NDLI: A practical framework for demand-driven interprocedural data flow analysis

Content Provider	ACM Digital Library
Author	Soffa, Mary Lou Gupta, Rajiv Duesterwald, Evelyn
Copyright Year	1997
Abstract	The high cost and growing importance of interprocedural data flow analysis have led to an increased interest in demand-driven algorithms. In this article, we present a general framework for developing demand-driven interprocedural data flow analyzers and report our experience in evaluating the performance of this approach. A demand for data flow information is modeled as a set of queries. The framework includes a generic demand-driven algorithm that determines the response to query by iteratively applying a system of query propagation rules. The propagation rules yield precise responses for the class of distributive finite data flow problems. We also describe a two-phase framework variation to accurately handle nondistributive problems. A performance evaluation of our demand-driven approach is presented for two data flow problems, namely, reaching-definitions and copy constant propagation. Our experiments show that demand-driven analysis performs well in practice, reducing both time and space requirements when compared with exhaustive analysis.
Starting Page	992
Ending Page	1030
Page Count	39
File Format	PDF
ISSN	01640925
e-ISSN	15584593
DOI	10.1145/267959.269970
Volume Number	19
Issue Number	6
Journal	ACM Transactions on Programming Languages and Systems (TOPLAS)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1997-11-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Copy constant propagation Data flow analysis Def-use chains Demand-driven algorithms Distributive data flow frameworks Interprocedural data flow analysis Program optimizations
Content Type	Text
Resource Type	Article
Subject	Software

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