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Jeffrey M. Barth

dblp:66/4362 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1977
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Program analysis · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program analysis
data flow analysis
0.011977
An Interprocedural Data Flow Analysis Algorithm · POPL 1977
Program analysis › static analysis
interprocedural analysis
0.011977
An Interprocedural Data Flow Analysis Algorithm · POPL 1977
Program analysis › data flow analysis
interprocedural dataflow analysis
0.011977
An Interprocedural Data Flow Analysis Algorithm · POPL 1977
YearPublicationVenuePosition
1977 An Interprocedural Data Flow Analysis Algorithm
abstract
A new interprocedural data flow analysis algorithm is presented and analyzed. The algorithm associates with each procedure in a program information about which variables may be modified, which may be used, and which are possibly preserved by a call on the procedure, and all of it subcalls. The algorithm is sufficiently powerful to be used on recursive programs and to deal with the sharing of variables which arises through reference parameters. The algorithm is unique in that it can compute all of this information in a single pass, not requiring a prepass to compute calling relationships or sharing patterns. A lower bound for the computational complexity of gathering interprocedural data flow information is derived and the algorithm is shown to be asymptotically optimal. The algorithm has been implemented and it is practical for use even on quite large programs.
Jeffrey M. Barth
POPL1