Catálogo de publicaciones - libros

COTS (Commercial Off-The-Shelf) components can be incorporated into other systems to help software developers to produce a new system, so that both artefacts — components and the system — form a single functional entity. In that way, developing software becomes a matter of balancing required and offered functionality between the parties. But required functionality is highly dependent on component’s users, i.e. stakeholders of a COTS component selection process. Inputs to this process include discussions with composers, reuse architects, business process coordinators, and so forth. In this paper, we present an approach for balancing stakeholder’s preferences, which can be used in the process of measuring functional suitability of COTS candidates. We describe and illustrate the use of our proposal to weight requirements of components and determine suitable COTS candidates for given software.

Nowadays, there is an increasing need for flexible approaches, adaptable to different kinds of Information System Development (ISD). But customization of ISD processes have mainly be thought of for the person in charge of building processes, i.e. the methodologists, in order to allow him/her to adapt the process to the need of its company or projects. But there is also a need for customizations dedicated to project team members (application engineers), to provide them with customized guidelines (or heuristics) which are to be followed while performing their daily task. The knowledge capitalization framework we propose supports evolvability and customization of ISD processes. Reuse and customization are handled through stored in a dedicated . Our purpose is not to propose a new way to built processes, as several approaches already exist on this topic, but to ease the use of existing ones by making them less rigid and allowing their adaptation to the need of the company, the project and most of all, the project team member. Therefore, in addition to a of , we propose a scalable and polymorphic structure allowing methodologists to define a working space through a made of . Thanks to this the project team members better qualify their ISD problem in order to find a suitable solution. A solution is made of organized into a specially built to answer the project team member need and directly usable by him/her.

The we focus on in this paper is a scalable structure which supports evolution and tailoring by the methodologists for the project team member’s need with regards to project and process features.

There is a growing need to reduce the cycle of business information systems development and make it independent of underlying technologies. Model-driven synthesis of software offers solutions to these problems. This article describes a method for synthesizing business software implementations from technology independent business models. The synthesis of business software implementation performed in two steps, is based on establishing a common feature space for problem and solution domains. In the first step, a solution domain and a software architecture style are selected by matching the explicitly required features of a given software system, and implicitly required features of a given problem domain to the features provided by the solution domain and the architectural style. In the second step, all the elements of a given business analysis model are transformed into elements or configurations in the selected solution domain according to the selected architectural style, by matching their required features to the features provided by the elements and configurations of the selected solution domain. In both steps it is possible to define cost functions for selecting between different alternatives which provide the same features. The differences of our method are the separate step of solution domain analysis during the software process, which produces the feature model of the solution domain, and usage of common feature space to select the solution domain, the architectural style and specific implementations.

The developments in the ICT led companies to strive to make parts of the business transaction electronic and raised again the issue of interoperability. Although interoperability between computer systems has been widely addressed in literature, the concept of interoperability between organizations is still to a large extent unexplored. Standards are claimed to help achieving interoperability. However, experience with the implementation of EDI standards shows that many EDI implementation projects led to technical solutions with unclear business benefits. New standards are currently being developed, however their implementation can also lead again to purely technical solution, if the social context is not taken sufficiently into account. In this paper we address the problem on how to identify interoperability problems on a pragmatic level that can occur between organizations that want to carry out business transactions electronically. We also point out that, in order to identify interoperability problems on a pragmatic level, it is necessary to capture the communication requirements of the business parties and to evaluate to what extent a standard is capable to meet these requirements. To perform that evaluation we develop a meta model for describing communication. The meta model is based on theory of speech-act and communicative actions. The use of the meta model to identify interoperability problems on a pragmatic level is illustrated with an example.

Past few years have witnessed a growing recognition of intelligent techniques for the construction of efficient and reliable intrusion detection systems. Due to increasing incidents of cyber attacks, building effective intrusion detection systems (IDS) are essential for protecting information systems security, and yet it remains an elusive goal and a great challenge. In this paper, we report a performance analysis between Multivariate Adaptive Regression Splines (MARS), neural networks and support vector machines. The MARS procedure builds flexible regression models by fitting separate splines to distinct intervals of the predictor variables. A brief comparison of different neural network learning algorithms is also given.

