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    A hybrid approach to conjunctive partial evaluation of logic programs

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    Conjunctive partial deduction is a well-known technique for the partial evaluation of logic programs. The original formulation follows the so called online approach where all termination decisions are taken on-the-fly. In contrast, offline partial evaluators first analyze the source program and produce an annotated version so that the partial evaluation phase should only follow these annotations to ensure the termination of the process. In this work, we introduce a lightweight approach to conjunctive partial deduction that combines some of the advantages of both online and offline styles of partial evaluation. © 2011 Springer-Verlag.This work has been partially supported by the Spanish Ministerio de Ciencia e Innovación under grant TIN2008-06622-C03-02 and by the Generalitat Valenciana under grant ACOMP/2010/042.Vidal Oriola, GF. (2011). A hybrid approach to conjunctive partial evaluation of logic programs. En Logic-Based Program Synthesis and Transformation. Springer Verlag (Germany). 6564:200-214. https://doi.org/10.1007/978-3-642-20551-4_13S2002146564Ben-Amram, A., Codish, M.: A SAT-Based Approach to Size Change Termination with Global Ranking Functions. In: Ramakrishnan, C.R., Rehof, J. (eds.) TACAS 2008. LNCS, vol. 4963, pp. 218–232. Springer, Heidelberg (2007)Bruynooghe, M., De Schreye, D., Martens, B.: A General Criterion for Avoiding Infinite Unfolding during Partial Deduction of Logic Programs. In: Saraswat, V., Ueda, K. (eds.) Proc. 1991 Int’l Symp. on Logic Programming, pp. 117–131 (1991)Christensen, N.H., Glück, R.: Offline Partial Evaluation Can Be as Accurate as Online Partial Evaluation. ACM Transactions on Programming Languages and Systems 26(1), 191–220 (2004)Codish, M., Taboch, C.: A Semantic Basis for the Termination Analysis of Logic Programs. Journal of Logic Programming 41(1), 103–123 (1999)De Schreye, D., Glück, R., Jørgensen, J., Leuschel, M., Martens, B., Sørensen, M.H.: Conjunctive Partial Deduction: Foundations, Control, Algorihtms, and Experiments. Journal of Logic Programming 41(2&3), 231–277 (1999)Hruza, J., Stepánek, P.: Speedup of logic programs by binarization and partial deduction. TPLP 4(3), 355–380 (2004)Jones, N.D., Gomard, C.K., Sestoft, P.: Partial Evaluation and Automatic Program Generation. Prentice-Hall, Englewood Cliffs (1993)Leuschel, M.: Homeomorphic Embedding for Online Termination of Symbolic Methods. In: Mogensen, T.Æ., Schmidt, D.A., Sudborough, I.H. (eds.) The Essence of Computation. LNCS, vol. 2566, pp. 379–403. Springer, Heidelberg (2002)Leuschel, M.: The DPPD (Dozens of Problems for Partial Deduction) Library of Benchmarks (2007), http://www.ecs.soton.ac.uk/~mal/systems/dppd.htmlLeuschel, M., Elphick, D., Varea, M., Craig, S., Fontaine, M.: The Ecce and Logen Partial Evaluators and Their Web Interfaces. In: Proc. of PEPM 2006, pp. 88–94. IBM Press (2006)Leuschel, M., Vidal, G.: Fast Offline Partial Evaluation of Large Logic Programs. In: Hanus, M. (ed.) LOPSTR 2008. LNCS, vol. 5438, pp. 119–134. Springer, Heidelberg (2009)Lloyd, J.W., Shepherdson, J.C.: Partial Evaluation in Logic Programming. Journal of Logic Programming 11, 217–242 (1991)Somogyi, Z.: A System of Precise Modes for Logic Programs. In: Shapiro, E.Y. (ed.) Proc. of Third Int’l Conf. on Logic Programming, pp. 769–787. The MIT Press, Cambridge (1986

