Specialized case tools for the development of expert systems

© 2018, Springer International Publishing AG, part of Springer Nature. This report presents an approach to building specialized computer-aided software engineering (CASE) tools for the development of expert systems. These tools form an integrated development environment allowing the computer aided development of different applications in the appropriate field. The integrated environment which we consider in our report represents the combination of SWI-PROLOG and Data Base Management System (DBMS) PostgreSQL tools. SWI-PROLOG provides the most appropriate tools for the solution of logical tasks in expert systems. However, SWI-PROLOG cannot manage large amounts of data. Therefore, we need to apply an appropriate data base management system to extend the capability of the knowledge base. For this purpose we used the most advanced open source PostgreSQL tools. As a result of our research we have created tools enabling the compatibility of SWI-PROLOG and DBMS PostgreSQL within the integrated development environment

A Practical Example for Model-Driven Web Requirements

The number of approaches for Web environments has grown very fast in the last years: HDM, OOHDM, and WSDM were among the first, and now a large number can be found in the literature. With the definition of MDA (Model- Driven Architecture) and the acceptance of MDE (Model-Driven Engineering) techniques in this environment, some groups are working in the use of metamodels and transformations to make their approaches more powerful. UWE (UMLBased Web Engineering) or OOWS (Object-Oriented Web Solutions) are only some examples. However, there are few real experiences with Web Engineering in the enterprise environment, and very few real applications of metamodels and MDE techniques. In this chapter the practical experience of a Web Engineering approach, NDT, in a big project developed in Andalusia is presented. Besides, it shows the usability of metamodels in real environments

An Exploratory Study of Forces and Frictions affecting Large-Scale Model-Driven Development

In this paper, we investigate model-driven engineering, reporting on an exploratory case-study conducted at a large automotive company. The study consisted of interviews with 20 engineers and managers working in different roles. We found that, in the context of a large organization, contextual forces dominate the cognitive issues of using model-driven technology. The four forces we identified that are likely independent of the particular abstractions chosen as the basis of software development are the need for diffing in software product lines, the needs for problem-specific languages and types, the need for live modeling in exploratory activities, and the need for point-to-point traceability between artifacts. We also identified triggers of accidental complexity, which we refer to as points of friction introduced by languages and tools. Examples of the friction points identified are insufficient support for model diffing, point-to-point traceability, and model changes at runtime.Comment: To appear in proceedings of MODELS 2012, LNCS Springe

Should I Bug You? Identifying Domain Experts in Software Projects Using Code Complexity Metrics

In any sufficiently complex software system there are experts, having a deeper understanding of parts of the system than others. However, it is not always clear who these experts are and which particular parts of the system they can provide help with. We propose a framework to elicit the expertise of developers and recommend experts by analyzing complexity measures over time. Furthermore, teams can detect those parts of the software for which currently no, or only few experts exist and take preventive actions to keep the collective code knowledge and ownership high. We employed the developed approach at a medium-sized company. The results were evaluated with a survey, comparing the perceived and the computed expertise of developers. We show that aggregated code metrics can be used to identify experts for different software components. The identified experts were rated as acceptable candidates by developers in over 90% of all cases

A comparative study of teaching forensics at a university degree level

Computer forensics is a relatively young University discipline which has developed strongly in the United States and the United Kingdom but is still in its infancy in continental Europe. The national programmes and courses offered therefore differ in many ways. We report on two recently established degree programmes from two European countries: Great Britain and Germany. We present and compare the design of both programmes and conclude that they cover two complementary and orthogonal aspects of computer forensics education: (a) rigorous practical skills and (b) competence for fundamental research discoveries

Knowledge formalization in experience feedback processes : an ontology-based approach

Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, knowledge management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an experience feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving themissions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable

BCAUS Project description and consideration of separation of data and control

The commonly stated truths that data may be segregated from program control in generic expert system shells and that such tools support straightforward knowledge representation were examined. The ideal of separation of data from program control in expert systems is difficult to realize for a variety of reasons. One approach to achieving this goal is to integrate hybrid collections of specialized shells and tools instead of producing custom systems built with a single all purpose expert system tool. Aspects of these issues are examined in the context of a specific diagnostic expert system application, the Backup Control Mode Analysis and Utility System (BCAUS), being developed for the Gamma Ray Observatory (GRO) spacecraft. The project and the knowledge gained in working on the project are described