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Forward Slicing by Conjunctive Partial Deduction and Argument Filtering

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  • Computer Science
  • Linguistics


Program slicing is a well-known methodology that aims at identifying the program statements that (potentially) affect the values computed at some point of interest. Within imperative programming, this technique has been successfully applied to debugging, specialization, merging, reuse, maintenance, etc. Due to its declarative nature, adapting the slicing notions and techniques to a logic programming setting is not an easy task. In this work, we define the first, semantics-preserving, forward slicing technique for logic programs. Our approach relies on the application of a conjunctive partial deduction algorithm for a precise propagation of information between calls. We do not distinguish between static and dynamic slicing since partial deduction can naturally deal with both static and dynamic data. Furthermore, this approach can quite easily be implemented by adding a new code generator on top of existing partial deduction systems. A slicing tool has been implemented in ECCE, where a post-processing transformation to remove redundant arguments has been added. Experiments conducted on a wide variety of programs are encouraging and demonstrate the usefulness of our approach, both as a classical slicing method and as a technique for code size reduction.

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