Contracts for higher-order functions

By R. Findler, Matthias Felleisen. ACM SIGPLAN International Conference on Functional Programming, 2002

508 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Information Systems

View Paper: https://www.semanticscholar.org/paper/7476e097c4f7b84418526922a2acd56b4e88142f

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Citations in the corpus

The ruby type checker (2013, background): “This conversion is similar to the conversion performed by Findler and Felleisen [7] to protect higher-order functions with contracts.”
Design and evaluation of gradual typing for python (2014, methodology): “We could possibly achieve some kind of static typing by introducing sum types into the language, or by using the occurrence typing of Tobin-Hochstadt and Felleisen [34].”
Static type inference for Ruby (2009, methodology): “Our vision of DRuby was inspired by an exciting body of recent work on mixing static and dynamic typing, including ideas such as soft typing [14], the dynamic type [2], gradual typing [33], and contracts [16].”
Mixed Messages: Measuring Conformance and Non-Interference in TypeScript (2017, unknown): “Our approach to function wrappers follows that of Findler and Felleisen [8] and Wadler and Findler [39].”
Hybrid type checking (2006, methodology): “The cast 〈S T 〉 t dynamically checks that the result of t is of type T (in a manner similar to coercions [38], contracts [13, 14], and to type casts in languages such as Java [20]).”
Gradual Soundness: Lessons from Static Python (2022, background): “This latter property means that blame-tracking [12] is trivial because casts either succeed or fail immediately.”
JSTrace: Run-time Type Discovery for JavaScript (2010, background): “While one of Typed JavaScript’s goals is to support migration to a static type system, we would do so only with clean separation between the typed and untyped parts of a program by using contracts [10].”
Gradual typing: a new perspective (2019, methodology): “This had to be done from scratch, since all existing formalizations of gradual typing were essentially syntax-based, even the remarkable AGT approach of Garcia et al. [2016]: although it gives an interpretation of gradual types via a łconcretizationž function, it relies on an łabstractionž function ”
The Design and Implementation of Typed Scheme: From Scripts to Programs (2011, unknown): “We intend to study an integration of latent predicates with higher-order contracts (Findler and Felleisen, 2002) and expect to ﬁnd additional uses.”
Gradual Typing for Functional Languages (2006, unknown): “This rule is inspired by the work on semantic casts [13, 14, 15], though the rule may look slightly different because the casts used in this paper are annotated with the target type only and not also with the source type.”
Gradual Typing for Objects (2007, background): “For example, casting at function types creates a wrapper function with the appropriate casts on the input and output [19, 20, 21, 48].”
Dynamic type inference for gradual Hindley–Milner typing (2018, background): “They have polarity to indicate which side of a cast to be blamed [Findler and Felleisen 2002].”