Deadlock detection in concurrent programs that create networks with arbitrary numbers of nodes is extremely complex and solutions either give imprecise answers or do not scale. To enable the analysis of such programs, (1) we define an algorithm for detecting deadlocks of a basic model featuring recursion and fresh name generation: the lam programs, and (2) we design a type system for value-passing CCS that returns lam programs. We show the soundness of the type system, and develop a type inference algorithm for it. The resulting algorithm is able to check deadlock-freedom of programs that cannot be handled by previous analyses, such as those that build unbounded networks.

Deadlock analysis of unbounded process networks / Kobayashi, Naoki; Laneve, Cosimo. - In: INFORMATION AND COMPUTATION. - ISSN 1090-2651. - STAMPA. - 252:(2017), pp. 48-70. [10.1016/j.ic.2016.03.004]

Deadlock analysis of unbounded process networks

LANEVE, COSIMO
2017

Abstract

Deadlock detection in concurrent programs that create networks with arbitrary numbers of nodes is extremely complex and solutions either give imprecise answers or do not scale. To enable the analysis of such programs, (1) we define an algorithm for detecting deadlocks of a basic model featuring recursion and fresh name generation: the lam programs, and (2) we design a type system for value-passing CCS that returns lam programs. We show the soundness of the type system, and develop a type inference algorithm for it. The resulting algorithm is able to check deadlock-freedom of programs that cannot be handled by previous analyses, such as those that build unbounded networks.
2017
Deadlock analysis of unbounded process networks / Kobayashi, Naoki; Laneve, Cosimo. - In: INFORMATION AND COMPUTATION. - ISSN 1090-2651. - STAMPA. - 252:(2017), pp. 48-70. [10.1016/j.ic.2016.03.004]
Kobayashi, Naoki; Laneve, Cosimo
File in questo prodotto:
File Dimensione Formato  
concur2014.pdf

accesso aperto

Tipo: Postprint
Licenza: Licenza per Accesso Aperto. Creative Commons Attribuzione - Non commerciale - Non opere derivate (CCBYNCND)
Dimensione 378.67 kB
Formato Adobe PDF
378.67 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/588181
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 24
  • ???jsp.display-item.citation.isi??? 18
social impact