Linear Arithmetic Constraints Research Articles

Approximate Integer Solution Counts over Linear Arithmetic Constraints

Counting integer solutions of linear constraints has found interesting applications in various fields. It is equivalent to the problem of counting lattice points inside a polytope. However, state-of-the-art algorithms for this problem become too slow for even a modest number of variables. In this paper, we propose a new framework to approximate the lattice counts inside a polytope with a new random-walk sampling method. The counts computed by our approach has been proved approximately bounded by a (epsilon, delta)-bound. Experiments on extensive benchmarks show that our algorithm could solve polytopes with dozens of dimensions, which significantly outperforms state-of-the-art counters.

Monitoring Arithmetic Temporal Properties on Finite Traces

We study monitoring of linear-time arithmetic properties against finite traces generated by an unknown dynamic system. The monitoring state is determined by considering at once the trace prefix seen so far, and all its possible finite-length, future continuations. This makes monitoring at least as hard as satisfiability and validity. Traces consist of finite sequences of assignments of a fixed set of variables to numerical values. Properties are specified in a logic we call ALTLf, combining LTLf (LTL on finite traces) with linear arithmetic constraints that may carry lookahead, i.e., variables may be compared over multiple instants of the trace. While the monitoring problem for this setting is undecidable in general, we show decidability for (a) properties without lookahead, and (b) properties with lookahead that satisfy the abstract, semantic condition of finite summary, studied before in the context of model checking. We then single out concrete, practically relevant classes of constraints guaranteeing finite summary. Feasibility is witnessed by a prototype implementation.

Leveraging polyhedral reductions for solving Petri net reachability problems

We propose a new method that takes advantage of structural reductions to accelerate the verification of reachability properties on Petri nets. Our approach relies on a state space abstraction, called polyhedral abstraction, which involves a combination between structural reductions and sets of linear arithmetic constraints between the marking of places. We propose a new data structure, called a Token Flow Graph (TFG), that captures the particular structure of constraints occurring in polyhedral abstractions. We leverage TFGs to efficiently solve two reachability problems: first to check the reachability of a given marking and then to compute the concurrency relation of a net, that is, all pairs of places that can be marked together in some reachable marking. Our algorithms are implemented in a tool, called Kong, that we evaluate on a large collection of models used during the 2020 edition of the Model Checking Contest. Our experiments show that the approach works well, even when a moderate amount of reductions applies.

MERRIN: MEtabolic regulation rule INference from time series data.

Many techniques have been developed to infer Boolean regulations from a prior knowledge network (PKN) and experimental data. Existing methods are able to reverse-engineer Boolean regulations for transcriptional and signaling networks, but they fail to infer regulations that control metabolic networks. We present a novel approach to infer Boolean rules for metabolic regulation from time-series data and a PKN. Our method is based on a combination of answer set programming and linear programming. By solving both combinatorial and linear arithmetic constraints, we generate candidate Boolean regulations that can reproduce the given data when coupled to the metabolic network. We evaluate our approach on a core regulated metabolic network and show how the quality of the predictions depends on the available kinetic, fluxomics or transcriptomics time-series data. Software available at https://github.com/bioasp/merrin. Supplementary data are available at https://doi.org/10.5281/zenodo.6670164.

New techniques for linear arithmetic: cubes and equalities

We present several new techniques for linear arithmetic constraint solving. They are all based on the linear cube transformation, a method presented here, which allows us to efficiently determine whether a system of linear arithmetic constraints contains a hypercube of a given edge length. Our first findings based on this transformation are two sound tests that find integer solutions for linear arithmetic constraints. While many complete methods search along the problem surface for a solution, these tests use cubes to explore the interior of the problems. The tests are especially efficient for constraints with a large number of integer solutions, e.g., those with infinite lattice width. Inside the SMT-LIB benchmarks, we have found almost one thousand problem instances with infinite lattice width. Experimental results confirm that our tests are superior on these instances compared to several state-of-the-art SMT solvers. We also discovered that the linear cube transformation can be used to investigate the equalities implied by a system of linear arithmetic constraints. For this purpose, we developed a method that computes a basis for all implied equalities, i.e., a finite representation of all equalities implied by the linear arithmetic constraints. The equality basis has several applications. For instance, it allows us to verify whether a system of linear arithmetic constraints implies a given equality. This is valuable in the context of Nelson–Oppen style combinations of theories.

