Construction of Abstract Domains for Heterogeneous Properties (Position Paper)

Rival, Xavier; Toubhans, Antoine; Chang, Bor-Yuh Evan

doi:10.1007/978-3-662-45231-8_40

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…Cousot and Cousot [20] present a general framework for modularly constructing program analyses, but it requires languages with compositional control flow. Toubhans, Rival and Chang [44,53] develop a modular domain design for pointer-manipulating programs, whereas our domain construction focuses on abstracting pure heterogeneous data-structures.…”

Section: Related Workmentioning

confidence: 99%

Verification of Program Transformations with Inductive Refinement Types

Al-Sibahi

Jensen

Dimovski

et al. 2021

ACM Trans. Softw. Eng. Methodol.

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High-level transformation languages like Rascal include expressive features for manipulating large abstract syntax trees: first-class traversals, expressive pattern matching, backtracking, and generalized iterators. We present the design and implementation of an abstract interpretation tool, Rabit, for verifying inductive type and shape properties for transformations written in such languages. We describe how to perform abstract interpretation based on operational semantics, specifically focusing on the challenges arising when analyzing the expressive traversals and pattern matching. Finally, we evaluate Rabit on a series of transformations (normalization, desugaring, refactoring, code generators, type inference, etc.) showing that we can effectively verify stated properties.

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Section: Related Workmentioning

confidence: 99%

Verification of Program Transformations with Inductive Refinement Types

Al-Sibahi

Jensen

Dimovski

et al. 2021

ACM Trans. Softw. Eng. Methodol.

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show abstract

“…Extending our modular construction to support relational information is future work. Rival et al [22,25] discuss how to provide a way to modularize symbolic memories used by pointer-manipulating by decompositing them into distinct sub-memories which share information. This is suitable if different parts of the program need to be analyzed with different abstractions.…”

Section: Related Workmentioning

confidence: 99%

Galois Connections for Recursive Types

Al-Sibahi

Jensen

Møgelberg

et al. 2020

From Lambda Calculus to Cybersecurity Through Program Analysis

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Building a static analyser for a real language involves modeling of large domains capturing the many available data types. To scale domain design and support efficient development of project-specific analyzers, it is desirable to be able to build, extend, and change abstractions in a systematic and modular fashion. We present a framework for modular design of abstract domains for recursive types and higher-order functions, based on the theory of solving recursive domain equations. We show how to relate computable abstract domains to our framework, and illustrate the potential of the construction by modularizing a monolithic domain for regular tree grammars. A prototype implementation in the dependently typed functional language Agda shows how the theoretical solution can be used in practice to construct static analysers. Authors ordered alphabetically type Fml = Atom ( int ) | Neg ( Fml ) | And ( Fml , Fml ) | Or ( Fml , Fml ) nnf ( f : Fml ) = case f of | Atom ( i ) -> Atom ( i ) | Neg ( Atom ( i )) -> Neg ( Atom ( i )) | Neg ( Neg ( f )) -> nnf f | Neg ( And ( f1 , f2 )) -> Or ( nnf ( Neg f1 ) , nnf ( Neg f2 )) | Neg ( Or ( f1 , f2 )) -> And ( nnf ( Neg f1 ) , nnf ( Neg f2 )) | Or ( f1 , f2 ) -> Or ( nnf f1 , nnf f2 ) | And ( f1 , f2 ) -> And ( nnf f1 , nnf f2 ) bool = unit+unit x0 : A0, . . . , xn : An ex xi : Ai Γ ex n : int Γ ex tt : unit Γ ex e1 : int Γ ex e2 : int Γ ex e1 e2 : int ( ∈ {+, −, ×}) Γ ex e1 : int Γ ex e2 : int Γ ex e1 ≤ e2 : bool Γ ex e1 : A1 Γ ex e2 : A2 Γ ex (e1, e2

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“…Cousot and Cousot [19] present a general framework for modularly constructing program analyses, but it requires languages with compositional control flow. Toubhans, Rival and Chang [38,48] develop a modular domain design for pointermanipulating programs, whereas our domain construction focuses on abstracting pure heterogeneous data-structures.…”

Section: Related Workmentioning

confidence: 99%

Verification of high-level transformations with inductive refinement types

et al. 2020

View full text Add to dashboard Cite

High-level transformation languages like Rascal include expressive features for manipulating large abstract syntax trees: first-class traversals, expressive pattern matching, backtracking and generalized iterators. We present the design and implementation of an abstract interpretation tool, Rabit, for verifying inductive type and shape properties for transformations written in such languages. We describe how to perform abstract interpretation based on operational semantics, specifically focusing on the challenges arising when analyzing the expressive traversals and pattern matching. Finally, we evaluate Rabit on a series of transformations (normalization, desugaring, refactoring, code generators, type inference, etc.) showing that we can effectively verify stated properties.

show abstract

Construction of Abstract Domains for Heterogeneous Properties (Position Paper)

Cited by 5 publications

References 11 publications

Verification of Program Transformations with Inductive Refinement Types

Verification of Program Transformations with Inductive Refinement Types

Galois Connections for Recursive Types

Verification of high-level transformations with inductive refinement types

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