International Journal of Software Engineering and Knowledge Engineering

Service-oriented architecture (SOA) is currently the predominant software integration framework. Web services provide the predominant platform for SOA. SOA as an integration architecture solution supports a range of application scenarios. We present a solution for the integration of business information systems based on SOA and Web services. We discuss maintainability requirements in relation to information-specific integration and architecture aspects. A template-based approach based on modular and declarative transformation rules and architectural styles and patterns defines our solution to the maintainability problem of integration architectures.

Computer gaming is a key component of the rapidly growing entertainment industry. Computer games are a multi-billion pound worldwide part of the entertainment industry. However, they are a relatively new type of software product and as such the manner in which they are designed and developed is still evolving. Computer games can be highly complex software systems that involve the expertise of a wide range of professionals ranging from programmers to animators, artists and musicians. When designing computer games, new game concepts can be difficult to communicate. In addition, the creative process could be benefited if game design ideas were capable of being shared widely and discussed. In this paper, we are to some extent shifting the focus from real world situation to what we shall term game world situation. That is, a logically simulated environment is created by defining situations and events based on the hierarchy structure of the situation. Our study defines event type, causality events and event normalization, and aims to develop a logical simulation method. These methods allow us to understand the communication of new game environment design. Specially, the introduction of the definition of events allows us to approach game design in a structural manner rather than by their classification. The proposed method was implemented in the context of changing among natural phenomena in a game environment.

In recent years, customer relationships have been recognized by enterprises as a critical factor to succeed in their business. Effective customer relationships can help enterprises to deliver more satisfying products/services to customers based on their needs, preferences, or past transactions. This model, however, emphasizes the use of customer information to benefit enterprises; in contrast customers receive less information from enterprises. To address this problem, many technologies have been proposed such as recommendation systems and intelligent agents that provide customers with more information for their possible needs. However, these technologies still have some shortcomings that initiate the discussion of a new Consumer Support Systems (CSS) paradigm. CSS is specifically structured to provide consumers with effective information from enterprises to support their decision making. In this paper, we present an object-oriented method for the development of CSS that supports enhanced customer relationships by emphasizing on effective information provision from enterprises to consumers. The method starts from the identification of CSS characteristics, through the recognition of a system architecture that supports the realization of these characteristics, and finally ends with the analysis and design of architectural class objects that collaborate to realize these characteristics. The method is use case driven with UML and Petri nets notations utilized and extended as its modeling tool. To illustrate this, the method is applied to an exemplified CSS for book publishing.

Providing support for eGovernment services is currently a high-speed race for public administrations and research institutions. In this process towards a fully transactional platform, several projects have made their contribution. Regretfully, current solutions unveils some drawbacks regarding interoperability and accessibility issues. In this context, this paper proposes a semantic approach to fulfill holistic services in the domain. Semantics is called to play a role of first importance as a tool for interoperability. LifeEvents and AdministrativeServices are artifacts defined within this technology. Using these, an entire software architecture is derived and, eventually implemented by means of a software platform also described in this paper. Finally, some conclusions are presented.

Predicting changes in software entities (e.g. source files) that are more likely to change can help in the efficient allocation of the project resources. A powerful change prediction tool can improve maintenance and evolution tasks in software projects in terms of cost and time factors. The vast majority of research works have focused on determining "where" the most change-prone entities are, and "how" the change will be propagated through a system. This article suggests that knowing "when" changes are likely to happen can also provide another consideration for managers and developers to plan their maintenance activities more efficiently. To address this issue, a Neural Network-based Temporal Change Prediction (NNTCP) framework is proposed. This novel framework indicates "where" the changes are likely to happen (i.e. hot spots), and then adds the time dimension to predict "when" it may occur. In proving this concept, the NNTCP framework is applied in two large-scale open source software projects, Mozilla and Eclipse. The results obtained indicate NNTCP can predict the occurrence of several future revisions with reasonable performance.

Decision trees are one of the most effective and widely used induction methods that have received a great deal of attention over the past twenty years. When decision tree induction algorithms were used with uncertain rather than deterministic data, the result is a complete tree, which can classify most of the unseen samples correctly. This tree would be pruned in order to reduce its classification error and over-fitting. Recently, multi agent researchers concentrated on learning from large databases. In this paper we present a novel multi agent learning method that is able to induce a decision tree from distributed training sets. Our method is based on combination of separate decision trees each provided by one agent. Hence an agent is provided to aggregate results of the other agents and induces the final tree. Our empirical results suggest that the proposed method can provide significant benefits to distributed data classification.