The value flow graph: a program representation for optimal program transformations
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PLDI '94 Proceedings of the ACM SIGPLAN 1994 conference on Programming language design and implementation
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Global optimization by suppression of partial redundancies
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POPL '77 Proceedings of the 4th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Flow Analysis of Computer Programs
Flow Analysis of Computer Programs
STACS '97 Proceedings of the 14th Annual Symposium on Theoretical Aspects of Computer Science
CONCUR '95 Proceedings of the 6th International Conference on Concurrency Theory
SAS '96 Proceedings of the Third International Symposium on Static Analysis
Detecting Equalities of Variables: Combining Efficiency with Precision
SAS '99 Proceedings of the 6th International Symposium on Static Analysis
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SAS '99 Proceedings of the 6th International Symposium on Static Analysis
Expansion-Based Removal of Semantic Partial Redundancies
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ISWC '09 Proceedings of the 8th International Semantic Web Conference
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QUATIC '10 Proceedings of the 2010 Seventh International Conference on the Quality of Information and Communications Technology
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In this paper we present a flexible framework for fine tuning the quality of program analysis based on variations, generalizations, and pragmatic extensions of Plotkin's Structured Operational Semantics (SOS). Key to these variations is the idea of Property-Oriented Expansion, here the non-standard use of the data component in SOS configurations, which ranges from simple abstract interpretations, over arbitrary data flow information, to e.g., temporal constraints. In its most general form, which is characterized by the notion of unifying models, this results in a framework not only for fine-tuning program analysis according to an aspect (quality) of choice, but also for synthesizing orchestrations for service-oriented applications based on loose temporal specifications. From an engineering perspective, the simple interface pattern underlying the unifying models approach was key for realizing our experimental platform. Our experimental results, in particular concerning the state explosion problem, indicate that, in practice, limiting the expansion to the previously determined areas of impact suffices to keep the code growth quite moderate.