Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: New Results

Automated and Interactive Theorem Proving

Participants : Gabor Alági, Haniel Barbosa, Jasmin Christian Blanchette, Martin Bromberger, Simon Cruanes, Pablo Dobal, Mathias Fleury, Pascal Fontaine, Maximilian Jaroschek, Marek Košta, Stephan Merz, Martin Riener, Thomas Sturm, Hernán Pablo Vanzetto, Uwe Waldmann, Daniel Wand, Christoph Weidenbach.

Combination of Satisfiability Procedures

Joint work with Christophe Ringeissen from the CASSIS project-team at Inria Nancy – Grand Est, and Paula Chocron, a student at the University of Buenos Aires.

A satisfiability problem is often expressed in a combination of theories, and a natural approach consists in solving the problem by combining the satisfiability procedures available for the component theories. This is the purpose of the combination method introduced by Nelson and Oppen. However, in its initial presentation, the Nelson-Oppen combination method requires the theories to be signature-disjoint and stably infinite (to ensure the existence of an infinite model). The design of a generic combination method for non-disjoint unions of theories is clearly a hard task, but it is worth exploring simple non-disjoint combinations that appear frequently in verification. An example is the case of shared sets, where sets are represented by unary predicates. Another example is the case of bridging functions between data structures and a target theory (e.g., a fragment of arithmetic).

We defined [24] a sound and complete combination procedure à la Nelson-Oppen for the theory of absolutely free data structures (including lists and trees) connected to another theory via bridging functions. This combination procedure has also been refined for standard interpretations. The resulting theory has a nice politeness property, enabling combinations with arbitrary decidable theories of elements. We also investigated [25] other theories amenable to similar combinations: this class includes the theory of equality, the theory of absolutely free data structures, and all the theories in between.

Adapting Real Quantifier Elimination Methods for Conflict Set Computation

The satisfiability problem in real closed fields is decidable. In the context of satisfiability modulo theories, the problem restricted to conjunctive sets of literals, that is, sets of polynomial constraints, is of particular importance. One of the central problems is the computation of good explanations of the unsatisfiability of such sets, i.e. obtaining a small subset of the input constraints whose conjunction is already unsatisfiable. We have adapted two commonly used real quantifier elimination methods, cylindrical algebraic decomposition and virtual substitution, to provide such conflict sets and demonstrate the performance of our method in practice [27] .

Codatatypes and Corecursion

Joint work with Andrei Popescu and Dmitriy Traytel (Technische Universität München) and Andrew Reynolds (EPFL).

Datatypes and codatatypes are useful for specifying and reasoning about (possibly infinite) computational processes. The Isabelle/HOL proof assistant is being extended with flexible and convenient support for (co)datatypes and (co)recursive functions on them. We extended the emergent framework for (co)codatatypes with automatic generation of nonemptiness witnesses [22] , nonemptiness being a proviso for introducing types in many logics, including Isabelle's higher-order logic. As a theoretical step towards a definitional mechanism in Isabelle, we formalized a framework for defining corecursive functions safely, based on corecursion up-to and relational parametricity [21] . The end product is a general corecursor that allows corecursive (and even recursive) calls under “friendly” operations—an improvement over the inflexible syntactic criteria of systems such as Agda and Coq.

In a related line of work, we improved the automation of the SMT solver CVC4 by designing, implementing, and evaluating a combined decision procedure for datatypes and codatatypes [31] . The procedure decides universal problems and is composable via the Nelson–Oppen method, as implemented in SMT solvers. The decision procedure for (co)datatypes is useful both for proving and for model finding. We have commenced work on a higher-order model finder based on CVC4, called Nunchaku, that relies heavily on the decision procedure.

Analysis and Generation of Structured Proofs

Joint work with Sascha Böhme (QAware GmbH), Maximilian Haslbeck and Tobias Nipkow (Technische Universität München), Daniel Matichuk (NICTA), and Steffen J. Smolka (Cornell University).

Isabelle/HOL is probably the most widely used proof assistant besides Coq. The Archive of Formal Proofs is a vast collection of computer-checked proofs developed using Isabelle, containing nearly 65 000 lemmas. We performed an in-depth analysis of the archive, looking at various properties of the proof developments, including size, dependencies, and proof style [18] . This give some insights into the nature of formal proofs.

In the context of the Sledgehammer bridge between automatic theorem provers and proof assistants, we designed a translation of machine-generated proofs into (semi-)intelligible Isabelle proofs that users can simply insert into their proof texts to discharge proof obligations [16] . While the output is designed for certifying the machine-generated proofs, it also has a pedagogical value: Unlike Isabelle's automatic tactics, which are black boxes, the proofs delivered by Sledgehammer can be inspected and understood. The direct proofs also form a good basis for manual tuning.

