KEMNAD:a knowledge engineering methodology for negotiating agent development

Automated negotiation is widely applied in various domains. However, the development of such systems is a complex knowledge and software engineering task. So, a methodology there will be helpful. Unfortunately, none of existing methodologies can offer sufficient, detailed support for such system development. To remove this limitation, this paper develops a new methodology made up of: (1) a generic framework (architectural pattern) for the main task, and (2) a library of modular and reusable design pattern (templates) of subtasks. Thus, it is much easier to build a negotiating agent by assembling these standardised components rather than reinventing the wheel each time. Moreover, since these patterns are identified from a wide variety of existing negotiating agents (especially high impact ones), they can also improve the quality of the final systems developed. In addition, our methodology reveals what types of domain knowledge need to be input into the negotiating agents. This in turn provides a basis for developing techniques to acquire the domain knowledge from human users. This is important because negotiation agents act faithfully on the behalf of their human users and thus the relevant domain knowledge must be acquired from the human users. Finally, our methodology is validated with one high impact system.

Tracing requirements for adaptive systems using claims

The complexity of environments faced by dynamically adaptive systems (DAS) means that the RE process will often be iterative with analysts revisiting the system specifications based on new environmental understanding product of experiences with experimental deployments, or even after final deployments. An ability to trace backwards to an identified environmental assumption, and to trace forwards to find the areas of a DAS's specification that are affected by changes in environmental understanding aids in supporting this necessarily iterative RE process. This paper demonstrates how claims can be used as markers for areas of uncertainty in a DAS specification. The paper demonstrates backward tracing using claims to identify faulty environmental understanding, and forward tracing to allow generation of new behaviour in the form of policy adaptations and models for transitioning the running system. © 2011 ACM.

On the use of software models during software execution

Increasingly software systems are required to survive variations in their execution environment without or with only little human intervention. Such systems are called "eternal software systems". In contrast to the traditional view of development and execution as separate cycles, these modern software systems should not present such a separation. Research in MDE has been primarily concerned with the use of models during the first cycle or development (i.e. during the design, implementation, and deployment) and has shown excellent results. In this paper the author argues that an eternal software system must have a first-class representation of itself available to enable change. These runtime representations (or runtime models) will depend on the kind of dynamic changes that we want to make available during execution or on the kind of analysis we want the system to support. Hence, different models can be conceived. Self-representation inevitably implies the use of reflection. In this paper the author briefly summarizes research that supports the use of runtime models, and points out different issues and research questions. © 2009 IEEE.

Dynamic decision networks for decision-making in self-adaptive systems:a case study

Bayesian decision theory is increasingly applied to support decision-making processes under environmental variability and uncertainty. Researchers from application areas like psychology and biomedicine have applied these techniques successfully. However, in the area of software engineering and speci?cally in the area of self-adaptive systems (SASs), little progress has been made in the application of Bayesian decision theory. We believe that techniques based on Bayesian Networks (BNs) are useful for systems that dynamically adapt themselves at runtime to a changing environment, which is usually uncertain. In this paper, we discuss the case for the use of BNs, speci?cally Dynamic Decision Networks (DDNs), to support the decision-making of self-adaptive systems. We present how such a probabilistic model can be used to support the decision making in SASs and justify its applicability. We have applied our DDN-based approach to the case of an adaptive remote data mirroring system. We discuss results, implications and potential bene?ts of the DDN to enhance the development and operation of self-adaptive systems, by providing mechanisms to cope with uncertainty and automatically make the best decision.

On the Models of Development and Distribution of Software

The notion model of development and distribution of software (MDDS) is introduced and its role for the efficiency of the software products is stressed. Two classical MDDS are presented and some attempts to adapt them to the contemporary trends in web-based software design are described. Advantages and shortcomings of the obtained models are outlined. In conclusion the desired features of a better MDDS for web-based solutions are given.