An Efficient Approach for Solving Optimization over Linear Arithmetic Constraints

Satisfiability Modulo Theories (SMT) have been widely investigated over the last decade. Recently researchers have extended SMT to the optimization problem over linear arithmetic constraints. To the best of our knowledge, Symba and OPT-MathSAT are two most efficient solvers available for this problem. The key algorithms used by Symba and OPT-MathSAT consist of the loop of two procedures: 1) critical finding for detecting a critical point, which is very likely to be globally optimal, and 2) global checking for confirming the critical point is really globally optimal. In this paper, we propose a new approach based on the Simplex method widely used in operation research. Our fundamental idea is to find several critical points by constructing and solving a series of linear problems with the Simplex method. Our approach replaces the algorithms of critical finding in Symba and OPT-MathSAT, and reduces the runtime of critical finding and decreases the number of executions of global checking. The correctness of our approach is proved. The experiment evaluates our implementation against Symba and OPT-MathSAT on a critical class of problems in real-time systems. Our approach outperforms Symba on 99.6% of benchmarks and is superior to OPT-MathSAT in large-scale cases where the number of tasks is more than 24. The experimental results demonstrate that our approach has great potential and competitiveness for the optimization problem.

Parallelizing simplex within SMT solvers

The usual approach in parallelizing SAT and SMT solvers is either to explore different parts of the search space in parallel (divide-and-conquer approach) or to run multiple instances of the same solver with suitably altered parameters in parallel, possibly exchanging some information during the solving process (parallel portfolio approach). Quite a different approach is to parallelize the execution of time-consuming algorithms that check for satisfiability and propagations during the search space exploration. Since most of the execution time is spent in these procedures, their efficient parallelization might be a promising research direction. In this paper we present our experience in parallelizing the simplex algorithm which is typically used in the SMT context to check the satisfiability of linear arithmetic constraints. We provide a detailed description of this approach and present experimental results that evaluate the potential of the approach compared to the parallel portfolio approach. We also consider the combination of the two approaches.

Proving correctness of imperative programs by linearizing constrained Horn clauses

AbstractWe present a method for verifying the correctness of imperative programs which is based on the automated transformation of their specifications. Given a programprog, we consider a partial correctness specification of the form {ϕ},prog{ψ}, where the assertions ϕ and ψ are predicates defined by a setSpecof possibly recursive Horn clauses with linear arithmetic (LA) constraints in their premise (also calledconstrained Horn clauses). The verification method consists in constructing a setPCof constrained Horn clauses whose satisfiability implies that {ϕ},prog, {ψ} is valid. We highlight some limitations of state-of-the-art constrained Horn clause solving methods, here calledLA-solving methods, which prove the satisfiability of the clauses by looking for linear arithmetic interpretations of the predicates. In particular, we prove that there exist some specifications that cannot be proved valid by any of thoseLA-solving methods. These specifications require the proof of satisfiability of a setPCof constrained Horn clauses that containnonlinear clauses(that is, clauses with more than one atom in their premise). Then, we present a transformation, calledlinearization, that convertsPCinto a set oflinearclauses (that is, clauses with at most one atom in their premise). We show that several specifications that could not be proved valid byLA-solving methods, can be proved valid after linearization. We also present a strategy for performing linearization in an automatic way and we report on some experimental results obtained by using a preliminary implementation of our method.

Distributed Manufacturing Networks

The authors consider optimization problems expressed in Decision Guidance Query Language that may involve linear arithmetic constraints, as well as finite domain and binary variables. They focus on Distributed Manufacturing Network optimization problems in which only a part of the problem is dynamic, i.e., the demand for the output products in a manufacturing network, whereas the rest of the problem is static, i.e., the connectivity graph of the assembly processes and the cost functions of machines. The authors propose the Online Decomposition Algorithm based on offline preprocessing that optimizes each static problem component for discretized values of shared constraint variables, and approximate the optimal aggregated utility functions. The Online Decomposition Algorithm uses the pre-processed approximated aggregated cost functions to decompose the original problem into smaller problems, and utilizes search heuristics for the combinatorial part of the problem based on the pre-processed look-up tables. They also conduct an initial experimental evaluation which shows that the Online Decomposition Algorithm, as compared with Mixed Integer Linear Programming, provides an order of magnitude improvement in terms of both computational time and the quality of found solutions for a class of problems for which pre-processing is possible.