Encoding Set-Theoretic Formulas in Many-Sorted First-Order Logic

TLA+ is a language for the formal specification of systems and algorithms whose first-order kernel is a variant of untyped Zermelo-Fraenkel set theory. Typical proof obligations that arise during the verification of TLA+ specifications mix reasoning about sets, functions, arithmetic, tuples, and records. Encoding such formulas in the input languages of standard first-order provers (SMT solvers or superposition-based provers for first-order logic) is paramount for obtaining satisfactory levels of automation. For set theory, the basic idea is to represent membership as an uninterpreted predicate for the backend provers, and to reduce set-theoretic expressions to this basic predicate. This is not straightforward for formulas involving set comprehension or for proofs that rely on extensionality for inferring equality of sets. Moreover, a full development of set-theoretic expressions may lead to large formulas that can overwhelm backend provers. We describe a technique that transforms set-theoretic formulas by successively applying rewriting and abstraction until a fixed point is reached. The technique is extended to handling functions, records, and tuples, and it is the kernel of the SMT backend of the TLA+ proof system (section 6.3 ). A paper describing our technique has been presented at the SETS workshop 2015 [46] .

Although the approach was mainly intended to support proofs, we have also started work on adapting it for constructing models of formulas in set theory. Being able to construct (counter-)models can help users understand why proof attempts fail. During his internship, Glen Mével from ENS Rennes designed translation rules for a core fragment of TLA+ set theory. He validated them by using the finite model finding functionality of the SMT solver CVC4 for constructing models, with encouraging preliminary results.

Linear Constraints in Integer Arithmetic

We have investigated linear integer constraint solving. Many existing algorithms rely on solving the rational relaxation and transferring the results to an integer branch and bound approach. This algorithm eventually terminates due to the well-known a priori exponential bounds of an integer solution. De Moura and Jovanović proposed the first model-driven terminating algorithm where the termination relies on the structure of the problem itself but not on a priori bounds [62] . However, the algorithm contained some bugs, in particular it did not terminate. We fixed the bugs by introducing the notion of Weak Cooper elimination. Termination requires adding more rules to the algorithm and refining some existing ones [23] .

Decidability of First-Order Clause Sets

Recursion is a necessary source for first-order undecidability of clause sets. If there are no cyclic, i.e., recursive definitions of predicates in such a clause set, (ordered) resolution terminates, showing decidability. In this work we present the first characterization of recursive clause sets enabling non-constant function symbols and depth increasing clauses but still preserving decidability. For this class called BDI (Bounded Depth Increase) we present a specialized superposition calculus. This work was published in the Journal of Logic and Computation [63] . Recursive clause sets also become decidable in the context of finite domain axioms. For this case we developped a new calculus that incorporates explicit partial model assumptions guiding the search [19] .

Building Blocks for Automated Reasoning

There are automated reasoning building blocks shared between today's prime calculi for propositional logic (CDCL), propositional logic modulo theories (CDCL(T)), and first-order logic with equality (superposition). Underlying all calculi is a partial model assumption guiding inferences that are not redundant. Deciding the abstract redundancy notion is basically as difficult as the overall satisfiability problem for the respective logic, but for well-chosen partial model assumptions inferences can be guaranteed to be non-redundant at much lower cost. For example, for SAT it is possible to computed inferences in linear time [40] that are guaranteed to be non-redundant.

Beagle – A Hierarchic Superposition Prover

Joint work with Peter Baumgartner and Joshua Bax from NICTA, Canberra, Australia.

Hierarchic superposition is a calculus for automated reasoning in first-order logic extended by some background theory. In [20] we describe an implementation of hierarchic superposition within the Beagle theorem prover, and report on Beagle's performance on the TPTP problem library. Currently implemented background theories are linear integer and linear rational arithmetic. Beagle features new simplification rules for theory reasoning and implements calculus improvements like weak abstraction and determining (un)satisfiability w.r.t. quantification over finite integer domains.

Modal Tableau Systems with Blocking and Congruence Closure

Joint work with Renate A. Schmidt from the University of Manchester, UK.

For many common modal and description logics there are ways to avoid the explicit use of equality in a tableau calculus. For more expressive logics, e.g., with nominals as in hybrid modal logics and description logics, avoiding equality becomes harder, though, and for modal logics where the binary relations satisfy frame conditions expressible as first-order formulae with equality, explicit handling of equations is the easiest and sometimes the only known way to perform equality reasoning. In [32] we describe an approach for efficient handling of equality in tableau systems. We combine Smullyan-style tableaux with a congruence closure algorithm, and demonstrate that this method also permits the use of common blocking restrictions such as ancestor blocking.

