On derived dependencies and connected databases
Journal of Logic Programming
Symbolic Boolean manipulation with ordered binary-decision diagrams
ACM Computing Surveys (CSUR)
Handbook of logic in artificial intelligence and logic programming
The quotient of an abstract interpretation
Theoretical Computer Science
Two classes of Boolean functions for dependency analysis
Science of Computer Programming
Sharing and groundness dependencies in logic programs
ACM Transactions on Programming Languages and Systems (TOPLAS)
Type dependencies for logic programs using ACI-unification
Theoretical Computer Science
POPL '77 Proceedings of the 4th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Implementing Groundness Analysis with Definite Boolean Functions
ESOP '00 Proceedings of the 9th European Symposium on Programming Languages and Systems
Comparing the Galois Connection and Widening/Narrowing Approaches to Abstract Interpretation
PLILP '92 Proceedings of the 4th International Symposium on Programming Language Implementation and Logic Programming
The Boolean Logic of Set Sharing Analysis
PLILP '98/ALP '98 Proceedings of the 10th International Symposium on Principles of Declarative Programming
Memoing Evaluation by Source-to-Source Transformation
LOPSTR '95 Proceedings of the 5th International Workshop on Logic Programming Synthesis and Transformation
Quotienting Share for Dependency Analysis
ESOP '99 Proceedings of the 8th European Symposium on Programming Languages and Systems
Worst-case groundness analysis using definite Boolean functions
Theory and Practice of Logic Programming
Positive Boolean Functions as Multiheaded Clauses
Proceedings of the 17th International Conference on Logic Programming
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We propose a new representation for the domain of Definite Boolean functions. The key idea is to view the set of models of a Boolean function as an incidence relation between variables and models. This enables two dual representations: the usual one, in terms of models, specifying which variables they contain; and the other in terms of variables, specifying which models contain them. We adopt the dual representation which provides a clean theoretical basis for the definition of efficient operations on Def in terms of classic ACI1 unification theory. Our approach illustrates in an interesting way the relation of Def to the well-known set-Sharing domain which can also be represented in terms of sets of models and ACI1 unification. From the practical side, a prototype implementation provides promising results which indicate that this representation supports efficient groundness analysis using Def formula. Moreover, widening on this representation is easily defined.