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Lattice frameworks for multisource and bidirectional data flow problems
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Source ACM Transactions on Programming Languages and Systems (TOPLAS) archive
Volume 17 ,  Issue 5  (September 1995) table of contents
Pages: 777 - 803  
Year of Publication: 1995
ISSN:0164-0925
Authors
Stephen P. Masticola  Siemens Corporate Research, Princeton, NJ
Thomas J. Marlowe  Seton Hall Univ., South Orange, NJ
Barbara G. Ryder  Rutgers Univ., Piscataway, NJ
Publisher
ACM  New York, NY, USA
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ABSTRACT

Multisource data flow problems involve information which may enter nodes independently through different classes of edges. In some cases, dissimilar meet operations appear to be used for different types of nodes. These problems include bidirectional and flow-sensitive problems as well as many static analyses of concurrent programs with synchronization. K-tuple frameworks, a type of standard data flow framework, provide a natural encoding for multisource problems using a single meet operator. Previously, the solution of these problems has been described as the fixed point of a set of data flow equations. Using our k-tuple representation, we can access the general results of standard data flow frameworks concerning convergence time and solution precision for these problems. We demonstrate this for the bidirectional component of partial redundancy suppression and two problems on the program summary graph. An interesting subclass of k-tuple frameworks, the join-of-meets frameworks, is useful for reachability problems, especially those stemming from analyses of explicitly parallel programs. We give results on function space properties for join-of-meets frameworks that indicate precise solutions for most of them will be difficult to obtain.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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REVIEW

"Pierre Jouvelot : Reviewer"

Static properties of programs, such as use/kill information or available expressions, which are commonly used in optimizing compilers, can often be determined using systems of graph dataflow equations. When these equations reference different   more...

Collaborative Colleagues:
Stephen P. Masticola: colleagues
Thomas J. Marlowe: colleagues
Barbara G. Ryder: colleagues