LEAPS is a state-of-the-art production system compiler that produces the fastest sequential executables of OPS5 rule sets. The performance of LEAPS is due to its reliance on complex data structures and search algorithms to speed rule processing. In this paper, we explain the LEAPS algorithms in terms of the programming abstractions of the P2 data structure compiler.

In this paper 1 we present performance results for a production system environment, CLIPS++, that demonstrate the advantage of selectively building and applying simple index structures. We contrast this to the extensive body of work on matching which over the years has evolved increasingly complex compositions of index structurs which are then uniformly applied to all the data types and rules in a production system program. Over a set of benchmark programs, the fastest executions are always attained by carefully selecting a good mixture of indexes rather than universal

Abstract—Thirty years after Forgy’s seminal dissertation, Rete remains the de facto standard matching algorithm. Despite promising research results, alternative algorithms such as TREAT and LEAPS have had little impact on modern production rule engines. Constraint Handling Rules (CHR) is a high-level, declarative programming language, similar to production rules. In recent years, CHR has increasingly been used in a wide range of general-purpose applications. State-of-the-art CHR systems use LEAPS-like lazy matching, and implement a large body of novel program analyses and optimization techniques to further improve performance. While obviously related, CHR and production rules research have mostly evolved independently from each other. With this article, we aim to foster cross-fertilization of implementation techniques. We provide a lucid, comprehensive overview of CHR’s rule evaluation methodology, and survey recent contributions to the field of lazy matching. Our empirical evaluation confirms Rete-based engines would surely benefit from incorporating similar techniques and optimizations.