Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
A practical framework for the abstract interpretation of logic programs
Journal of Logic Programming
Abstract interpretation for concurrent logic languages
Proceedings of the 1990 North American conference on Logic programming
Analysis of constraint logic programs
Proceedings of the 1990 North American conference on Logic programming
Global flow analysis as a practical compilation tool
Journal of Logic Programming
A general framework for semantics-based bottom-up abstract interpretation of logic programs
ACM Transactions on Programming Languages and Systems (TOPLAS)
Experimental evaluation of a generic abstract interpretation algorithm for PROLOG
ACM Transactions on Programming Languages and Systems (TOPLAS)
PLILP '92 Proceedings of the 4th International Symposium on Programming Language Implementation and Logic Programming
Groundness Analysis for Prolog: Implementation and Evaluation of the Domain Prop
Groundness Analysis for Prolog: Implementation and Evaluation of the Domain Prop
A Universal Top-Down Fixpoint Algorithm
A Universal Top-Down Fixpoint Algorithm
Precise and efficient groundness analysis for logic programs
ACM Letters on Programming Languages and Systems (LOPLAS)
Denotational abstract interpretation of logic programs
ACM Transactions on Programming Languages and Systems (TOPLAS)
Combinations of abstract domains for logic programming
POPL '94 Proceedings of the 21st ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Toupie: The µ-calculus over Finite Domains as a Constraint Language
Journal of Automated Reasoning
SAS '99 Proceedings of the 6th International Symposium on Static Analysis
Infinitary relations and their representation
Science of Computer Programming - Special issue on static analysis (SAS'99)
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The domain Prop [22,8] is aconceptually simple and elegant abstract domain to compute groundnessinformation for Prolog programs. In particular, abstract substitutionsare represented by Boolean functions built using the logical connectives⇔,∨,∧.Prop has raised much theoreticalinterest recently but little is known about the practical accuracy andefficiency of this domain.In this paper, we describe an implementation ofProp and we use it to instantiate ageneric abstract interpretation algorithm [14, 10, 17, 15]. A keyfeature of the implementation is the use of ordered binary decision graphs. The implementation has been compared systematically to two otherabstract domains, Mode and Pattern, from the point of view ofgroundness analysis.The experimental results indicate that(1)Prop is very accurate to infergroundness information; (2) this domain is quite practical in terms ofefficiency, although it is theoretically exponential (in the number ofclause variables).