison Under Abstraction for Verifying Linearizability

Automated Termination Proofs for Java Programs with Cyclic Data

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