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Vincent Simonet

dblp:92/4440 · DBLP profile ↗
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6ranked-venue papers
4as first author
0since 2021 · last 2007
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 5 · 3 first-authorSecurity and privacy · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
3 papers
Programming languages and type systems · 92% Program analysis · 8%
Network and information security
2 papers
Systems and software security · 100%

Topics — the 9 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Programming languages and type systems
type systems
0.122007
A constraint-based approach to guarded algebraic data types · ACM Trans. Program. Lang. Syst. 2007
Information flow inference for ML · ACM Trans. Program. Lang. Syst. 2003
Programming languages and type systems › type inference
constraint-based type inference
0.122007
A constraint-based approach to guarded algebraic data types · ACM Trans. Program. Lang. Syst. 2007
Information flow inference for ML · POPL 2002
Programming languages and type systems › functional programming › algebraic data types
guarded algebraic data types
0.112007
A constraint-based approach to guarded algebraic data types · ACM Trans. Program. Lang. Syst. 2007
Programming languages and type systems
type inference
0.112007
A constraint-based approach to guarded algebraic data types · ACM Trans. Program. Lang. Syst. 2007
Systems and software security
information flow control
0.012003
Information flow inference for ML · ACM Trans. Program. Lang. Syst. 2003
Programming languages and type systems › type systems › security type systems
information-flow type systems
0.012003
Information flow inference for ML · ACM Trans. Program. Lang. Syst. 2003
Systems and software security › information flow control
noninterference
0.012002
Information flow inference for ML · POPL 2002
Program analysis › static analysis
information flow analysis
0.012002
Information flow inference for ML · POPL 2002
Programming languages and type systems › type systems › polymorphism
polymorphic recursion
0.012007
A constraint-based approach to guarded algebraic data types · ACM Trans. Program. Lang. Syst. 2007

Methods — techniques the papers use, named apart from their topics

subject reduction · 0.1semi-syntactic type soundness · 0.1constraint-based type system · 0.1
YearPublicationVenuePosition
2007 A constraint-based approach to guarded algebraic data types
abstract
We study HMG(X), an extension of the constraint-based type system HM(X) with deep pattern matching, polymorphic recursion, andguarded algebraic data types. Guarded algebraic data types subsume the concepts known in the literature asindexed types,guarded recursive datatype constructors,(first-class) phantom types, andequality qualified types, and are closely related toinductive types. Their characteristic property is to allow every branch of a case construct to be typechecked under different assumptions about the type variables in scope. We prove that HMG(X) is sound and that, provided recursive definitions carry a type annotation, type inference can be reduced to constraint solving. Constraint solving is decidable, at least for some instances ofX, but prohibitively expensive. Effective type inference for guarded algebraic data types is left as an issue for future research.
Vincent Simonet, François Pottier
ACM Trans. Program. Lang. Syst.1
2003 Type Inference with Structural Subtyping: A Faithful Formalization of an Efficient Constraint Solver
Vincent Simonet
APLAS1
2003 An extension of HM(X) with bounded existential and universal data-types
abstract
We propose a conservative extension of HM(X), a generic constraint-based type inference framework, with bounded existential (a.k.a. abstract) and universal (a.k.a. polymorphic) data-types. In the first part of the article, which remains abstract of the type and constraint language (i.e. the logic X), we introduce the type system, prove its safety and define a type inference algorithm which computes principal typing judgments. In the second part, we propose a realistic constraint solving algorithm for the case of structural sub-typing, which handles the non-standard construct of the constraint language generated by type inference: a form of bounded universal quantification.
Vincent Simonet
ICFP1
2003 Information flow inference for ML
abstract
This paper presents a type-based information flow analysis for a call-by-value λ-calculus equipped with references, exceptions and let-polymorphism, which we refer to as ML. The type system is constraint-based and has decidable type inference. Its noninterference proof is reasonably light-weight, thanks to the use of a number of orthogonal techniques. First, a syntactic segregation between values and expressions allows a lighter formulation of the type system. Second, noninterference is reduced to subject reduction for a nonstandard language extension. Lastly, a semi-syntactic approach to type soundness allows dealing with constraint-based polymorphism separately.
François Pottier, Vincent Simonet
ACM Trans. Program. Lang. Syst.2
2002 Fine-Grained Information Flow Analysis for a \lambda Calculus with Sum Types
abstract
This paper presents a new type system tracing information flow for a λ-calculus equipped with polymorphic “let ” and with sums (a.k.a. union types or polymorphic variants). The type system allows establishing (weak) noninterference properties. Thanks to original forms of security annotations and constraints, it is more accurate than existing analyses. Through a straightforward encoding into sums, this work also provides a new type-based information flow analysis for programming languages featuring exceptions. From these systems, one may derive constraint-based formulations, in the style of HM(X), which have decidable type inference. 1
Vincent Simonet
CSFW1
2002 Information flow inference for ML
abstract
This paper presents a type-based information flow analysis for a call-by-value λ-calculus equipped with references, exceptions and let-polymorphism, which we refer to as Core ML. The type system is constraint-based and has decidable type inference. Its non-interference proof is reasonably lightweight, thanks to the use of a number of orthogonal techniques. First, a syntactic segregation between values and expressions allows a lighter formulation of the type system. Second, non-interference is reduced to subject reduction for a non-standard language extension. Lastly, a semi-syntactic approach to type soundness allows dealing with constraint-based polymorphism separately.
François Pottier, Vincent Simonet
POPL2