Abstract interpretation and application to logic programs
Journal of Logic Programming
Set based program analysis
Formal language, grammar and set-constraint-based program analysis by abstract interpretation
FPCA '95 Proceedings of the seventh international conference on Functional programming languages and computer architecture
Fast static analysis of C++ virtual function calls
Proceedings of the 11th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Componential set-based analysis
Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation
Partial online cycle elimination in inclusion constraint graphs
PLDI '98 Proceedings of the ACM SIGPLAN 1998 conference on Programming language design and implementation
Projection merging: reducing redundancies in inclusion constraint graphs
Proceedings of the 27th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Scalable propagation-based call graph construction algorithms
OOPSLA '00 Proceedings of the 15th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Principles of Program Analysis
Principles of Program Analysis
POPL '82 Proceedings of the 9th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Proceedings of the Workshop on Object-Oriented Technology
Reducing the Cost of Data Flow Analysis By Congruence Partitioning
CC '94 Proceedings of the 5th International Conference on Compiler Construction
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This paper proposes a transformation-based approach to design efficient constraint-based analysis at a larger granularity. In this approach, we can design a less or equally precise but more efficient version of an original analysis by rule transformation. To do this, we first define or design an index determination rule for a new sparse analysis based on some syntactic properties, so that it can partition the original indices, and then transform the original construction rules into new ones by applying the partition. As applications of this approach, we presents sparse versions of side-effect analysis and exception analysis, which give equally precise information for functions as the original ones.