Satisfiability with Index Dependency

We study the Boolean Satisfiability Problem (SAT) restricted on input formulas for which there are linear arithmetic constraints imposed on the indices of variables occurring in the same clause. This can be seen as a structural counterpart of Schaefer’s dichotomy theorem which studies the SAT problem with additional constraints on the assigned values of variables in the same clause. More precisely, let k-SAT(\(m,\mathcal{A}\)) denote the SAT problem restricted on instances of k-CNF formulas, in every clause of which the indices of the last k − m variables are totally decided by the first m ones through some linear equations chosen from \(\mathcal{A}\). For example, if \(\mathcal{A}\) contains i 3 = i 1 + 2i 2 and i 4 = i 2 − i 1 + 1, then a clause of the input to 4-SAT(\(2,\mathcal{A}\)) has the form \(y_{i_1}\lor y_{i_2} \lor y_{i_1+2i_2} \lor y_{i_2-i_1+1}\), with y i being x i or \(\overline{x_i}\). We obtain the following results:

NeVer: a tool for artificial neural networks verification

The adoption of Artificial Neural Networks (ANNs) in safety-related applications is often avoided because it is difficult to rule out possible misbehaviors with traditional analytical or probabilistic techniques. In this paper we present NeVer, our tool for checking safety of ANNs. NeVer encodes the problem of verifying safety of ANNs into the problem of satisfying corresponding Boolean combinations of linear arithmetic constraints. We describe the main verification algorithm and the structure of NeVer. We present also empirical results confirming the effectiveness of NeVer on realistic case studies.

Equality detection for linear arithmetic constraints

Satisfiability modulo theories (SMT) play a key role in verification applications. A crucial SMT problem is to combine separate theory solvers for the union of theories. In previous work, the simplex method is used to determine the solvability of constraint systems and the equalities implied by constraint systems are detected by a multitude of applications of the dual simplex method. We present an effective simplex tableau-based method to identify all implicit equalities such that the simplex method is harnessed to an irreducible minimum. Experimental results show that the method is feasible and effective.

Modeling and Verifying Time Sensitive Security Protocols with Constraints

This paper researches the characteristic of time sensitive protocols and presents a method with simple operations to verify protocols with time stamps and avoid false attacks. Firstly, an extension of π calculus is given to model a time sensitive security protocol. And then, by appending linear arithmetic constraints to the Horn logic model, the extended Horn logic model of security protocols and the modified-version verification method with time constraints are represented. All operations and the strategy of verification are defined for our constraints system. Thirdly, a method is given to determine whether the constraints has a solution or not. Finally, as a result of an experiment, Denning-Sacco protocol with time stamps is verified. The experiment shows that our approach is an innovative and effective method on verifying time sensitive security protocols.

Efficient Symbolic Representations for Arithmetic Constraints in Verification

In this paper we discuss efficient symbolic representations for infinite-state systems specified using linear arithmetic constraints. We give algorithms for constructing finite automata which represent integer sets that satisfy linear constraints. These automata can represent either signed or unsigned integers and have a lower number of states compared to other similar approaches. We present efficient storage techniques for the transition function of the automata and extend the construction algorithms to formulas on both boolean and integer variables. We also derive conditions which guarantee that the pre-condition computations used in symbolic verification algorithms do not cause an exponential increase in the automata size. We experimentally compare different symbolic representations by using them to verify non-trivial concurrent systems. Experimental results show that the symbolic representations based on our construction algorithms outperform the polyhedral representation used in Omega Library, and the automata representation used in LASH.

Bounded Model Checking for Timed Automata

Given a timed automaton M, a linear temporal logic formula φ, and a bound k, bounded model checking for timed automata determines if there is a falsifying path of length k to the hypothesis that M satisfies the specification φ. This problem can be reduced to the satisfiability problem for Boolean constraint formulas over linear arithmetic constraints. We show that bounded model checking for timed automata is complete, and we give lower and upper bounds for the length k of counterexamples. Moreover, we define bounded model checking for networks of timed automata in a compositional way.

