  Tabling for contextual abduction in logic programming has been introduced as
a means to store previously obtained abductive solutions in one context to be
reused in another context. This paper identifies a number of issues in the
existing implementations of tabling in contextual abduction and aims to
mitigate the issues. We propose a new program transformation for integrity
constraints to deal with their proper application for filtering solutions while
also reducing the table memory usage. We further optimize the table memory
usage by selectively picking predicates to table and by pragmatically
simplifying the representation of the problem. The evaluation of our proposed
approach, on both artificial and real world problems, shows that they improve
the scalability of tabled abduction compared to previous implementations.
