Polynomial Interpretations over the Natural, Rational and Real Numbers Revisited

Polynomial interpretations are a useful technique for proving termination of term rewrite systems. They come in various flavors: polynomial interpretations with real, rational and integer coefficients. As to their relationship with respect to termination proving power, Lucas managed to prove in 2006 that there are rewrite systems that can be shown polynomially terminating by polynomial interpretations with real (algebraic) coefficients, but cannot be shown polynomially terminating using polynomials with rational coefficients only. He also proved the corresponding statement regarding the use of rational coefficients versus integer coefficients. In this article we extend these results, thereby giving the full picture of the relationship between the aforementioned variants of polynomial interpretations. In particular, we show that polynomial interpretations with real or rational coefficients do not subsume polynomial interpretations with integer coefficients. Our results hold also for incremental termination proofs with polynomial interpretations.Comment: 28 pages; special issue of RTA 201

Synthesis of sup-interpretations: a survey

In this paper, we survey the complexity of distinct methods that allow the programmer to synthesize a sup-interpretation, a function providing an upper- bound on the size of the output values computed by a program. It consists in a static space analysis tool without consideration of the time consumption. Although clearly related, sup-interpretation is independent from termination since it only provides an upper bound on the terminating computations. First, we study some undecidable properties of sup-interpretations from a theoretical point of view. Next, we fix term rewriting systems as our computational model and we show that a sup-interpretation can be obtained through the use of a well-known termination technique, the polynomial interpretations. The drawback is that such a method only applies to total functions (strongly normalizing programs). To overcome this problem we also study sup-interpretations through the notion of quasi-interpretation. Quasi-interpretations also suffer from a drawback that lies in the subterm property. This property drastically restricts the shape of the considered functions. Again we overcome this problem by introducing a new notion of interpretations mainly based on the dependency pairs method. We study the decidability and complexity of the sup-interpretation synthesis problem for all these three tools over sets of polynomials. Finally, we take benefit of some previous works on termination and runtime complexity to infer sup-interpretations.Comment: (2012

Solving polynomial constraints for proving termination of rewriting

A termination problem can be transformed into a set of polynomial constraints. Up to now, several approaches have been studied to deal with these constraints as constraint solving problems. In this thesis, we study in depth some of these approaches, present some advances in each approach.Navarro Marset, RA. (2008). Solving polynomial constraints for proving termination of rewriting. http://hdl.handle.net/10251/13626Archivo delegad

A Survey of Satisfiability Modulo Theory

Satisfiability modulo theory (SMT) consists in testing the satisfiability of first-order formulas over linear integer or real arithmetic, or other theories. In this survey, we explain the combination of propositional satisfiability and decision procedures for conjunctions known as DPLL(T), and the alternative "natural domain" approaches. We also cover quantifiers, Craig interpolants, polynomial arithmetic, and how SMT solvers are used in automated software analysis.Comment: Computer Algebra in Scientific Computing, Sep 2016, Bucharest, Romania. 201

Polynomials over the reals are safe for program interpretations

In the field of implicit computational complexity, we are con- sidering in this paper the fruitful branch of interpretation methods. Due to their good intensional properties, they have been widely developped. Among usual issues is the synthesis problem which has been solved by the use of Tarski's decision procedure, and consequently interpretations are usually chosen over the reals rather than over the integers. Doing so, one cannot use anymore the (good) properties of the natural (well-) ordering of N employed to bound the complexity of programs. We show that, actually, polynomials over the reals benefit from some properties that allows their safe use for complexity. We illustrate this by two char- acterizations, one of PTIME and one of PSPACE

Efficient Solving of Quantified Inequality Constraints over the Real Numbers

Let a quantified inequality constraint over the reals be a formula in the first-order predicate language over the structure of the real numbers, where the allowed predicate symbols are $\leq$ and $<$. Solving such constraints is an undecidable problem when allowing function symbols such $\sin$ or $\cos$. In the paper we give an algorithm that terminates with a solution for all, except for very special, pathological inputs. We ensure the practical efficiency of this algorithm by employing constraint programming techniques