Constraint-Based Verification of Parameterized Cache Coherence Protocols

We propose a new method for the parameterized verification of formal specifications of cache coherence protocols. The goal of parameterized verification is to establish system properties for an arbitrary number of caches. In order to achieve this purpose we define abstractions that allow us to reduce the original parameterized verification problem to a control state reachability problem for a system with integer data variables. Specifically, the methodology we propose consists of the following steps. We first define an abstraction in which we only keep track of the number of caches in a given state during the execution of a protocol. Then, we use linear arithmetic constraints to symbolically represent infinite sets of global states of the resulting abstract protocol. For reasons of efficiency, we relax the constraint operations by interpreting constraints over real numbers. Finally, we check parameterized safety properties of abstract protocols using symbolic backward reachability, a strategy that allows us to obtain sufficient conditions for termination for an interesting class of protocols. The latter problem can be solved by using the infinite-state model checker HyTech: Henzinger, Ho, and Wong-Toi, “A model checker for hybrid systems,” Proc. of the 9th International Conference on Computer Aided Verification (CAV'97), Lecture Notes in Computer Science, Springer, Haifa, Israel, 1997, Vol. 1254, pp. 460–463. HyTech handles linear arithmetic constraints using the polyhedra library of Halbwachs and Proy, “Verification of real-time systems using linear relation analysis,” Formal Methods in System Design, Vol. 11, No. 2, pp. 157–185, 1997. By using this methodology, we have automatically validated parameterized versions of widely implemented write-invalidate and write-update cache coherence protocols like Synapse, MESI, MOESI, Berkeley, Illinois, Firefly and Dragon (Handy, The Cache Memory Book, Academic Press, 1993). With this application, we have shown that symbolic model checking tools like HyTech, originally designed for the verification of hybrid systems, can be applied successfully to new classes of infinite-state systems of practical interest.

A symbolic manipulator for automated verification of reactive systems with heterogeneous data types

In this paper, we present the design and implementation of the Composite Symbolic Library, a symbolic manipulator for model checking systems with heterogeneous data types. Our tool provides a common interface for different symbolic representations, such as BDDs, for representing Boolean logic formulas and polyhedral representations for linear arithmetic formulas. Based on this common interface, these data structures are combined using a disjunctive composite representation. We propose several heuristics for efficient manipulation of this composite representation and present experimental results that demonstrate their performance. We used an object-oriented design to implement the Composite Symbolic Library. We imported the CUDD library (a BDD library) and the Omega Library (a linear arithmetic constraint manipulator that uses polyhedral representations) to our tool by writing wrappers around them which conform to our symbolic representation interface. Our tool supports polymorphic verification procedures which dynamically select symbolic representations based on the input specification. Our symbolic representation library can be used as an interface between different symbolic libraries, model checkers, and specification languages. We expect our tool to be useful in integrating different tools and techniques for symbolic model checking, and in comparing their performance.

QOCA: A Constraint Solving Toolkit for Interactive Graphical Applications

We describe an object-oriented constraint solving toolkit, QOCA, designed for interactive graphical applications. It has a simple yet powerful interface based on the i>metric space model for constraint manipulation. In this model interaction with the constraint solver can occur in three ways: a constraint may be added, a constraint may be deleted, or values for designated “edit” variables may be suggested. Currently, QOCA supports linear arithmetic constraints and two different metrics: the square of the Euclidean distance and Manhattan distance. It provides three solvers, all of which rely on keeping the constraints in solved form and relies on novel algorithms for efficient resolving of constraints during direct manipulation. We provide a thorough evaluation of QOCA, both of the interface design and the speed of constraint solving.

The Cassowary linear arithmetic constraint solving algorithm

Linear equality and inequality constraints arise naturally in specifying many aspects of user interfaces, such as requiring that one window be to the left of another, requiring that a pane occupy the leftmost third of a window, or preferring that an object be contained within a rectangle if possible. Previous constraint solvers designed for user interface applications cannot handle simultaneous linear equations and inequalities efficiently. This is a major limitation, as such systems of constraints arise often in natural declarative specifications. We describe Cassowary---an incremental algorithm based on the dual simplex method, which can solve such systems of constraints efficiently. We have implemented the algorithm as part of a constraint-solving toolkit. We discuss the implementation of the toolkit, its application programming interface, and its performance.

Constraint-based document layout for the Web

Constraints can be used to specify declaratively the desired layout of a Web document. We present a system architecture in which both the author and the viewer can impose page layout constraints, some required and some preferential. The final appearance of the Web page is thus the result of negotiation between author and viewer, where this negotiation is carried out by solving the set of required and preferential constraints imposed by both parties. We identify two plausible system architectures, based on different ways of dividing the work of constraint solving between Web server and Web client. We describe a prototype constraint-based Web authoring system and viewing tool that provides linear arithmetic constraints for specifying the layout of the document as well as finite-domain constraints for specifying font size relationships. Finally, we provide an empirical evaluation of the prototype.