Integrating runtime assertions with dynamic types: Structuring a derivation from an incomputable specification

An inherent incomputability in the specification of a functional language extension that combines assertions with dynamic type checking is isolated in an explicit derivation from mathematical specifications. The combination of types and assertions (into "dynamic assertion-types" - DATs) is a significant issue since, because the two are congruent means for program correctness, benefit arises from their better integration in contrast to the harm resulting from their unnecessary separation. However, projecting the "set membership" view of assertion-checking into dynamic types results in some incomputable combinations. Refinement of the specification of DAT checking into an implementation by rigorous application of mathematical identities becomes feasible through the addition of a "best-approximate" pseudo-equality that isolates the incomputable component of the specification. This formal treatment leads to an improved, more maintainable outcome with further development potential.

Specification matching of object-oriented components

Object-orientation supports software reuse via features such as abstraction, information hiding, polymorphism, inheritance and redefinition. However, while libraries of classes do exist, one of the challenges that still remains is to locate suitable classes and adapt them to meet the specific requirements of the software developer. Traditional approaches to library retrieval are text-based; it is therefore difficult for the developer to express their requirements in a precise and unambiguous manner. A more promising approach is specification-based retrieval, where library component interfaces and requirements are expressed using a formal specification language. In this case retrieval is based on matching formal specifications. In this paper we describe how existing approaches to specification matching can be extended to handle object-oriented components.

Model specification and forecasting foreign exchange rates with vector autoregressions

This study examines the forecasting accuracy of alternative vector autoregressive models each in a seven-variable system that comprises in turn of daily, weekly and monthly foreign exchange (FX) spot rates. The vector autoregressions (VARs) are in non-stationary, stationary and error-correction forms and are estimated using OLS. The imposition of Bayesian priors in the OLS estimations also allowed us to obtain another set of results. We find that there is some tendency for the Bayesian estimation method to generate superior forecast measures relatively to the OLS method. This result holds whether or not the data sets contain outliers. Also, the best forecasts under the non-stationary specification outperformed those of the stationary and error-correction specifications, particularly at long forecast horizons, while the best forecasts under the stationary and error-correction specifications are generally similar. The findings for the OLS forecasts are consistent with recent simulation results. The predictive ability of the VARs is very weak.

Comparing knowledge management between organisations:searching for good practice

This paper reports ongoing work that is attempting to find out ‘what is good practice for knowledge management’. The data we have to analyse this issue is 109 maps of knowledge (on knowledge management) which were built during 18 group workshops with 152 people from 15 different organisations. The maps contain data on the aspirations and action plans which UK managers have to improve knowledge management practices in their organisation. So far we have attempted a number of approaches to analysing this data, both inductive and deductive, but we still feel there is more to be learned from the rich data set we have. The paper presents a flavour of the work we have done, have considered doing, and have resisted doing. The aim of the paper is to stimulate debate on the strengths of our analyses and, more importantly, on amassing views of how it can be further strengthened, and the difficulties and dilemmas which might need to be overcome.

A review of multi-factor capacity expansion models for manufacturing plants:searching for a holistic decision aid

Investment in capacity expansion remains one of the most critical decisions for a manufacturing organisation with global production facilities. Multiple factors need to be considered making the decision process very complex. The purpose of this paper is to establish the state-of-the-art in multi-factor models for capacity expansion of manufacturing plants within a corporation. The research programme consisting of an extensive literature review and a structured assessment of the strengths and weaknesses of the current research is presented. The study found that there is a wealth of mathematical multi-factor models for evaluating capacity expansion decisions however no single contribution captures all the different facets of the problem.

Searching for lean white-collar workers

The purpose of this research has been to investigate the extent to which Lean techniques have been applied to indirect or White Collar activities within manufacturing operations. The work has been based on a systematic review of the literature and six UK based case studies. Both are described in the paper. The findings from this work include, for example, that there are few reports off the application of Lean in this context. The more substantive papers focus on NPI and Project Management, where as, Support and ‘Front Office’ activities are covered only briefly in ‘trade journal’ articles. These do demonstrate that Lean techniques can be applied successfully to non-production related activities, and there are significant opportunities for work in this area. However, the definition of Lean is evolving and practitioners do not share a common understanding of terminology. This may undermine their accuracy when reporting the application of Lean techniques.

RELAX:incorporating uncertainty into the specification of self-adaptive systems

Self-adaptive systems have the capability to autonomously modify their behaviour at run-time in response to changes in their environment. Self-adaptation is particularly necessary for applications that must run continuously, even under adverse conditions and changing requirements; sample domains include automotive systems, telecommunications, and environmental monitoring systems. While a few techniques have been developed to support the monitoring and analysis of requirements for adaptive systems, limited attention has been paid to the actual creation and specification of requirements of self-adaptive systems. As a result, self-adaptivity is often constructed in an ad-hoc manner. In this paper, we argue that a more rigorous treatment of requirements explicitly relating to self-adaptivity is needed and that, in particular, requirements languages for self-adaptive systems should include explicit constructs for specifying and dealing with the uncertainty inherent in self-adaptive systems. We present RELAX, a new requirements language for selfadaptive systems and illustrate it using examples from the smart home domain. © 2009 IEEE.

Hausdorff Distances for Searching in Binary Text Images

This work has been partially supported by Grant No. DO 02-275, 16.12.2008, Bulgarian NSF, Ministry of Education and Science.

Searching for Nearest Strings with Neural-Like String Embedding

We analyze an approach to a similarity preserving coding of symbol sequences based on neural distributed representations and show that it can be viewed as a metric embedding process.