First-order unification by structural recursion

Functional Reactive Programming (FRP) is an approach to reactive programming where systems are structured as networks of functions operating on signals. FRP is based on the synchronous data-flow paradigm and supports both continuous-time and discrete-time signals (hybrid systems). What sets FRP apart from most other languages for similar applications is its support for systems with dynamic structure and for higher-order reactive constructs.Statically guaranteeing correctness properties of programs is an attractive proposition. This is true in particular for typical application domains for reactive programming such as embedded systems. To that end, many existing reactive languages have type systems or other static checks that guarantee domain-specific properties, such as feedback loops always being well-formed. However, they are limited in their capabilities to support dynamism and higher-order data-flow compared with FRP. Thus, the onus of ensuring such properties of FRP programs has so far been on the programmer as established static techniques do not suffice.In this paper, we show how dependent types allow this concern to be addressed. We present an implementation of FRP embedded in the dependently-typed language Agda, leveraging the type system of the host language to craft a domain-specific (dependent) type system for FRP. The implementation constitutes a discrete, operational semantics of FRP, and as it passes the Agda type, coverage, and termination checks, we know the operational semantics is total, which means our type system is safe.

We propose a representation of interactive systems in dependent type theory. This is meant as a basis for an execution environment for dependently typed programs, and for reasoning about their construction. The inspiration is the ‘I/O-monad’ of Haskell. The fundamental notion is an I/O-tree; its definition is parameterised over a general notion of dependently typed, command-response interactions called a world. I/O-trees represent strategies for one of the parties in a command/response interaction - the notion is not confined to functional programming. We present I/O-trees in two forms. The first form, which is simpler, is suitable for Turing-complete functional programming languages with general recursion, but is non-normalising. The second is definable within (ordinary) normalising type theory and we identify programs written in it as ‘normalising I/O-programs’. We define new looping constructs (while and repeat), and a new refinement construct (redirect), which permits the implementation of libraries. We introduce a bisimulation relation between interactive programs, with respect to which we prove the monad laws and defining equations of while. Most definitions in this article make essential use of the expressive strength of dependent typing.KeywordsFunctional programmingreactive programminginteractiondependent typesmonadic I/Orepetition constructsrefinement

Leader election problem is among the important problems in distributed computing. The continued evolution of distributed systems keeps the distributed computing an open area of research. Distributed algorithms are hard to design and much harder to prove. To make designing distributed algorithm easier, we model this latter with a local computations model. Distributed algorithms are formally presented by rewriting rules. Beyond a formal presentation of these algorithms, local computations theory proposes not only a correctness proof by the use of invariants but also a termination proof by the use of the graph mathematical tool-box. Based on both, the local computations model and the mobile agent paradigms, we present in this paper a distributed algorithm that elects a leader and computes a spanning tree in a dynamic graph. Computations in dynamic graphs can be affected by a set of topological events: we address the appearance and the disappearance of places and communication channels. Our goal is to always maintain a tree by a single leader or a forest of sub-trees where each one has its own leader.

In this paper a language-based approach to functionally correct imperative programming is proposed. The approach is based on a programming language called RSP1, which combines dependent types, general recursion, and imperative features in a type-safe way, while preserving decidability of type checking. The methodology used is that of internal verification, where programs manipulate programmer-supplied proofs explicitly as data. The fundamental technical idea of RSP1 is to identify problematic operations as impure, and keep them out of dependent types. The resulting language is powerful enough to verify statically non-trivial properties of imperative and functional programs. The paper presents the ideas through the examples of statically verified merge sort, statically verified imperative binary search trees, and statically verified directed acyclic graphs.

Coq is a proof assistant featuring a tactic-based interactive theorem prover. The latest incarnation comes with over 150 tactics that assist the user in developing a formal proof. These tactics range from the simple and mundane to the ‘allpowerful’. Some examples from the latter category are the omega tactic that solves a goal in Presburger arithmetic and the ring and field tactics that solve identities modulo associativity and commutativity in ring and field structures. This paper presents a new proof tactic that decides equalities and inequalities between terms over lattices. It uses a decision procedure that is a variation on Whitman’s algorithm and is implemented using a technique known as proof by reflection. We will paint the essence of the approach in broad strokes and discuss the use of certified functional programs to aid the automation of formal reasoning. This paper makes three contributions. Firstly it serves an an introduction to using proof by reflection approach Coq. This utilizes the Ltac language and two recent extensions to the Coq system: type classes and the PROGRAM extension. Secondly it gives a certified implementation of Whitman’s algorithm in Coq, with proofs of correctness and termination. Thirdly, the final product of this work is a useable proof tactic that can be applied to proof goals involving equalities and inequalities in lattice theory. The rest of the paper is organized as follows: Section 2 will give a short introduction to Coq, highlighting the concept of a proof term, and will refresh the necessary details of lattice theory. We will give a motivation for the problem in Section 3, and a Coq-based introduction to free lattices along with the decision

