User interface development and software environments : the Chiron-1 system

User interface development systems for software environments have to cope with the broad, extensible and dynamic character of such environments, must support internal and external integration, and should enable various software development strategies. The Chiron-1 system adapts and extends key ideas from current research in user interface development systems to address the particular demands of software environments. Important Chiron-1 concepts are: separation of concerns, dynamism, and open architecture. We discuss the requirements on such user interface development systems, present the Chiron-1 architecture and a scenario of its usage, detail the concepts it embodies, and report on its design and prototype implementation

Ship product modelling

This paper is a fundamental review of ship product modeling techniques with a focus on determining the state of the art, to identify any shortcomings and propose future directions. The review addresses ship product data representations, product modeling techniques and integration issues, and life phase issues. The most significant development has been the construction of the ship Standard for the Exchange of Product Data (STEP) application protocols. However, difficulty has been observed with respect to the general uptake of the standards, in particular with the application to legacy systems, often resulting in embellishments to the standards and limiting the ability to further exchange the product data. The EXPRESS modeling language is increasingly being superseded by the extensible mark-up language (XML) as a method to map the STEP data, due to its wider support throughout the information technology industry and its more obvious structure and hierarchy. The associated XML files are, however, larger than those produced using the EXPRESS language and make further demands on the already considerable storage required for the ship product model. Seamless integration between legacy applications appears to be difficult to achieve using the current technologies, which often rely on manual interaction for the translation of files. The paper concludes with a discussion of future directions that aim to either solve or alleviate these issues

Requirements, design and business process reengineering as vital parts of any system development methodology

This thesis analyzes different aspects of system development life cycle, concentrating on the requirements and design stages. It describes various methodologies, methods and tools that have been developed over the years. It evaluates them and compares them against each other. Finally a conclusion is made that there is a very important stage missing in the system development life cycle, which is the Business Process Reengineering Stage

Proceedings of the 1994 Monterey Workshop, Increasing the Practical Impact of Formal Methods for Computer-Aided Software Development: Evolution Control for Large Software Systems Techniques for Integrating Software Development Environments

Office of Naval Research, Advanced Research Projects Agency, Air Force Office of Scientific Research, Army Research Office, Naval Postgraduate School, National Science Foundatio

Applying Software Product Lines to Build Autonomic Pervasive Systems

In this Master Thesis, we have proposed a model-driven Software Product Line (SPL) for developing autonomic pervasive systems. The work focusses on reusing the Variability knowledge from the SPL design to the SPL products. This Variability knowledge enables SPL products to deal with adaptation scenarios (evolution and involution) in an autonomic way.Cetina Englada, C. (2008). Applying Software Product Lines to Build Autonomic Pervasive Systems. http://hdl.handle.net/10251/12447Archivo delegad

Goal-driven agent-oriented software processes

The quality of software processes is acknowledged as a critical factor for delivering quality software systems. Any initiative for improving the quality of software processes requires their explicit representation and management. A current representational metaphor for systems is agent orientation, which has become one of the recently recognized engineering paradigms. In this article, we argue for the convenience of representing the software process using an agent-oriented language to model it and a goal-driven procedure to design it. Particularly we propose using the i* framework which is both an agent- and a goal-oriented modeling language. We review the possibilities of i* as a software process modeling language, and we also show how success factors can be made explicit in i* representations of the software processes. Finally, we illustrate the approach with an example based on the development of a set of ergonomic and safety software tools.Peer ReviewedPostprint (published version

Second CLIPS Conference Proceedings, volume 1

Topics covered at the 2nd CLIPS Conference held at the Johnson Space Center, September 23-25, 1991 are given. Topics include rule groupings, fault detection using expert systems, decision making using expert systems, knowledge representation, computer aided design and debugging expert systems

Extending evolutionary multi-objective optimization of business process designs

Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2019.Optimizing a problem to produce a set of improved solutions is not a new concept. Many scientific areas have been benefited by the application of optimizations techniques and so have business processes. The competitive business environments have led organizations into examining and re-designing their core business processes, aiming for improving their performance and market responsiveness. The optimization and the continuous improvement of business processes within a company, can give the advantage to the company to be more competitive by reducing its costs, improving the delivery quality and efficiency, and enabling adaptation to changing environments. This thesis focuses on business process multi-objective optimization with evolutionary algorithms. There have already been optimization approaches with evolutionary algorithms for business process optimization problems that demonstrated rather satisfactory results. This thesis aims to improve and extent those approaches by providing a revised and refined version of an existing business process optimization framework by Vergidis (2008), that incorporates a pre-processing technique for enhancing the efficiency of the employed Evolutionary Multi-objective Optimization Algorithms (EMOAs), a new process composition algorithm that make the new framework capable of fulfilling more real-life constraints and handling more complex problems and many other features such as ease of use, more efficient I/O, better interactivity and easy maintenance. The proposed pre-processing technique was tested as a standalone procedure and demonstrated satisfactory results, managing to reduce drastically the problem dataset of all scenarios examined. The results of the whole optimization framework for the real-life scenarios examined, were very promising and indicated that the framework work as expected. It can automate the process composition and identify alternative business process designs with optimized attribute values

Artificial Intelligence Research Branch future plans

This report contains information on the activities of the Artificial Intelligence Research Branch (FIA) at NASA Ames Research Center (ARC) in 1992, as well as planned work in 1993. These activities span a range from basic scientific research through engineering development to fielded NASA applications, particularly those applications that are enabled by basic research carried out in FIA. Work is conducted in-house and through collaborative partners in academia and industry. All of our work has research themes with a dual commitment to technical excellence and applicability to NASA short, medium, and long-term problems. FIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at the Jet Propulsion Laboratory (JPL) and AI applications groups throughout all NASA centers. This report is organized along three major research themes: (1) Planning and Scheduling: deciding on a sequence of actions to achieve a set of complex goals and determining when to execute those actions and how to allocate resources to carry them out; (2) Machine Learning: techniques for forming theories about natural and man-made phenomena; and for improving the problem-solving performance of computational systems over time; and (3) Research on the acquisition, representation, and utilization of knowledge in support of diagnosis design of engineered systems and analysis of actual systems