Models for logics and conditional constraints in automated proofs of termination

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-13770-4_3Reasoning about termination of declarative programs, which are described by means of a computational logic, requires the definition of appropriate abstractions as semantic models of the logic, and also handling the conditional constraints which are often obtained. The formal treatment of such constraints in automated proofs, often using numeric interpretations and (arithmetic) constraint solving can greatly benefit from appropriate techniques to deal with the conditional (in)equations at stake. Existing results from linear algebra or real algebraic geometry are useful to deal with them but have received only scant attention to date. We investigate the definition and use of numeric models for logics and the resolution of linear and algebraic conditional constraints as unifying techniques for proving termination of declarative programs.Developed during a sabbatical year at UIUC. Supported by projects NSF CNS13-19109, MINECO TIN2010-21062-C02-02 and TIN2013-45732-C4-1-P, and GV BEST/2014/026 and PROMETEO/2011/052.Lucas Alba, S.; Meseguer, J. (2014). Models for logics and conditional constraints in automated proofs of termination. En Artificial Intelligence and Symbolic Computation. Springer Verlag (Germany). 9-20. https://doi.org/10.1007/978-3-319-13770-4_3S920Alarcón, B., Gutiérrez, R., Lucas, S., Navarro-Marset, R.: Proving Termination Properties with mu-term. In: Johnson, M., Pavlovic, D. (eds.) AMAST 2010. LNCS, vol. 6486, pp. 201–208. Springer, Heidelberg (2011)Alarcón, B., Lucas, S., Navarro-Marset, R.: Using Matrix Interpretations over the Reals in Proofs of Termination. In: Proc. of PROLE 2009, pp. 255–264 (2009)Clavel, M., Durán, F., Eker, S., Lincoln, P., Martí-Oliet, N., Meseguer, J., Talcott, C. (eds.): All About Maude - A High-Performance Logical Framework. LNCS, vol. 4350. Springer, Heidelberg (2007)Contejean, E., Marché, C., Tomás, A.-P., Urbain, X.: Mechanically proving termination using polynomial interpretations. J. of Aut. Reas. 34(4), 325–363 (2006)Endrullis, J., Waldmann, J., Zantema, H.: Matrix Interpretations for Proving Termination of Term Rewriting. J. of Aut. Reas. 40(2-3), 195–220 (2008)Fuhs, C., Giesl, J., Middeldorp, A., Schneider-Kamp, P., Thiemann, R., Zankl, H.: Maximal Termination. In: Voronkov, A. (ed.) RTA 2008. LNCS, vol. 5117, pp. 110–125. Springer, Heidelberg (2008)Futatsugi, K., Diaconescu, R.: CafeOBJ Report. AMAST Series. World Scientific (1998)Hudak, P., Peyton-Jones, S.J., Wadler, P.: Report on the Functional Programming Language Haskell: a non–strict, purely functional language. Sigplan Notices 27(5), 1–164 (1992)Lucas, S.: Context-sensitive computations in functional and functional logic programs. Journal of Functional and Logic Programming 1998(1), 1–61 (1998)Lucas, S.: Polynomials over the reals in proofs of termination: from theory to practice. RAIRO Theoretical Informatics and Applications 39(3), 547–586 (2005)Lucas, S., Marché, C., Meseguer, J.: Operational termination of conditional term rewriting systems. Information Processing Letters 95, 446–453 (2005)Lucas, S., Meseguer, J.: Proving Operational Termination of Declarative Programs in General Logics. In: Proc. of PPDP 2014, pp. 111–122. ACM Digital Library (2014)Lucas, S., Meseguer, J.: 2D Dependency Pairs for Proving Operational Termination of CTRSs. In: Proc. of WRLA 2014. LNCS, vol. 8663 (to appear, 2014)Lucas, S., Meseguer, J., Gutiérrez, R.: Extending the 2D DP Framework for CTRSs. In: Selected papers of LOPSTR 2014. LNCS (to appear, 2015)Meseguer, J.: General Logics. In: Ebbinghaus, H.-D., et al. (eds.) Logic Colloquium 1987, pp. 275–329. North-Holland (1989)Nguyen, M.T., de Schreye, D., Giesl, J., Schneider-Kamp, P.: Polytool: Polynomial interpretations as a basis for termination of logic programs. Theory and Practice of Logic Programming 11(1), 33–63 (2011)Ohlebusch, E.: Advanced Topics in Term Rewriting. Springer (April 2002)Prestel, A., Delzell, C.N.: Positive Polynomials. In: From Hilbert’s 17th Problem to Real Algebra. Springer, Berlin (2001)Podelski, A., Rybalchenko, A.: A Complete Method for the Synthesis of Linear Ranking Functions. In: Steffen, B., Levi, G. (eds.) VMCAI 2004. LNCS, vol. 2937, pp. 239–251. Springer, Heidelberg (2004)Schrijver, A.: Theory of linear and integer programming. John Wiley & Sons (1986)Zantema, H.: Termination of Context-Sensitive Rewriting. In: Comon, H. (ed.) RTA 1997. LNCS, vol. 1232, pp. 172–186. Springer, Heidelberg (1997

On the Termination of Linear and Affine Programs over the Integers

The termination problem for affine programs over the integers was left open in\cite{Braverman}. For more that a decade, it has been considered and cited as a challenging open problem. To the best of our knowledge, we present here the most complete response to this issue: we show that termination for affine programs over Z is decidable under an assumption holding for almost all affine programs, except for an extremely small class of zero Lesbegue measure. We use the notion of asymptotically non-terminating initial variable values} (ANT, for short) for linear loop programs over Z. Those values are directly associated to initial variable values for which the corresponding program does not terminate. We reduce the termination problem of linear affine programs over the integers to the emptiness check of a specific ANT set of initial variable values. For this class of linear or affine programs, we prove that the corresponding ANT set is a semi-linear space and we provide a powerful computational methods allowing the automatic generation of these $ANT$ sets. Moreover, we are able to address the conditional termination problem too. In other words, by taking ANT set complements, we obtain a precise under-approximation of the set of inputs for which the program does terminate.Comment: arXiv admin note: substantial text overlap with arXiv:1407.455