Relational String Abstract Domains

Arceri, Vincenzo; Olliaro, Martina; Cortesi, Agostino; Ferrara, Pietro

doi:10.1007/978-3-030-94583-1_2

Cited by 9 publications

(9 citation statements)

References 35 publications

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“…The affine equalities or affine inequalities domains [16,30], however, are not. The relational string domains recently proposed by Arceri et al [6] in Sec. 5.1 through Sec.…”

Section: Relational Domainsmentioning

confidence: 99%

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Clustered Relational Thread-Modular Abstract Interpretation with Local Traces

Schwarz¹,

Saan²,

Seidl³

et al. 2023

Preprint

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We construct novel thread-modular analyses that track relational information for potentially overlapping clusters of global variables -given that they are protected by common mutexes. We provide a framework to systematically increase the precision of clustered relational analyses by splitting control locations based on abstractions of local traces. As one instance, we obtain an analysis of dynamic thread creation and joining. Interestingly, tracking less relational information for globals may result in higher precision. We consider the class of 2-decomposable domains that encompasses many weakly relational domains (e.g., Octagons). For these domains, we prove that maximal precision is attained already for clusters of globals of sizes at most 2.

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“…The affine equalities or affine inequalities domains [16,30], however, are not. The relational string domains recently proposed by Arceri et al [6] in Sec. 5.1 through Sec.…”

Section: Relational Domainsmentioning

confidence: 99%

“…While we were not able to run Watts, we executed our analysis on the benchmarks reported on in [31]. We took the benchmarks as available from the GitHub repository 6 . The benchmarks proposed in this paper consist of two set of C-source files containing multi-threaded code with asserts.…”

Section: I2 Watts Benchmark Suitementioning

confidence: 99%

Clustered Relational Thread-Modular Abstract Interpretation with Local Traces

Schwarz¹,

Saan²,

Seidl³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The affine equalities or affine inequalities domains [16,30], however, are not. The relational string domains proposed by Arceri et al [6,, are examples of non-numeric 2-decomposable domains.…”

Section: Relational Domainsmentioning

confidence: 99%

Clustered Relational Thread-Modular Abstract Interpretation with Local Traces

Schwarz

Saan

Seidl

et al. 2023

Lecture Notes in Computer Science

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We construct novel thread-modular analyses that track relational information for potentially overlapping clusters of global variables – given that they are protected by common mutexes. We provide a framework to systematically increase the precision of clustered relational analyses by splitting control locations based on abstractions of local traces. As one instance, we obtain an analysis of dynamic thread creation and joining. Interestingly, tracking less relational information for globals may result in higher precision. We consider the class of 2-decomposable domains that encompasses many weakly relational domains (e.g., Octagons). For these domains, we prove that maximal precision is attained already for clusters of globals of sizes at most 2.

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“…Abstract interpretation [18] provides a general framework to build a sound static analysis from a basic semantics and an abstraction relation, and to verify semantic properties. Notably, it has been applied to verify numerical properties [21,36], the absence of runtime errors [7], string properties [26,4], array properties [29,30,31,20], liveness properties [57], and security properties [5,27,25]. Several families of shape analyses have also been designed to infer properties of programs manipulating dynamic data-structures, including TVLA [53] and shape analyses based on separation logic [52].…”

Section: Introductionmentioning

confidence: 99%

“…Existing sequence abstractions typically rely on regular expressions or finite automata [47,3,49]. More recently, [4] extends such an abstraction with sub-string, length, and element position constraints. However, these abstractions lack predicates such as constraints over extremal elements or sortedness.…”

Section: Introductionmentioning

confidence: 99%

A Product of Shape and Sequence Abstractions

Giet,

Ridoux,

Rival

2023

Lecture Notes in Computer Science

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Traditional separation logic-based shape analyses utilize inductive summarizing predicates so as to capture general properties of the layout of data-structures, to verify accurate manipulations of, e.g., various forms of lists or trees. However, they also usually abstract away contents properties, so that they may only verify memory safety and invariance of data-structure shapes. In this paper, we introduce a novel abstract domain to describe sequences of values of unbounded size, and track constraints on their length and on extremal values contained in them. We define a reduced product of such a sequence abstraction together with an existing shape abstraction so as to infer both shape and contents properties of data-structures. We report on the implementation of the sequence domain, its integration into a static analyzer for C code, and we evaluate its ability to verify partial functional correctness properties for list and tree algorithms.

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Relational String Abstract Domains

Cited by 9 publications

References 35 publications

Clustered Relational Thread-Modular Abstract Interpretation with Local Traces

Clustered Relational Thread-Modular Abstract Interpretation with Local Traces

Clustered Relational Thread-Modular Abstract Interpretation with Local Traces

A Product of Shape and Sequence Abstractions

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