NDLI: Design and implementation of sparse global analyses for C-like languages

Content Provider	ACM Digital Library
Author	Heo, Kihong Lee, Woosuk Lee, Wonchan Yi, Kwangkeun Oh, Hakjoo
Abstract	In this article we present a general method for achieving global static analyzers that are precise, sound, yet also scalable. Our method generalizes the sparse analysis techniques on top of the abstract interpretation framework to support relational as well as non-relational semantics properties for C-like languages. We first use the abstract interpretation framework to have a global static analyzer whose scalability is unattended. Upon this underlying sound static analyzer, we add our generalized sparse analysis techniques to improve its scalability while preserving the precision of the underlying analysis. Our framework determines what to prove to guarantee that the resulting sparse version should preserve the precision of the underlying analyzer. We formally present our framework; we present that existing sparse analyses are all restricted instances of our framework; we show more semantically elaborate design examples of sparse non-relational and relational static analyses; we present their implemen- tation results that scale to analyze up to one million lines of C programs. We also show a set of implementation techniques that turn out to be critical to economically support the sparse analysis process.
Starting Page	229
Ending Page	238
Page Count	10
File Format	PDF
ISSN	03621340 15581160
DOI	10.1145/2345156.2254092
Journal	ACM SIGPLAN Notices (SIGP)
Volume Number	47
Issue Number	6
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1983-05-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Static analysis Abstract interpretation Sparse analysis
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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