Automata learning is a popular technique for inferring minimal automata through membership and equivalence queries. In this paper, we generalise learning to the theory of coalgebras. The approach relies on the use of logical formulas as tests, based on a dual adjunction between states and logical theories. This allows us to learn, e.g., labelled transition systems, using Hennessy-Milner logic. Our main contribution is an abstract learning algorithm, together with a proof of correctness and termination.

I report on an experience using the Coq proof assistant to develop a program verification tool with a machine-checkable proof of full correctness. The verifier is able to prove memory safety of x86 machine code programs compiled from code that uses algebraic datatypes. The tool's soundness theorem is expressed in terms of the bit-level semantics of x86 programs, so its correctness depends on very few assumptions. I take advantage of Coq's support for programming with dependent types and modules in the structure of my development. The approach is based on developing a library of reusable functors for transforming a verifier at one level of abstraction into a verifier at a lower level. Using this library, it's possible to prototype a verifier based on a new type system with a minimal amount of work, while obtaining a very strong soundness theorem about the final product.

Domain theory is the mathematical theory underlying denotational semantics. This thesis presents a formalization of domain theory in the Higher Order Logic (HOL) theorem proving system along with a mechanization of proof functions and other tools to support reasoning about the denotations of functional programs. By providing a fixed point operator for functions on certain domains which have a special undefined (bottom) element, this extension of HOL supports the definition of recursive functions which are not also primitive recursive. Thus, it provides an approach to the long-standing and important problem of defining non-primitive recursive functions in the HOL system.<br /> <br />Our philosophy is that there must be a direct correspondence between elements of complete partial orders (domains) and elements of HOL types, in order to allow the reuse of higher order logic and proof infrastructure already available in the HOL system. Hence, we are able to mix domain theoretic reasoning with reasoning in the set theoretic HOL world to advantage, exploiting HOL types and tools directly. Moreover, by mixing domain and set theoretic reasoning, we are able to eliminate almost all reasoning about the bottom element of complete partial orders that makes the LCF theorem prover, which supports a first order logic of domain theory, difficult and tedious to use. A thorough comparison with LCF is provided.<br /> <br />The advantages of combining the best of the domain and set theoretic worlds in the same system are demonstrated in a larger example, showing the correctness of a unification algorithm. A major part of the proof is conducted in the set theoretic setting of higher order logic, and only at a late stage of the proof domain theory is introduced to give a recursive definition of the algorithm, which is not primitive recursive. Furthermore, a total well-founded recursive unification function can be defined easily in pure HOL by proving that the unification algorithm (defined in domain theory) always terminates; this proof is conducted by a non-trivial well-founded induction. In such applications, where non-primitive recursive HOL functions are defined via domain theory and a proof of termination, domain theory constructs only appear temporarily.

We define a morphism from nominal syntax, which supports binding, to standard (first-order) syntax. We use this morphism to extend Paterson and Wegman’s linear first-order unification algorithm in order to deal with terms modulo alpha-equivalence. The nominal unification algorithm obtained is quadratic in time.

Behavioural equivalence for functional languages with algebraic effects and general recursion is often difficult to formalize. When modelling the behaviour of higher-order programs, one often needs to employ multiple coinductive structures simultaneously. In this paper, we aim to simplify the issue with a single external stream monad dealing with recursion, and deal with the structures for modelling higher-order types in a purely inductive (finite) manner. We take a page from classical domain theory, modelling recursive programs as limits of increasing sequences of “finite” denotational elements. We carry around a single relation which contains all relevant information of behaviour: self-related elements are considered correct according to the denotational semantics, and two elements that are related both ways are considered equivalent. We implement equivalence of effectful programs using a relation lifting, creating a notion of behavioural equivalence for approximations. This is lifted to behavioural equivalence for recursive programs modelled by sequences of approximations, using a relator implementing a notion of weak similarity. We apply this to a fragment of call-by-push-value lambda calculus with algebraic effects, and establish a denotational equivalence which is sound with respect to an operational semantics, and sound with respect to contextual equivalence.KeywordsProgram equivalenceAlgebraic effectsCall-by-push-valueAgda