Computer-aided System of Semantic Text Analysis of a Technical Specification

The given work is devoted to development of the computer-aided system of semantic text analysis of a technical specification. The purpose of this work is to increase efficiency of software engineering based on automation of semantic text analysis of a technical specification. In work it is offered and investigated the model of the analysis of the text of the technical project is submitted, the attribute grammar of a technical specification, intended for formalization of limited Russian is constructed with the purpose of analysis of offers of text of a technical specification, style features of the technical project as class of documents are considered, recommendations on preparation of text of a technical specification for the automated processing are formulated. The computer-aided system of semantic text analysis of a technical specification is considered. This system consists of the following subsystems: preliminary text processing, the syntactic and semantic analysis and construction of software models, storage of documents and interface.

A "Cross-technology" Software Development Approach

Contemporary web-based software solutions are usually composed of many interoperating applications. Classical approach is the different applications of the solution to be created inside one technology/platform, e.g. Java-technology, .NET-technology, etc. Wide spread technologies/platforms practically discourage (and sometime consciously make impossible) the cooperation with elements of the concurrent technologies/platforms. To make possible the usage of attractive features of one technology/platform in another technology/platform some “cross-technology” approach is necessary. In the paper is discussed the possibility to combine two existing instruments – interoperability protocols and “lifting” of procedures – in order to obtain such cross-technology approach.

Using Reengineering Techniques for Distance Study Course Improvement

The paper analyses the reengineering concept as it comes from software engineering and management fields. We combine two viewpoints and apply them to solve a problem of reengineering of a distance study system, in general, and the unit of learning, in particular. We propose a framework for reengineering of unit of learning, based on general model of software reengineering, and present a case study, in which we describe, how one topic of distance study course was reengineered, considering triple consistency principle and requirements for computer science. The proposed framework contributes to increasing quality, effectiveness and systematization of delivering distance studies.

Software and Services − Research and Education in Bulgaria

Доклад по покана, поместен в сборника на Националната конференция "Образованието в информационното общество", Пловдив, май, 2010 г.

Semantically Enhanced Software Documentation Processes

High-quality software documentation is a substantial issue for understanding software systems. Shorter time-to-market software cycles increase the importance of automatism for keeping the documentation up to date. In this paper, we describe the automatic support of the software documentation process using semantic technologies. We introduce a software documentation ontology as an underlying knowledge base. The defined ontology is populated automatically by analysing source code, software documentation and code execution. Through selected results we demonstrate that the use of such semantic systems can support software documentation processes efficiently.

BOWL:augmenting the semantic web with beliefs

As the Semantic Web is an open, complex and constantly evolving medium, it is the norm, but not exception that information at different sites is incomplete or inconsistent. This poses challenges for the engineering and development of agent systems on the Semantic Web, since autonomous software agents need to understand, process and aggregate this information. Ontology language OWL provides core language constructs to semantically markup resources on the Semantic Web, on which software agents interact and cooperate to accomplish complex tasks. However, as OWL was designed on top of (a subset of) classic predicate logic, it lacks the ability to reason about inconsistent or incomplete information. Belief-augmented Frames (BAF) is a frame-based logic system that associates with each frame a supporting and a refuting belief value. In this paper, we propose a new ontology language Belief-augmented OWL (BOWL) by integrating OWL DL and BAF to incorporate the notion of confidence. BOWL is paraconsistent, hence it can perform useful reasoning services in the presence of inconsistencies and incompleteness. We define the abstract syntax and semantics of BOWL by extending those of OWL. We have proposed reasoning algorithms for various reasoning tasks in the BOWL framework and we have implemented the algorithms using the constraint logic programming framework. One example in the sensor fusion domain is presented to demonstrate the application of BOWL.

