Integrating a Preprocessor Based on Unification in the Laboratory for Rapid Rewriting

In normalization, traversing the term to find a match with a rule costs most of the time. This thesis presents the design, implementation, and integration of a unification-based preprocessor into the Laboratory for Rapid Rewriting, LRR, and the current status of LRR. LRR consists of two interpreters: Smaran, which stores the history of all rule applications, and TGR, which stands for Term Graph Rewriter. We have improved the preprocessor and the DS-list significantly and efficiently integrated their latest versions into both components of LRR. The performance of the latest version of LRR on some benchmarks – both favorable and unfavorable – is presented and compared with other interpreters including Maude and Rascal.Computer Science, Department o