Parametric polymorphism constrains the behavior of pure functional pro-grams in a way that allows the derivation of interesting theorems about them solely from their types, i.e., virtually for free. The formal background of such ‘free theorems’ is well developed for extensions of the Girard-Reynolds polymorphic lambda calculus by algebraic datatypes and general recursion, provided the resulting calculus is endowed with either a purely strict or a purely nonstrict semantics. But modern functional languages like Clean and Haskell, while using nonstrict evaluation by default, also provide means to enforce strict evaluation of subcomputations at will. The resulting selective strictness gives the advanced programmer explicit control over evaluation order, but is not without semantic consequences: it breaks standard parametricity results. This paper develops an operational semantics for a core calculus supporting all the language features emphasized above. Its main achievement is the characterization of observational approximation with respect to this operational semantics via a carefully constructed logical relation. This establishes the formal basis for new parametricity results, as illustrated by several example applications, including the first complete correctness proof for short cut fusion in the presence of selective strictness. The focus on observational approximation, rather than equivalence, allows a finer-grained analysis of computational behavior in the presence of selective strictness than would be possible with observational equivalence alone.

We consider what we term existence-constrained semi-infinite programs. They contain a finite number of (upper-level) variables, a regular objective, and semi-infinite existence constraints. These constraints assert that for all (medial-level) variable values from a set of infinite cardinality, there must exist (lower-level) variable values from a second set that satisfy an inequality. Existence-constrained semi-infinite programs are a generalization of regular semi-infinite programs, possess three rather than two levels, and are found in a number of applications. Building on our previous work on the global solution of semi-infinite programs (Djelassi and Mitsos in J Glob Optim 68(2):227–253, 2017), we propose (for the first time) an algorithm for the global solution of existence-constrained semi-infinite programs absent any convexity or concavity assumptions. The algorithm is guaranteed to terminate with a globally optimal solution with guaranteed feasibility under assumptions that are similar to the ones made in the regular semi-infinite case. In particular, it is assumed that host sets are compact, defining functions are continuous, an appropriate global nonlinear programming subsolver is used, and that there exists a Slater point with respect to the semi-infinite existence constraints. A proof of finite termination is provided. Numerical results are provided for the solution of an adjustable robust design problem from the chemical engineering literature.

Auxiliary variables in partial correctness programming logics

This work develops a novel power control framework for energy-efficient power control in wireless networks. The proposed method is a new branch-and-bound procedure based on problem-specific bounds for energy-efficiency maximization that allow for faster convergence. This enables to find the global solution for all of the most common energy-efficient power control problems with a complexity that, although still exponential in the number of variables, is much lower than other available global optimization frameworks. Moreover, the reduced complexity of the proposed framework allows its practical implementation through the use of deep neural networks. Specifically, thanks to its reduced complexity, the proposed method can be used to train an artificial neural network to predict the optimal resource allocation. This is in contrast with other power control methods based on deep learning, which train the neural network based on suboptimal power allocations due to the large complexity that generating large training sets of optimal power allocations would have with available global optimization methods. As a benchmark, we also develop a novel first-order optimal power allocation algorithm. Numerical results show that a neural network can be trained to predict the optimal power allocation policy.

We present an algorithm for unification of higher-order patterns modulo simple syntactic equational theories as defined by Kirchner [14]. The algorithm by Miller [17] for pattern unification, refined by Nipkow [18] is first modified in order to behave as a first-order unification algorithm. Then the mutation rule for syntactic theories of Kirchner [13,14] is adapted to pattern E-unification. If the syntactic algorithm for a theory E terminates in the first-order case, then our algorithm will also terminate for pattern E-unification. The result is a DAG-solved form plus some equations of the form λ øverlinex.F(øverlinex) = λ øverlinex. F(øverlinex^π ) where øverlinex^π is a permutation of øverlinex When all function symbols are decomposable these latter equations can be discarded, otherwise the compatibility of such equations with the solved form remains open.