Data Mining for Software Development Life Cycle Quality Management

Computer software plays an important role in business, government, society and sciences. To solve real-world problems, it is very important to measure the quality and reliability in the software development life cycle (SDLC). Software Engineering (SE) is the computing field concerned with designing, developing, implementing, maintaining and modifying software. The present paper gives an overview of the Data Mining (DM) techniques that can be applied to various types of SE data in order to solve the challenges posed by SE tasks such as programming, bug detection, debugging and maintenance. A specific DM software is discussed, namely one of the analytical tools for analyzing data and summarizing the relationships that have been identified. The paper concludes that the proposed techniques of DM within the domain of SE could be well applied in fields such as Customer Relationship Management (CRM), eCommerce and eGovernment. ACM Computing Classification System (1998): H.2.8.

Design software architecture models using ontology

Software architecture plays an essential role in the high level description of a system design, where the structure and communication are emphasized. Despite its importance in the software engineering process, the lack of formal description and automated verification hinders the development of good software architecture models. In this paper, we present an approach to support the rigorous design and verification of software architecture models using the semantic web technology. We view software architecture models as ontology representations, where their structures and communication constraints are captured by the Web Ontology Language (OWL) and the Semantic Web Rule Language (SWRL). Specific configurations on the design are represented as concrete instances of the ontology, to which their structures and dynamic behaviors must conform. Furthermore, ontology reasoning tools can be applied to perform various automated verification on the design to ensure correctness, such as consistency checking, style recognition, and behavioral inference.

Creating Responsive Information Systems with the Help of SSADM

In this paper, a program for a research is outlined. Firstly, the concept of responsive information systems is defined and then the notion of the capacity planning and software performance engineering is clarified. Secondly, the purpose of the proposed methodology of capacity planning, the interface to information systems analysis and development methodologies (SSADM), the advantage of knowledge-based approach is discussed. The interfaces to CASE tools more precisely to data dictionaries or repositories (IRDS) are examined in the context of a certain systems analysis and design methodology (e.g. SSADM).

Design and implementation of a multisite data repository for pediatric epilepsy

This dissertation established a software-hardware integrated design for a multisite data repository in pediatric epilepsy. A total of 16 institutions formed a consortium for this web-based application. This innovative fully operational web application allows users to upload and retrieve information through a unique human-computer graphical interface that is remotely accessible to all users of the consortium. A solution based on a Linux platform with My-SQL and Personal Home Page scripts (PHP) has been selected. Research was conducted to evaluate mechanisms to electronically transfer diverse datasets from different hospitals and collect the clinical data in concert with their related functional magnetic resonance imaging (fMRI). What was unique in the approach considered is that all pertinent clinical information about patients is synthesized with input from clinical experts into 4 different forms, which were: Clinical, fMRI scoring, Image information, and Neuropsychological data entry forms. A first contribution of this dissertation was in proposing an integrated processing platform that was site and scanner independent in order to uniformly process the varied fMRI datasets and to generate comparative brain activation patterns. The data collection from the consortium complied with the IRB requirements and provides all the safeguards for security and confidentiality requirements. An 1-MR1-based software library was used to perform data processing and statistical analysis to obtain the brain activation maps. Lateralization Index (LI) of healthy control (HC) subjects in contrast to localization-related epilepsy (LRE) subjects were evaluated. Over 110 activation maps were generated, and their respective LIs were computed yielding the following groups: (a) strong right lateralization: (HC=0%, LRE=18%), (b) right lateralization: (HC=2%, LRE=10%), (c) bilateral: (HC=20%, LRE=15%), (d) left lateralization: (HC=42%, LRE=26%), e) strong left lateralization: (HC=36%, LRE=31%). Moreover, nonlinear-multidimensional decision functions were used to seek an optimal separation between typical and atypical brain activations on the basis of the demographics as well as the extent and intensity of these brain activations. The intent was not to seek the highest output measures given the inherent overlap of the data, but rather to assess which of the many dimensions were critical in the overall assessment of typical and atypical language activations with the freedom to select any number of dimensions and impose any degree of complexity in the nonlinearity of the decision space.