CASE tools supporting many activities of the software development process embed visual modeling environments. Indeed, visual languages are practical means to allow engineers to define models and different views of software systems. However the effectiveness of visual modeling environments strongly depends from the process and tools used for their development. In this paper we present a user-centered methodology for the development of customized visual environments, and a tool to support it. The use of UML meta-modeling techniques and formal methods characterizes the proposed approach. Moreover, incremental development and rapid prototyping are ensured by the use of an automatic generation tool that allows designers to focus on structural features of the target language disregarding the visual environment creation.

Some consulting projects are carried out in virtual teams, which are networks of people sharing a common purpose and working across organizational and temporal boundaries by using information technologies. Multiple investigations covering these teams focus on coordination, group communication and computer supported collaborative work. However, additional perspectives like the formation of teams are also important. Here one should deal with the question: how to form the best team?

To approach this question, we have defined team formation as the process of finding the right expert for a given task and allocating the set of experts that best fulfills team requirements. This has been further transformed into a problem of constraint based optimal resource allocation.

Our environment for computer supported team formation has been developed by having adopted the brokerage view that consists of mediating experts between peers requesting a team and the ones willing to participate in a team. Computer supported brokerage of experts has been realized as a distributed problem solving that involves entities representing experts, brokers and team initiators.

E-learning is starting to play a major role in the learning and teaching activities at institutions of higher education worldwide. The students perform significant parts of their study activities decentralized and access the necessary information sources via the Internet. Several tools have been developed providing basic infrastructures that enable individual and collaborative work in a location-independent and time-independent fashion. Still, systems that adequately provide personalized and permanent support for using these tools are still to come.

This paper reports on the advances of the Semantic E-learning Agent (SEA) project, whose objective is to develop virtual student advisors, that render support to university students in order to successfully organize und perform their studies. The E-learning agents are developed with novel concepts of the Semantic Web and agents technology. The key concept is the semantic modeling of the E-learning domain by means of XML-based applied ontology languages such as DAML+OIL and OWL. Software agents apply ontological and domain knowledge in order to assist human users in their decision making processes. For this task, the inference engine JESS is applied in conjunction with the agent framework JADE.

Providing mobile workers with mobile devices such as a Compaq iPaq with a CDPD card can support them in retrieving information from centralized information systems. More specifically, mobile devices can enable mobile users to make notifications for schedule changes and add new data into the information system. In addition these devices can facilitate group communication anytime and anywhere. This paper presents different ways of providing non-critical information in a timely fashion for nomadic users of mobile devices using a wireless network. A distributed application prototype to support nomadic users is proposed, and a simulated environment is used to evaluate the prototype. Since solutions for seamless access are highly domain specific, the study involves homecare workers at Saskatoon District Health (SDH). By keeping track of the users’ current context (time, location etc.) and a user task model, it is possible to predict the information needs of mobile users and to provide context dependent adaptation of both the content and the functionality. Moreover, to avoid interrupts in the user’s interaction with the main information sources, methods for mobile transactions management using agent-based smart proxies that buffer, delay or pre-fetch information/data are introduced.

This paper proposes an agent programming language called AgentSpeak(I). This new language allows agent programs (1) to effectively perform while having incomplete knowledge of the environment, (2) to detect no-longer possible goals and re-plan these goals correspondingly, and (3) to behave reactively to changes of environment. Specifically, AgentSpeak(I) uses default theory as agent belief theory, agent always act with preferred default extension at current time point (i.e. preference may changes over time). A belief change operator for default theory is also provided to assist agent program to update its belief theory. Like other BDI agent programming languages, AgentSpeak(I) uses semantics of transitional system. It appears that the language is well suited for intelligent applications and high level control robots, which are required to perform in highly dynamic environment.