We start with a mathematical definition of a real interval as a closed, connected set of reals. Interval arithmetic operations (addition, subtraction, multiplication and division) are likewise defined mathematically and we provide algorithms for computing these operations assuming exact real arithmetic. Next, we define interval arithmetic operations on intervals with IEEE 754 floating point endpoints to be sound and optimal approximations of the real interval operations and we show that the IEEE standard’s specification of operations involving the signed infinities, signed zeros, and the exact/inexact flag are such as to make a correct and optimal implementation more efficient. From the resulting theorems we derive data that are sufficiently detailed to convert directly to a program for efficiently implementing the interval operations. Finally we extend these results to the case of general intervals, which are defined as connected sets of reals that are not necessarily closed. 1

CLIP is an implementation of CLP(Intervals) which has been designed to be verifiably correct in the sense that the answers it returns are mathematically correct solutions to the underlying arithmetic constraints. This fundamental design criteria affects many aspects of the implementation from the input and output of decimal constants to the design of the interval arithmetic libraries and the constraint solving algorithms. In particular, to enhance verifiability, CLIP employs the simplest model of constraint solving in which constraints are decomposed into sets of primitive constraints which are then solved using a library of primitive constraint contractors. This approach results in a simple constraint solver whose correctness is relatively straightforward to verify, but the solver is only able to solve relatively simple constraints. In this paper, we present the syntax, semantics, and implementation of CLIP, and we show how to use metalevel techniques to enhance the power of the CLIP constraint solver while preserving the simple structure of the system. In particular, we demonstrate that several of the box-narrowing algorithms from the Newton and Numerica systems can be easily implemented in CLIP. The principal advantages of this approach are (1) the resulting solvers are relatively easy to prove correct, (2) new solvers can be rapidly prototyped since the code is more concise and declarative than for imperative languages, and (3) contractors can be implemented directly from mathematical formulae without having to first prove results about interval arithmetic operators. Finally, the source code for the system is publicly available, which is a clear prerequisite for public, independent verifiability.

Abstract This paper presents a branching schema for the solving of a wide range of interval constraint satisfaction problems defined on any domain of computation, finite or infinite, provided the domain forms a lattice. After a formal definition of the branching schema, useful and interesting properties, satisfied by all instances of the schema, are presented. Examples are then used to illustrate how a range of operational behaviors can be modelled by means of different schema instantiations. It is shown how the operational procedures of many constraint systems (including cooperative systems) can be viewed as instances of this branching schema. Basic directives to adapt this schema to solving constraint optimization problems are also provided.

CLIP is an implementation of CLP(Intervals) which has been designed to be veriably correct in the sense that the answers it returns are mathematically correct solutions to the underlying arithmetic constraints. This fundamental design criteria aects many aspects of the implementation from the input and output of decimal constants to the design of the interval arithmetic libraries and the constraint solving algorithms. In particular, to enhance veriability, CLIP employs the simplest model of constraint solving in which constraints are decomposed into sets of primitive constraints which are then solved using a library of primitive constraint contractors. This approach results in a simple constraint solver whose correctness is relatively straightforward to verify, but the solver is only able to solve relatively simple constraints. In this paper, we present the syntax, semantics, and implementation of CLIP, and we show how to use metalevel techniques to enhance the power of the CLIP constraint solver while preserving the simple structure of the system. In particular, we demonstrate that several of the box-narrowing algorithms from the Newton and Numerica systems can be easily implemented in CLIP. The principal advantages of this approach are (1) the resulting solvers are relatively easy to prove correct, (2) new solvers can be rapidly prototyped since the code is more concise and declarative than for imperative languages, and (3) contractors can be implemented directly from mathematical formulae without having to rst prove results about interval arithmetic operators. Finally, the source code for the system is publicly available, which is a clear prerequisite for public, independent veriability. 1

We use an interval-based Analytic Constraint Logic Programming (ACLP) language to accurately and declaratively model Hybrid Systems. In particular, we model the continuous part of Hybrid Systems using Ordinary Di#erential Equation (ODE) constraints on function variables. Because we make intervals ubiquitous, error bars in measurements and ODE parameters can be modeled explicitly in a natural manner.

This paper focuses on the branching process for solving any constraint satisfaction problem (CSP). A parametrised schema is proposed that (with suitable instantiations of the parameters) can solve CSP's on both finite and infinite domains. The paper presents a formal specification of the schema and a statementofanumber of interesting properties that, subject to certain conditions, are satisfied by any instances of the schema. It is also shown that the operational procedures of many constraint systems (including cooperative systems) satisfy these conditions. Moreover, the schema is also used to solve the same CSP in different ways by means of different instantiations of its parameters.

We introduce an extension of linear constraints, called linearrange constraints, which allows for (meta-)reasoning about the approximation width of variables. Semantics for linearrange constraints is provided in terms of parameterized linear systems. We devise procedures for checking satisfiability and for entailing the maximal width of a variable. An extension of the constraint logic programming language CLP(R) is proposed by admitting linear-range constraints.

We use an interval-based Analytic Constraint Logic Programming (ACLP) language to accurately and declaratively model Hybrid Systems. In particular, we model the continuous part of Hybrid Systems using Ordinary Di#erential Equation (ODE) constraints on function variables. Because we make intervals ubiquitous, error bars in measurements and ODE parameters can be modeled explicitly in a natural manner. There are