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dc.contributor.authorKot, Lucjaen_US
dc.contributor.authorKozen, Dexteren_US
dc.date.accessioned2007-04-04T19:38:06Z
dc.date.available2007-04-04T19:38:06Z
dc.date.issued2004-12-20en_US
dc.identifier.citationhttp://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cis/TR2004-1971en_US
dc.identifier.urihttps://hdl.handle.net/1813/5671
dc.description.abstractMost standard approaches to the static analysis of programs, such as the popular worklist method, are first-order methods that inductively annotate program points with abstract values. In this paper we introduce a second-order approach based on Kleene algebra. In this approach, the primary objects of interest are not the abstract data values, but the transfer functions that manipulate them. These elements form a Kleene algebra. The dataflow labeling is not achieved by inductively labeling the program with abstract values, but rather by computing the star (Kleene closure) of a matrix of transfer functions. In this paper we introduce the method and prove soundness and completeness with respect to the standard worklist algorithm.en_US
dc.format.extent160905 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.publisherCornell Universityen_US
dc.subjectcomputer scienceen_US
dc.subjecttechnical reporten_US
dc.titleSecond-Order Abstract Interpretation via Kleene Algebraen_US
dc.typetechnical reporten_US


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