Subtropical Real Root Finding

This research is motivated by a series of studies of Hopf bifurcations [60] , [59] for reaction systems in chemistry and gene regulatory networks in systems biology. The relevant systems are originally given in terms of ordinary differential equations, for which Hopf bifurcations can be described algebraically [54] , [74] , [58] , [57] , typically resulting in one very large multivariate polynomial equation f=0 subject to a few much simpler polynomial side conditions g1>0, ..., gn>0. For these algebraic systems one is interested in feasibility over the reals and, in the positive case, in at least one feasible point. It turns out that, generally, scientifically meaningful information can be obtained already by checking only the feasibility of f=0, which is the focus of this project. For further details on the motivating problems, we refer to our earlier publications [72] , [71] , [56] , [55] .

With one of our models, viz. Mitogen-activated protein kinase (MAPK), we obtain and solve polynomials of considerable size. Our currently largest instance mapke5e6 contains 863,438 monomials in 10 variables. One of the variables occurs with degree 12, all other variables occur with degree 5. Such problem sizes are clearly beyond the scope of classical methods in symbolic computation. To give an impression, the size of an input file with mapke5e6 in infix notation is 30 MB large. LaTeX-formatted printing of mapke5e6 would fill more than 5000 pages in this report.

We have developed an incomplete but terminating algorithm for finding real roots of large multivariate polynomials [33] . The principal idea is to take an abstract view of the polynomial as the set of its exponent vectors supplemented with sign information on the corresponding coefficients. To that extent, out approach is quite similar to tropical algebraic geometry [73] . However, after our abstraction we do not consider tropical varieties but employ linear programming to determine certain suitable points in the Newton polytope, which somewhat resembles successful approaches to sum-of-square decompositions [67] .

We have implemented our approach in Reduce [61] using direct function calls to the dynamic library of the LP solver Gurobi [48] . In practical computations on several hundred examples originating from the work within an interdisciplinary research group our method has failed due to its incompleteness in only 10 percent of the cases. The longest computation time observed was around 16 s for the above-mentioned mapke5e6 . With a publication of our computational results in a physics journal, our research had considerable impact beyond computer science [17] .

Standard Answers for Virtual Substitution

Joint work with A. Dolzmann from Leibniz-Zentrum für Informatik in Saarbrücken, Germany.

We consider existential problems over the reals. Extended quantifier elimination generalizes the concept of regular quantifier elimination by additionally providing answers which are descriptions of possible assignments for the quantified variables. Implementations of extended quantifier elimination via virtual substitution have been successfully applied to various problems in science and engineering.

So far, the answers produced by these implementations included infinitesimal and infinite numbers, which are hard to interpret in practice. This has been explicitly criticized in the scientific literature. In our article [44] , we introduce a complete post-processing procedure to convert, for fixed values of parameters, all answers into standard real numbers. We furthermore demonstrate the successful application of an implementation of our method within Redlog to a number of extended quantifier elimination problems from the scientific literature including computational geometry, motion planning, bifurcation analysis for models of genetic circuits and for mass action, and sizing of electrical networks.

A Generalized Framework for Virtual Substitution

We generalize the framework of virtual substitution for real quantifier elimination to arbitrary but bounded degrees [45] . We make explicit the representation of test points in elimination sets using roots of parametric univariate polynomials described by Thom codes. Our approach follows an early suggestion by Weispfenning, which has never been carried out explicitly.

We give necessary and sufficient conditions for the existence of a root with a given test point representation. These conditions are used to rule out redundant test points. Our encoding allows us to distinguish between test points that represent lower bounds and test points representing upper bounds of a satisfying interval for a given input formula. Furthermore, we show how to reduce the size of elimination sets by generalizing a well-known idea from linear virtual substitution, namely to consider only test points representing lower bounds of a satisfying interval.

Our framework relies on some external algorithm 𝒜, which is used to eliminate a single existential quantifier from a finite set of generic formulas. The existence of 𝒜 is guaranteed by the fact that admits quantifier elimination. We briefly refer to experiments which compared the performance of our framework—when Cylindrical Algebraic Decomposition is used as the external algorithm—to other quantifier elimination algorithms. Unfortunately, our approach is not yet able to compete with other state-of-the-art quantifier elimination algorithms. However, currently ongoing research suggests the possibility for drastic improvements in practice. Investigating this is left for future work.