The importance of requirements, which in practice often means natural language requirements, for a successful software project cannot be underestimated. Although requirement analysis has been traditionally reserved to the experience of professionals, there is no reason not to use various automatic techniques to the same end. In this paper we present Circe, a Web-based environment for aiding in natural language requirements gathering, elicitation, selection, and validation and the tools it integrates. These tools have been used in several experiments both in academic and in industrial environments. Among other features, Circe can extract abstractions from natural language texts, build various models of the system described by the requirements, check the validity of such models, and produce functional metric reports. The environment can be easily extended to enhance its natural language recognition power, or to add new models and views on them

Second revision, Version 2.0 26/12/96Abstract Process-centered Software Engineering Environments (PSEEs) are the most recent generation of environments supporting software development activities. They exploit an explicit representation of the process (called the process model) that specifies how to carry out software development activities, the roles and tasks of software developers, and how to use and control software development tools. A process model is therefore a vehicle to better understand and communicate the process. If it is expressed in a formal notation, it can be used to support a variety of activities such as process analysis, process simulation, and process enactment.PSEEs provide automatic support for these activities. They exploit languages based on different paradigms, such as Petri nets and rule-based systems. They include facilities to edit and analyse process models. By enacting the process model, a PSEE provides a variety of services such as software developers assistance, automation of routine tasks, invocation and control of software development tools, and enforcement of mandatory rules and practices.Several PSEEs have been developed, both as research projects and also as commercial products. The initial deployment and exploitation of this technology has made it possible to produce a significant amount of experiences, comments, evaluations, and feedback. We still miss, however, consistent and comprehensive assessment methods that can be used to collect and organize these information. This paper aims at contributing to the definition of such method, by providing a systematic comparison grid and by accomplishing an initial evaluation of the state of the art in the field. This evaluation takes into account the systems that have been developed by the authors in the past 5 years, and also the main characteristics of other wellknown environments.

This paper presents CIRCE, an environment for the analysis of natural language requirements. CIRCE is first presented in terms of its architecture, based on a transformational paradigm. Details are then given for the various transformation steps, including (i) a novel technique for parsing natural language requirements, and (ii) an expert system based on modular agents, embodying intensional knowledge about software systems in general. The result of all the transformations is a set of models for the requirements document, for the system described by the requirements, and for the requirements writing process. These models can be inspected, measured, and validated against a given set of criteria.Some of the features of the environment are shown by means of an example. Various stages of requirements analysis are covered, from initial sketches to pseudo-code and UML models.

In this paper we propose a class of process metrics based on the continuous monitoring of product attributes. Two such metrics are defined for the requirements analysis process, namely stability (i.e., how smoothly the process of introducing information in a requirements document flows) and efficiency (i.e., which part of the effort of the analysts is spent in reworks). These measures can be used for the timely identification of risky trends in a requirements analysis process. The paper also gives some results from an experiment on the collection and use of the measures we introduced

Distributed Online Social Networks (DOSNs) have recently been proposed to grant users more control over the data they share with the other users. Indeed, in contrast to centralized Online Social Networks (such as Facebook), DOSNs are not based on centralized storage services, because the contents shared by the users are stored on the devices of the users themselves. One of the main challenges in a DOSN comes from guaranteeing availability of the users' contents when the data owner disconnects from the network. In this paper, we focus our attention on data availability by proposing a distributed allocation strategy which takes into account both the privacy policies defined on the contents and the availability patterns (online/offline) of the users in order to allocate their contents on trusted nodes. A linear predictor is used to model and to predict the availability status of the users in a future time interval, on the basis of their past temporal behaviour. We conduct a set of experiments on a set of traces taken from Facebook. The results prove the effectiveness of our approach by showing high availability of users' profiles.