Work

Relevant context inference

Year: 1999

Type: conference-paper

Abstract: Relevant context inference (RCI) is a modular technique for flow- and context-sensitive data-flow analysis of statically typed object-oriented programming languages such as C++ and Java. RCI can be used to analyze complete programs as well as incomplete programs such as libraries; this approach does not require that the entire program be memory-resident during the analysis. RCI is presented in the context of points-to analysis for a realistic subset of C++. The empirical evidence obtained from a prototype implementation argues the effectiveness of RCI.

Source: ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL)

DOI: 10.1145/292540.292554

Authors: Ramkrishna Chatterjee, Barbara G. Ryder, William A. Landi

Institutions: Rutgers, The State University of New Jersey, Siemens (United States)

Language: English

Topic: Logic, programming, and type systems

Subfield: Software

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: National Science Foundation

Award: Scalable Static Techniques for Exhaustive and Incremental Analyses of C Systems