Formal and efficient verification techniques for Real-Time UML models

The real-time UML profile TURTLE has a formal semantics expressed by translation into a timed process algebra: RT-LOTOS. RTL, the formal verification tool developed for RT-LOTOS, was first used to check TURTLE models against design errors. This paper opens new avenues for TURTLE model verification. It shows how recent work on translating RT-LOTOS specifications into Time Petri net model may be applied to TURTLE. RT-LOTOS to TPN translation patterns are presented. Their formal proof is the subject of another paper. These patterns have been implemented in a RT-LOTOS to TPN translator which has been interfaced with TINA, a Time Petri Net Analyzer which implements several reachability analysis procedures depending on the class of property to be verified. The paper illustrates the benefits of the TURTLE->RT-LOTOS->TPN transformation chain on an avionic case study

An investigation of machine learning based prediction systems

Traditionally, researchers have used either o�f-the-shelf models such as COCOMO, or developed local models using statistical techniques such as stepwise regression, to obtain software eff�ort estimates. More recently, attention has turned to a variety of machine learning methods such as artifcial neural networks (ANNs), case-based reasoning (CBR) and rule induction (RI). This paper outlines some comparative research into the use of these three machine learning methods to build software e�ort prediction systems. We briefly describe each method and then apply the techniques to a dataset of 81 software projects derived from a Canadian software house in the late 1980s. We compare the prediction systems in terms of three factors: accuracy, explanatory value and configurability. We show that ANN methods have superior accuracy and that RI methods are least accurate. However, this view is somewhat counteracted by problems with explanatory value and configurability. For example, we found that considerable eff�ort was required to configure the ANN and that this compared very unfavourably with the other techniques, particularly CBR and least squares regression (LSR). We suggest that further work be carried out, both to further explore interaction between the enduser and the prediction system, and also to facilitate configuration, particularly of ANNs

From RT-LOTOS to Time Petri Nets new foundations for a verification platform

The formal description technique RT-LOTOS has been selected as intermediate language to add formality to a real-time UML profile named TURTLE. For this sake, an RT-LOTOS verification platform has been developed for early detection of design errors in real-time system models. The paper discusses an extension of the platform by inclusion of verification tools developed for Time Petri Nets. The starting point is the definition of RT-LOTOS to TPN translation patterns. In particular, we introduce the concept of components embedding Time Petri Nets. The translation patterns are implemented in a prototype tool which takes as input an RT-LOTOS specification and outputs a TPN in the format admitted by the TINA tool. The efficiency of the proposed solution has been demonstrated on various case studies

Subtyping for Hierarchical, Reconfigurable Petri Nets

Hierarchical Petri nets allow a more abstract view and reconfigurable Petri nets model dynamic structural adaptation. In this contribution we present the combination of reconfigurable Petri nets and hierarchical Petri nets yielding hierarchical structure for reconfigurable Petri nets. Hierarchies are established by substituting transitions by subnets. These subnets are themselves reconfigurable, so they are supplied with their own set of rules. Moreover, global rules that can be applied in all of the net, are provided

Decision Making in the Medical Domain: Comparing the Effectiveness of GP-Generated Fuzzy Intelligent Structures

ABSTRACT: In this work, we examine the effectiveness of two intelligent models in medical domains. Namely, we apply grammar-guided genetic programming to produce fuzzy intelligent structures, such as fuzzy rule-based systems and fuzzy Petri nets, in medical data mining tasks. First, we use two context-free grammars to describe fuzzy rule-based systems and fuzzy Petri nets with genetic programming. Then, we apply cellular encoding in order to express the fuzzy Petri nets with arbitrary size and topology. The models are examined thoroughly in four real-world medical data sets. Results are presented in detail and the competitive advantages and drawbacks of the selected methodologies are discussed, in respect to the nature of each application domain. Conclusions are drawn on the effectiveness and efficiency of the presented approach

The uses of process modeling : a framework for understanding modeling formalisms

There is wide-spread recognition of the urgent need to improve software processes in order to improve the performance of software organizations. Process models are essential in achieving understanding and visibility of processes and are important for other uses including the analysis of processes for improvement. It has been increasingly difficult to compare and evaluate the variety of process modeling formalisms that have appeared in recent years without a clear understanding of precisely for what they will be used. The contribution of this paper is to provide an understanding and a fairly comprehensive catalog of the applications of process modeling for which formalisms may be used. The primary mechanism for doing this is a guided tour of the literature on process modeling supplemented by recent industrial experience. In the paper, basic definitions concerning processes, process descriptions and process modeling are reviewed and then uses of process modeling are surveyed under the following headings: communication among process participants, construction of new processes, control of processes, process· analysis, and process support by automation. Comments are offered on paradigms for process modeling formalisms and directions for future work to permit evolution of a discipline of process engineering are given