Claudia Raibulet

Evaluation of dynamic adaptivity through metrics: an achievable target?

Dynamic adaptivity is one of the most challenging non-functional issues to address during the engineering of information systems. Furthermore, it is even harder to evaluate. The definition of mechanisms through which adaptivity may be evaluated would be very useful both for the maintainability, reusability, and evolution of adaptive systems, and for the relations which may be established among adaptive systems (e.g., interaction, integration). In this paper we propose examples of metrics for dynamic adaptivity which may be considered a starting point for future research on (1) the feasibility related to the definition of measurable evaluation mechanisms for adaptive systems, and (2) the usability of these metrics as design hints in the development process of new adaptive systems and as formal approaches for the evaluation of existing adaptive systems.

A comparison of reverse engineering tools based on design pattern decomposition

The usefulness of design patterns in forward engineering is already well-known and several tools provide support for their application in the development of software systems. While the role of design patterns in reverse engineering is still argued primarily due to their informal definition which leads to various possible implementations of each pattern. One of the most discussed aspects related to design patterns is about the need of their formalization according to the drawbacks this can represent. Formalization leads to the identification of the so-called sub-patterns, which are the recurring fundamental elements design patterns are composed of. In this paper we analyze the role sub-patterns play in two reverse engineering tools: FUJABA and SPQR. Attention is focused on how sub-patterns are exploited to define and to detect design patterns. To emphasize the similarities and differences between the two approaches, the composite design pattern is considered as example.

Criteria for the evaluation of self-* systems

In the last years, the growing complexity of the current applications has led to the design of self-adapting systems presenting self-* properties. These systems are composed of several autonomous interactive entities. They behave autonomously and present enhanced characteristics allowing them to handle dynamics coming from exogenous and endogenous changes. In this paper, we propose a set of criteria for the description and evaluation of the adaptive properties of such systems. They aim to provide a concrete mechanism to analyze the quality of the design of adaptive systems, to evaluate the effect of self-* properties on the performances and to compare the adaptive features of different systems. The criteria are grouped into different categories: methodological, architectural, intrinsic, and runtime evaluation. They have been identified and specified by analyzing several case studies, which address self-adaptivity issues through different approaches with different objectives in various application contexts.

Facets of Adaptivity

Adaptivity is one of the key requirements of todays information systems. It is used in various areas which may range from control and operating systems to networks, from robotics to intelligent systems, from multimedia to information retrieval and Web Services. Essentially, it is related to changes performed in the systems at run-time. These changes may regard various aspects: architectural, structural, behavioral or content. Considering the diversity of its application areas and of ways of achievement, this paper aims to discuss the facetsof adaptivity by raising the following questions: Why is it needed? Which are its objectives? Which are its main open research issues?

Components in an adaptive and QoS-based architecture

This paper aims to present the main software components we have developed in the context of the ARM (Adaptive Resource Management) project at University of Milano-Bicocca for an adaptive, distributed, service-oriented architecture. The goal of ARM is to manage the resources of a system in a way that enables it to dynamically identify and execute services on the available resources. Our approach chooses the most appropriate resource that is able to execute a service with the requested qualities of service (QoSs). To achieve adaptivity, ARM uses reflection at the architectural level. Exploiting the reflective representation of the systems resources and their related QoSs, ARM may organize them accordingly to various criteria and evaluate them based on their QoSs features and their potentiality in executing a requested service with the requested QoSs. To validate the ARM concepts, a prototype based on the peer-to-peer paradigm is currently under development. It aims to provide an adaptive support when using the resources available in our department.

Elemental Design Patterns Recognition In Java

The decomposition of design patterns into simpler elements may reduce significantly the creation of variants in forward engineering, while it increases the possibility of identifying applied patterns in reverse engineering. Nevertheless, there are few reverse engineering tools that exploit the decomposition of patterns (i.e., FUJABA, SPQR). The SPQR approach introduces a catalog of elemental design patterns (EDP) and a rule set based on sigma-calculus through which EDPs are defined and composed into design patterns. Considering the SPQR approach particularly interesting, we propose a novel solution for defining and detecting EDPs and, further, design patterns. Our approach defines EDPs as logical functions of eight symbolic variables, each variable representing a method call (e.g., method name, method signature, method declaration, this reference, super reference) or a class property (superclass, same family, same object). An EDP detector has been developed based on this approach, representing a starting point for future developments towards design pattern recognition in the reverse engineering context

Design patterns: a survey on their micro-structures

Design patterns play a significant role in reverse engineering by providing information not only on how but also on why a solution has been implemented in a specific way because of their semantics. The application of design patterns leads to their personalization to a specific context, hence to the generation of variants. This makes their recognition a challenging task, which may be addressed through the understanding and detection of the micro‐structures design patterns are made of. This is very useful for the detection as well as for the application of design patterns. The principal aim of this paper is to present a survey on these micro‐structures and a comparison among them in the perspective of reverse engineering. Because of their less complex structure and behavior, as well as closer link to the source code, the recognition of these micro‐structures may be automated, which can be considered a step towards the automatic recognition of the more complex design patterns. In this paper, we consider four of the most significant types of micro‐structures: elemental design patterns, clues, sub‐patterns, and micro patterns. To analyze the role of the micro‐structures in the design pattern detection process, we make a comparison among these four types of micro‐structures and among the micro‐structures of various types in order to identify the relations among them. Copyright

Understanding the relevance of micro-structures for design patterns detection

One important issue concerning design patterns in reverse engineering is their detection to support program comprehension, design recovery, system (re-)documentation, and software evolution. The objectives of this paper are to identify and analyze different types of building blocks of design patterns and to evaluate if the detection of these building blocks (called micro-structures) is relevant for the detection of occurrences of the design patterns. This analysis is useful to understand how the different types of micro-structures can be combined to better comprehend design patterns and to improve their detection. To achieve the objectives, the paper provides a description of different micro-structures, an analysis of their relevance in different design motifs, and a statistical analysis on the number and types of micro-structures present in different design patterns. Finally, we investigate if the detection of some design patterns can be performed only through the detection of a combined set of micro-structures, or other techniques should be exploited.

Risk assessment in work environments: modeling and simulation

The paper proposes a characterization of risks and a service‐oriented prototype to face risky situations in work environments, such as in industrial plants or building construction areas. A risk is the overture of emergencies that produce human and/or material damages. Therefore, it is particularly critical to identify and manage risks to avoid their evolution into emergencies. In this paper, we outline the technological features of a risk environment and propose a risk model and a service‐based simulation prototype aimed to improve safety in work environments. We discuss engineering issues concerning risk modeling and management. Furthermore, we propose a risk management system solution and its related implemented prototype composed of services able to detect and also to prevent the occurrence of risk conditions. Copyright

Wearable Services in Risk Management

In this paper, the key ideas of ambient intelligence, wearable objects and service-oriented computing are combined so that appliances and devices can disappear and become part of the work garments and environment of the individual and, as an effect, services emerge to face risky situations through reaction to alarms and to perform risk management. Along this line, we outline the features of a wearable-based services system aimed at improving safety in work places.