Derivation of graph and pointer algorithms

We introduce operators and laws of an algebra of formal languages, a subalgebra of which corresponds to the algebra of (multiary) relations. This algebra is then used in the formal specification and derivation of some graph and pointer algorithms

Derivation of data intensive algorithms by formal transformation: the Schorr-Waite graph marking algorithm

Dated September 19, 1996In this paper we consider a particular class of algorithms which present certain difficulties to formal verification. These are algorithms which use a single data structure for two or more purposes, which combine program control information with other data structures or which are developed as a combination of a basic idea with an implementation technique. Our approach is based on applying proven semantics-preserving transformation rules in a wide spectrum language. Starting with a set theoretical specification of “reachability” we are able to derive iterative and recursive graph marking algorithms using the “pointer switching” idea of Schorr and Waite. There have been several proofs of correctness of the Schorr-Waite algorithm, and a small number of transformational developments of the algorithm. The great advantage of our approach is that we can derive the algorithm from its specification using only general-purpose transformational rules: without the need for complicated induction arguments. Our approach applies equally well to several more complex algorithms which make use of the pointer switching strategy, including a hybrid algorithm which uses a fixed length stack, switching to the pointer switching strategy when the stack runs out

Provably Correct Derivation of Algorithms Using FermaT

The transformational programming method of algorithm derivation starts with a formal specification of the result to be achieved, plus some informal ideas as to what techniques will be used in the implementation. The formal specification is then transformed into an implementation, by means of correctness-preserving refinement and transformation steps, guided by the informal ideas. The transformation process will typically include the following stages: (1) Formal specification (2) Elaboration of the specification, (3) Divide and conquer to handle the general case (4) Recursion introduction, (5) Recursion removal, if an iterative solution is desired, (6) Optimisation, if required. At any stage in the process, sub-specifications can be extracted and transformed separately. The main difference between this approach and the invariant based programming approach (and similar stepwise refinement methods) is that loops can be introduced and manipulated while maintaining program correctness and with no need to derive loop invariants. Another difference is that at every stage in the process we are working with a correct program: there is never any need for a separate "verification" step. These factors help to ensure that the method is capable of scaling up to the development of large and complex software systems. The method is applied to the derivation of a complex linked list algorithm and produces code which is over twice as fast as the code written by Donald Knuth to solve the same problem

Functional programming and graph algorithms

This thesis is an investigation of graph algorithms in the non-strict purely functional language Haskell. Emphasis is placed on the importance of achieving an asymptotic complexity as good as with conventional languages. This is achieved by using the monadic model for including actions on the state. Work on the monadic model was carried out at Glasgow University by Wadler, Peyton Jones, and Launchbury in the early nineties and has opened up many diverse application areas. One area is the ability to express data structures that require sharing. Although graphs are not presented in this style, data structures that graph algorithms use are expressed in this style. Several examples of stateful algorithms are given including union/find for disjoint sets, and the linear time sort binsort. The graph algorithms presented are not new, but are traditional algorithms recast in a functional setting. Examples include strongly connected components, biconnected components, Kruskal's minimum cost spanning tree, and Dijkstra's shortest paths. The presentation is lucid giving more insight than usual. The functional setting allows for complete calculational style correctness proofs - which is demonstrated with many examples. The benefits of using a functional language for expressing graph algorithms are quantified by looking at the issues of execution times, asymptotic complexity, correctness, and clarity, in comparison with traditional approaches. The intention is to be as objective as possible, pointing out both the weaknesses and the strengths of using a functional language

A methodology for programming with concurrency: An informal presentation

AbstractIn this methodology, programming problems which can be specified by an input/output assertion pair are solved in two steps: 1.(1) Refinement of a correct program that can be implemented sequentially.2.(2) Declaration of program properties, so-called semantic relations, that allow relaxations in the sequencing of the refinement's operations (e.g., concurrency).Formal properties of refinements comprise semantics (input/output characteristics) and (sequential) execution time. Declarations of semantic relations preserve the semantics but may improve the execution time of a refinement. The consequences are: 1.(a) The concurrency in a program is deduced from its formal semantics. Semantic correctness is not based on concurrency but precedes it.2.(b) Concurrency is a property not of programs but of executions. Programs do not contain concurrent commands, only suggestions (declarations) of concurrency.3.(c) The declaration of too much concurrency is impossible. Programs do not contain primitives for synchronization or mutual exclusion.4.(d) Proofs of parallel correctness are stepwise without auxiliary variables.5.(e) Freedom from deadlock and starvation is implicit without recourse to an authority outside the program, e.g., a fair scheduler

Transformation�based implementation and optimization of programs exploiting the basic Andorra model.

The characteristics of CC and CLP systems are in principle very dierent However a recent trend towards convergence in the implementation techniques for these systems can be observed While CLP and Prolog systems have been incorporating capabilities to deal with userdened suspension and coroutining CC compilers have been trying to coalesce negrained tasks into coarsergrained sequential threads This convergence of techniques opens up the possibility of having a general purpose kernel language and abstract machine to serve as a compilation target for a variety of userlevel languages We propose a transformation technique directed towards such an objective In particular we report on techniques to support the Andorra computational model essentially emulating the AndorraI system via program transformation into a sequential language with delay primitives The system is automatic comprising an optional program analyzer and a basic transformer to the kernel language It turns out that a simple parallel CLP or Prolog system with dynamic scheduling is sucient as a kernel language for this purpose The preliminary results are quite encouraging performance of the resulting system is comparable to the current AndorraI implementation

Polynomial Path Orders: A Maximal Model

This paper is concerned with the automated complexity analysis of term rewrite systems (TRSs for short) and the ramification of these in implicit computational complexity theory (ICC for short). We introduce a novel path order with multiset status, the polynomial path order POP*. Essentially relying on the principle of predicative recursion as proposed by Bellantoni and Cook, its distinct feature is the tight control of resources on compatible TRSs: The (innermost) runtime complexity of compatible TRSs is polynomially bounded. We have implemented the technique, as underpinned by our experimental evidence our approach to the automated runtime complexity analysis is not only feasible, but compared to existing methods incredibly fast. As an application in the context of ICC we provide an order-theoretic characterisation of the polytime computable functions. To be precise, the polytime computable functions are exactly the functions computable by an orthogonal constructor TRS compatible with POP*