Some considerations on the compile-time analysis of constraint logic programs

This paper discusses some issues which arise in the dataflow analysis of constraint logic programming (CLP) languages. The basic technique applied is that of abstract interpretation. First, some types of optimizations possible in a number of CLP systems (including efficient parallelization) are presented and the information that has to be obtained at compile-time in order to be able to implement such optimizations is considered. Two approaches are then proposed and discussed for obtaining this information for a CLP program: one based on an analysis of a CLP metainterpreter using standard Prolog analysis tools, and a second one based on direct analysis of the CLP program. For the second approach an abstract domain which approximates groundness (also referred to as "definiteness") information (i.e. constraint to a single value) and the related abstraction functions are presented.

[1]  Francesca Rossi,et al.  On the Correctness and Efficiency of Independent And-Parallelism in Logic Programs , 1989, NACLP.

[2]  Patrick Cousot,et al.  Abstract interpretation: a unified lattice model for static analysis of programs by construction or approximation of fixpoints , 1977, POPL.

[3]  William H. Winsborough,et al.  Path-Dependent Reachability Analysis for Multiple Specialization , 1989, NACLP.

[4]  Patrick Cousot,et al.  Comparing the Galois Connection and Widening/Narrowing Approaches to Abstract Interpretation , 1992, PLILP.

[5]  Francesca Rossi,et al.  Non-Strict Independent And-Parallelism , 1990, ICLP.

[6]  Kim Marriott,et al.  Analysis of Constraint Logic Programs , 1990, NACLP.

[7]  Saumya K. Debray,et al.  On the Practicality of Global Flow Analysis of Logic Programs , 1988, ICLP/SLP.

[8]  Dean Jacobs,et al.  Accurate and Efficient Approximation of Variable Aliasing in Logic Programs , 1989, NACLP.

[9]  Joxan Jaffar,et al.  Methodology and Implementation of a CLP System , 1987, ICLP.

[10]  Alvin M. Despain,et al.  Semi-Intelligent Backtracking of Prolog Based on Static Data Dependency Analysis , 1985, SLP.

[11]  W. Older,et al.  Extending Prolog with Constraint Arithmetic on Real Intervals , 1990 .

[12]  Gerda Janssens,et al.  The Impact of Abstract Interpretation: An Experiment in Code Generation , 1989, International Conference on Logic Programming.

[13]  Andrew Taylor,et al.  LIPS on a MIPS: Results from a Prolog Compiler for a RISC , 1990, ICLP.

[14]  Manuel V. Hermenegildo,et al.  Determination of variable dependence information at compile-time through abstract interpretation , 1989 .

[15]  Saumya K. Debray,et al.  Detection and Optimization of Functional Computations in Prolog , 1986, ICLP.

[16]  Fosca Giannotti,et al.  A Technique for Recursive Invariance Detection and Selective Program Specification , 1991, PLILP.

[17]  Pascal Van Hentenryck,et al.  Solving Large Combinatorial Problems in Logic Programming , 1990, J. Log. Program..

[18]  Peter Van Roy,et al.  The Benefits of Global Dataflow Analysis for an Optimizing Prolog Compiler , 1990, NACLP.

[19]  John S. Conery,et al.  The and/or process model for parallel interpretation of logic programs , 1983 .

[20]  Maurice Bruynooghe,et al.  A framework for the abstract interpretation of logic programs , 1987 .

[21]  Gerda Janssens,et al.  An Instance of Abstract Interpretation Integrating Type and Mode Inferencing , 1988, ICLP/SLP.

[22]  Patrick Cousot.  Abstract Interpretation of Logic Programs , 1991, ICLP.

[23]  Manuel V. Hermenegildo,et al.  Combined Determination of Sharing and Freeness of Program Variables through Abstract Interpretation , 1991, ICLP.

[24]  Pascal Van Hentenryck.  Parallel Constraint Satisfaction in Logic Programming: Preliminary Results of CHIP within PEPSys , 1989, ICLP.

[25]  Alain Colmerauer,et al.  Opening the Prolog III universe , 1987 .