    Supervising Offline Partial Evaluation of Logic Programs using Online Techniques

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    A major impediment for more widespread use of offline partial evaluation is the difficulty of obtaining and maintaining annotations for larger, realistic programs. Existing automatic binding-time analyses still only have limited applicability and annotations often have to be created or improved and maintained by hand, leading to errors. We present a technique to help overcome this problem by using online control techniques which supervise the specialisation process in order to help the development and maintenance of correct annotations by identifying errors. We discuss an implementation in the Logen system and show on a series of examples that this approach is effective: very few false alarms were raised while infinite loops were detected quickly. We also present the integration of this technique into a web interface, which highlights problematic annotations directly in the source code. A method to automatically fix incorrect annotations is presented, allowing the approach to be also used as a pragmatic binding time analysis. Finally we show how our method can be used for efficiently locating built-in errors in Prolog source code

    Normalisierung und partielle Auswertung von funktional-logischen Programmen

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    This thesis deals with the development of a normalization scheme and a partial evaluator for the functional logic programming language Curry. The functional logic programming paradigm combines the two most important fields of declarative programming, namely functional and logic programming. While functional languages provide concepts such as algebraic data types, higher-order functions or demanddriven evaluation, logic languages usually support a non-deterministic evaluation and a built-in search for results. Functional logic languages finally combine these two paradigms in an integrated way, hence providing multiple syntactic constructs and concepts to facilitate the concise notation of high-level programs. However, both the variety of syntactic constructs and the high degree of abstraction complicate the translation into efficient target programs. To reduce the syntactic complexity of functional logic languages, a typical compilation scheme incorporates a normalization phase to subsequently replace complex constructs by simpler ones until a minimal language subset is reached. While the individual transformations are usually simple, they also have to be correctly combined to make the syntactic constructs interact in the intended way. The efficiency of normalized programs can then be improved by means of different optimization techniques. A very powerful optimization technique is the partial evaluation of programs. Partial evaluation basically anticipates the execution of certain program fragments at compile time and computes a semantically equivalent program, which is usually more efficient at run time. Since partial evaluation is a fully automatic optimization technique, it can also be incorporated into the normal compilation scheme of programs. Nevertheless, this also requires termination of the optimization process, which establishes one of the main challenges for partial evaluation besides semantic equivalence. In this work we consider the language Curry as a representative of the functional logic programming paradigm. We develop a formal representation of the normalization process of Curry programs into a kernel language, while respecting the interference of different language constructs. We then define the dynamic semantics of this kernel language, before we subsequently develop a partial evaluation scheme and show its correctness and termination. Due to the previously described normalization process, this scheme is then directly applicable to arbitrary Curry programs. Furthermore, the implementation of a practical partial evaluator is sketched based on the partial evaluation scheme, and its applicability and usefulness is documented by a variety of typical partial evaluation examples

    Fast Offline Partial Evaluation of Logic Programs

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    One of the most important challenges in partial evaluation is the design of automatic methods for ensuring the termination of the process. In this work, we introduce sufficient conditions for the strong (i.e., independent of a computation rule) termination and quasitermination of logic programs which rely on the construction of size-change graphs. We then present a fast binding-time analysis that takes the output of the termination analysis and annotates logic programs so that partial evaluation terminates. In contrast to previous approaches, the new binding-time analysis is conceptually simpler and considerably faster, scaling to medium-sized or even large examples. © 2014 Elsevier Inc. All rights reserved.This work has been partially supported by the Spanish Ministerio de Ciencia e Innovacion under grant TIN2008-06622-C03-02 and by the Generalitat Valenciana under grant PROMETEO/2011/052.Leuschel, M.; Vidal Oriola, GF. (2014). Fast Offline Partial Evaluation of Logic Programs. Information and Computation. 235:70-97. https://doi.org/10.1016/j.ic.2014.01.005S709723
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