JNI light: An operational model for the core JNI

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Through foreign function interfaces (FFIs), software components in different programming languages interact with each other in the same address space. Recent years have witnessed a number of systems that analyze FFIs for safety and reliability. However, lack of formal specifications of FFIs hampers progress in this endeavor. We present a formal operational model, JNI Light (JNIL), for a subset of a widely used FFI - the Java Native Interface (JNI). JNIL focuses on the core issues when a high-level garbage-collected language interacts with a low-level language. It proposes abstractions for handling a shared heap, crosslanguage method calls, cross-language exception handling, and garbage collection. JNIL can directly serve as a formal basis for JNI tools and systems. The abstractions in JNIL are also useful when modeling other FFIs, such as the Python/C interface and the OCaml/C interface.

Original languageEnglish (US)
Title of host publicationProgramming Languages and Systems - 8th Asian Symposium, APLAS 2010, Proceedings
Pages114-130
Number of pages17
DOIs
StatePublished - Dec 1 2010
Event8th Asian Symposium on Programming Languages and Systems, APLAS 2010 - Shanghai, China
Duration: Nov 28 2010Dec 1 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6461 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th Asian Symposium on Programming Languages and Systems, APLAS 2010
CountryChina
CityShanghai
Period11/28/1012/1/10

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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    Tan, G. (2010). JNI light: An operational model for the core JNI. In Programming Languages and Systems - 8th Asian Symposium, APLAS 2010, Proceedings (pp. 114-130). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6461 LNCS). https://doi.org/10.1007/978-3-642-17164-2_9