An integration of partial evaluation in a generic abstract interpretation framework

Information generated by abstract interpreters has long been used to perform program specialization. Additionally, if the abstract interpreter generates a multivariant analysis, it is also possible to perform múltiple specialization. Information about valúes of variables is propagated by simulating program execution and performing fixpoint computations for recursive calis. In contrast, traditional partial evaluators (mainly) use unfolding for both propagating valúes of variables and transforming the program. It is known that abstract interpretation is a better technique for propagating success valúes than unfolding. However, the program transformations induced by unfolding may lead to important optimizations which are not directly achievable in the existing frameworks for múltiple specialization based on abstract interpretation. The aim of this work is to devise a specialization framework which integrates the better information propagation of abstract interpretation with the powerful program transformations performed by partial evaluation, and which can be implemented via small modifications to existing generic abstract interpreters. With this aim, we will relate top-down abstract interpretation with traditional concepts in partial evaluation and sketch how the sophisticated techniques developed for controlling partial evaluation can be adapted to the proposed specialization framework. We conclude that there can be both practical and conceptual advantages in the proposed integration of partial evaluation and abstract interpretation

Concolic Execution and Test Case Generation in Prolog

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-17822-6_10Symbolic execution extends concrete execution by allowing symbolic input data and then exploring all feasible execution paths. It has been defined and used in the context of many different programming languages and paradigms. A symbolic execution engine is at the heart of many program analysis and transformation techniques, like partial evaluation, test case generation or model checking, to name a few. Despite its relevance, traditional symbolic execution also suffers from several drawbacks. For instance, the search space is usually huge (often infinite) even for the simplest programs. Also, symbolic execution generally computes an overapproximation of the concrete execution space, so that false positives may occur. In this paper, we propose the use of a variant of symbolic execution, called concolic execution, for test case generation in Prolog. Our technique aims at full statement coverage. We argue that this technique computes an underapproximation of the concrete execution space (thus avoiding false positives) and scales up better to medium and large Prolog applications.This work has been partially supported by the EU (FEDER) and the Spanish Ministerio de Economía y Competitividad (Secretaría de Estado de Investigación, Desarrollo e Innovación) under grant TIN2013-44742-C4-1-R and by the Generalitat Valenciana under grant PROMETEO/2011/052.Vidal Oriola, GF. (2015). Concolic Execution and Test Case Generation in Prolog. En Logic-Based Program Synthesis and Transformation. Springer. 167-181. https://doi.org/10.1007/978-3-319-17822-6_10S167181Albert, E., Arenas, P., Gómez-Zamalloa, M., Rojas, J.M.: Test case generation by symbolic execution: basic concepts, a CLP-based instance, and actor-based concurrency. In: Bernardo, M., Damiani, F., Hähnle, R., Johnsen, E.B., Schaefer, I. (eds.) SFM 2014. LNCS, vol. 8483, pp. 263–309. Springer, Heidelberg (2014)Belli, F., Jack, O.: Implementation-based analysis and testing of Prolog programs. In: ISSTA, pp. 70–80. ACM (1993)Clarke, L.A.: A program testing system. In: Proceedings of the 1976 Annual Conference (ACM’76), Houston, pp. 488–491 (1976)De Schreye, D., Glück, R., Jørgensen, J., Leuschel, M., Martens, B., Sørensen, M.H.: Conjunctive partial deduction: foundations, control, algorithms, and experiments. J. Log. Program. 41(2&3), 231–277 (1999)Giesl, J., Ströder, T., Schneider-Kamp, P., Emmes, F., Fuhs, C.: Symbolic evaluation graphs and term rewriting: a general methodology for analyzing logic programs. In: PPDP’12, pp. 1–12. ACM (2012)Godefroid, P., Klarlund, N., Sen, K.: DART: directed automated random testing. In: Proceedings of PLDI’05, pp. 213–223. ACM (2005)Godefroid, P., Levin, M.Y., Molnar, D.A.: Sage: whitebox fuzzing for security testing. Commun. ACM 55(3), 40–44 (2012)Gómez-Zamalloa, M., Albert, E., Puebla, G.: Test case generation for object-oriented imperative languages in CLP. TPLP 10(4–6), 659–674 (2010)King, J.C.: Symbolic execution and program testing. Commun. ACM 19(7), 385–394 (1976)Leuschel, M.: The DPPD (Dozens of Problems for Partial Deduction) Library of Benchmarks. http://www.ecs.soton.ac.uk/mal/systems/dppd.html (2007)Lloyd, J.W.: Foundations of Logic Programming, 2nd edn. Springer, Berlin (1987)Lloyd, J.W., Shepherdson, J.C.: Partial evaluation in logic programming. J. Log. Program. 11, 217–242 (1991)Martens, B., Gallagher, J.: Ensuring global termination of partial deduction while allowing flexible polyvariance. In: Proceedings of ICLP’95, pp. 597–611. MIT Press (1995)Pasareanu, C.S., Rungta, N.: Symbolic PathFinder: symbolic execution of Java bytecode. In: Pecheur, C., Andrews, J., Di Nitto, E. (eds.) ASE, pp. 179–180. ACM (2010)Rojas, J.M., Gómez-Zamalloa, M.: A framework for guided test case generation in constraint logic programming. In: Albert, E. (ed.) Proceedings of LOPSTR. LNCS, vol. 7844, pp. 176–193. Springer, Heidelberg (2013)Sen, K., Marinov, D., Agha, G.: CUTE: a concolic unit testing engine for C. In: Proceedings of ESEC/SIGSOFT FSE 2005, pp. 263–272. ACM (2005)Ströder, T., Emmes, F., Schneider-Kamp, P., Giesl, J., Fuhs, C.: A linear operational semantics for termination and complexity analysis of $$\sf ISO$$ $$\sf Prolog$$ . In: Vidal, G. (ed.) LOPSTR’11. LNCS, vol. 7225, pp. 237–252. Springer, Heidelberg (2012

