On the discovery of business processes orchestration patterns

COORDINSPECTOR is a Software Tool aiming at extracting the coordination layer of a software system. Such a reverse engineering process provides a clear view of the actually invoked services as well as the logic behind such invocations. The analysis process is based on program slicing techniques and the generation of, System Dependence Graphs and Coordination Dependence Graphs. The tool analyzes Common Intermediate Language (CIL), the native language of the Microsoft .Net Framework, thus making suitable for processing systems developed in any .Net Framework compilable language. COORDINSPECTOR generates graphical representations of the coordination layer together with business process orchestrations specified in WSBPEL 2.0

Criminal Liability of Organizations, Corporations, Legal Persons, and Similar Entities on Law of Portuguese Cybercrime: A Brief Discussion on the Issue of Crimes of “False Information,” the “Damage on Other Programs or Computer Data,” the “Computer-Software Sabotage,” the “Illegitimate Access,” the “Unlawful Interception,” and “Illegitimate Reproduction of the Protected Program”

Abstract: in Portugal, and in much of the legal systems of Europe, «legal persons» are likely to be criminally responsibilities also for cybercrimes. Like for example the following crimes: «false information»; «damage on other programs or computer data»; «computer-software sabotage»; «illegitimate access»; «unlawful interception» and «illegitimate reproduction of protected program». However, in Portugal, have many exceptions. Exceptions to the «question of criminal liability» of «legal persons». Some «legal persons» can not be blamed for cybercrime. The legislature did not leave! These «legal persons» are v.g. the following («public entities»): legal persons under public law, which include the public business entities; entities utilities, regardless of ownership; or other legal persons exercising public powers. In other words, and again as an example, a Portuguese public university or a private concessionaire of a public service in Portugal, can not commit (in Portugal) any one of cybercrime pointed. Fair? Unfair. All laws should provide that all legal persons can commit cybercrimes. PS: resumo do artigo em inglês.

GUIsurfer: A Reverse Engineering Framework for User Interface Software

GUIsurfer: A Reverse Engineering Framework for User Interface Software

COORDINSPECTOR: a tool for extracting coordination data from legacy code

More and more current software systems rely on non trivial coordination logic for combining autonomous services typically running on different platforms and often owned by different organizations. Often, however, coordination data is deeply entangled in the code and, therefore, difficult to isolate and analyse separately. COORDINSPECTOR is a software tool which combines slicing and program analysis techniques to isolate all coordination elements from the source code of an existing application. Such a reverse engineering process provides a clear view of the actually invoked services as well as of the orchestration patterns which bind them together. The tool analyses Common Intermediate Language (CIL) code, the native language of Microsoft .Net Framework. Therefore, the scope of application of COORDINSPECTOR is quite large: potentially any piece of code developed in any of the programming languages which compiles to the .Net Framework. The tool generates graphical representations of the coordination layer together and identifies the underlying business process orchestrations, rendering them as Orc specifications

Domain-Specific Language for Coordination patterns

The integration and composition of software systems requires a good architectural design phase to speed up communications between (remote) components. However, during implementation phase, the code to coordinate such components often ends up mixed in the main business code. This leads to maintenance problems, raising the need for, on the one hand, separating the coordination code from the business code, and on the other hand, providing mechanisms for analysis and comprehension of the architectural decisions once made. In this context our aim is at developing a domain-specific language, CoordL, to describe typical coordination patterns. From our point of view, coordination patterns are abstractions, in a graph form, over the composition of coordination statements from the system code. These patterns would allow us to identify, by means of pattern-based graph search strategies, the code responsible for the coordination of the several components in a system. The recovering and separation of the architectural decisions for a better comprehension of the software is the main purpose of this pattern language

The role of coordination analysis in software integration projects

What sort of component coordination strategies emerge in a software integration process? How can such strategies be discovered and further analysed? How close are they to the coordination component of the envisaged architectural model which was supposed to guide the integration process? This paper introduces a framework in which such questions can be discussed and illustrates its use by describing part of a real case-study. The approach is based on a methodology which enables semi-automatic discovery of coordination patterns from source code, combining generalized slicing techniques and graph manipulation

The perceived potential of business social networking sites

Business social networking is a facilitator of several business activities, such as market studies, communication with clients, and identification of business partners. This paper traduces the results of a study undertaken with the purpose of getting to know how the potential of networking is perceived in the promotion of business by participants of the LinkedIn network, and presents two main contributions: (1) to disseminate within the business community which is the relevance given to social networking; and (2) which are the social networks best suitable to the promotion of business, to support the definition of strategies and approaches accordingly. The results confirm that LinkedIn is the most suitable network to answer the needs of those that look for professional contacts and for the promotion of business, while innovation is the most recognized factor in the promotion of business through social networking. This study contributes to a better understanding of the potential of different business social networking sites, to support organizations and professionals to align their strategies with the perceived potential of each network.

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.