Type-Based Analysis for Session Inference (Extended Abstract)

Abstract : We propose a type-based analysis to infer the session protocols of channels in an ML-like concurrent functional language. Combining and extending well-known techniques, we develop a type-checking system that separates the underlying ML type system from the typing of sessions. Without using linearity, our system guarantees communication safety and partial lock freedom. It also supports provably complete session inference for finite sessions with no programmer annotations. We exhibit the usefulness of our system with interesting examples, including one which is not typable in substructural type systems.
Type de document :
Communication dans un congrès
Elvira Albert; Ivan Lanese. 36th International Conference on Formal Techniques for Distributed Objects, Components, and Systems (FORTE), Jun 2016, Heraklion, Greece. Lecture Notes in Computer Science, LNCS-9688, pp.248-266, 2016, Formal Techniques for Distributed Objects, Components, and Systems. 〈10.1007/978-3-319-39570-8_17〉
Liste complète des métadonnées

Littérature citée [19 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01432922
Contributeur : Hal Ifip <>
Soumis le : jeudi 12 janvier 2017 - 11:34:30
Dernière modification le : jeudi 12 janvier 2017 - 11:38:42
Document(s) archivé(s) le : vendredi 14 avril 2017 - 12:37:03

Fichier

 Accès restreint
Fichier visible le : 2019-01-01

Connectez-vous pour demander l'accès au fichier

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Citation

Carlo Spaccasassi, Vasileios Koutavas. Type-Based Analysis for Session Inference (Extended Abstract). Elvira Albert; Ivan Lanese. 36th International Conference on Formal Techniques for Distributed Objects, Components, and Systems (FORTE), Jun 2016, Heraklion, Greece. Lecture Notes in Computer Science, LNCS-9688, pp.248-266, 2016, Formal Techniques for Distributed Objects, Components, and Systems. 〈10.1007/978-3-319-39570-8_17〉. 〈hal-01432922〉

Partager

Métriques

Consultations de la notice

32