Fast Offline Partial Evaluation of Logic Programs

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

A Partial Evaluation Framework for Order-sorted Equational Programs modulo Axioms

[EN] Partial evaluation is a powerful and general program optimization technique with many successful applications. Existing PE schemes do not apply to expressive rule-based languages like Maude, CafeOBJ, OBJ, ASF+SDF, and ELAN, which support: 1) rich type structures with sorts, subsorts, and overloading; and 2) equational rewriting modulo various combinations of axioms such as associativity, commutativity, and identity. In this paper, we develop the new foundations needed and illustrate the key concepts by showing how they apply to partial evaluation of expressive programs written in Maude. Our partial evaluation scheme is based on an automatic unfolding algorithm that computes term variants and relies on high-performance order-sorted equational least general generalization and order-sorted equational homeomorphic embedding algorithms for ensuring termination. We show that our partial evaluation technique is sound and complete for convergent rewrite theories that may contain various combinations of associativity, commutativity, and/or identity axioms for different binary operators. We demonstrate the effectiveness of Maude's automatic partial evaluator, Victoria, on several examples where it shows significant speed-ups. (C) 2019 Elsevier Inc. All rights reserved.This work has been partially supported by the EU (FEDER) and the Spanish MCIU under grant RTI2018-094403-B-C32, by Generalitat Valenciana under grant PROMETEO/2019/098, and by NRL under contract number N00173-17-1-G002. Angel Cuenca-Ortega has been supported by the SENESCYT, Ecuador (scholarship program 2013).Alpuente Frasnedo, M.; Cuenca-Ortega, AE.; Escobar Román, S.; Meseguer, J. (2020). A Partial Evaluation Framework for Order-sorted Equational Programs modulo Axioms. Journal of Logical and Algebraic Methods in Programming. 110:1-36. https://doi.org/10.1016/j.jlamp.2019.100501S13611

Normalisierung und partielle Auswertung von funktional-logischen Programmen

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

Ensuring Global Termination of Partial Deduction while Allowing Flexible Polyvariance

The control of polyvariance is a key issue in partial deduction of logic programs. Certainly, only finitely many specialised versions of any procedure should be generated, while, on the other hand, overly severe limitations should not be imposed. In this paper, well-founded orderings serve as a starting point for tackling this so-called "global termination" problem. Polyvariance is determined by the set of distinct "partially deduced" atoms generated during partial deduction. Avoiding ad-hoc techniques, we formulate a quite general framework where this set is represented as a tree structure. Associating weights with nodes, we define a well-founded order among such structures, thus obtaining a foundation for certified global termination of partial deduction. We include an algorithm template, concrete instances of which can be used in actual implementations, prove termination and correctness, and report on the results of some experiments. Finally, we conjecture that the proposed framewor..

Ensuring global termination of partial deduction while allowing flexible polyvariance

status: publishe

Ensuring Global Termination of Partial Deduction while Allowing Flexible Polyvariance

The control of polyvariance is a key issue in partial deduction of logic programs. Certainly, only finitely many specialised versions of any procedure should be generated, while, on the other hand, overly severe limitations should not be imposed. In this paper, well-founded orderings serve as a starting point for tackling this so-called "global termination" problem. Polyvariance is determined by the set of distinct "partially deduced" atoms generated during partial deduction. Avoiding ad-hoc techniques, we formulate a quite general framework where this set is represented as a tree structure. Associating weights with nodes, we define a well-founded order among such structures, thus obtaining a foundation for certified global termination of partial deduction. We include an algorithm template, concrete instances of which can be used in actual implementations, prove termination and correctness, and report on the results of some experiments. Finally, we conjecture that the proposed framewor..