Finding Optimum Abstractions in Parametric Dataflow Analysis

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We propose a technique to efficiently search a large family of abstractions in order to prove a query using a parametric dataflow analysis. Our technique either finds the cheapest such abstraction or shows that none exists. It is based on counterexample-guided abstraction refinement but applies a novel meta-analysis on abstract counterexample traces to efficiently find abstractions that are incapable of proving the query. We formalize the technique in a generic framework and apply it to two analyses: a type-state analysis and a thread-escape analysis. We demonstrate the effectiveness of the technique on a suite of Java benchmark programs.
Publisher
ASSOC COMPUTING MACHINERY
Issue Date
2013-06
Language
English
Article Type
Article; Proceedings Paper
Citation

ACM SIGPLAN NOTICES, v.48, no.6, pp.365 - 376

ISSN
0362-1340
DOI
10.1145/2499370.2462185
URI
http://hdl.handle.net/10203/225274
Appears in Collection
CS-Journal Papers(저널논문)
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