1,721,107 research outputs found
Business process flexibility - a systematic literature review with a software systems perspective
No full textBusiness Process flexibility supports organizations in changing their everyday work activities to remain competitive. Since much research has been done on this topic a better awareness on the current state of knowledge is needed. This paper reports the results of a systematic literature review to develop a map on Business Process flexibility with a special focus on software systems related aspects. It covers a spectrum of the state of the art from academic point of view. It includes 164 research works from the main computer science digital libraries. After an introduction into the topic the applied methodology is described. The output of the paper is in the form of schemes and reflections. Starting from the needs for Business Process flexibility, its impact on Business Process life-cycle is introduced. Successively instruments used to express and to support Business Process flexibility are presented together with related validation scenarios. In this paper we also highlight possible future research lines needing further investigations. In particular we identified room for future works in the area of languages for modeling flexibility, on-the-fly verification solutions, adaptation of Business Process running instances, and techniques for evolution recognition
An experience in using machine learning for short-term predictions in smart transportation systems
Full text linkBike-sharing systems (BSS) are a means of smart transportation with the benefit of a positive impact on urban mobility. To improve the satisfaction of a user of a BSS, it is useful to inform her/him on the status of the stations at run time, and indeed most of the current systems provide the information in terms of number of bicycles parked in each docking stations by means of services available via web. However, when the departure station is empty, the user could also be happy to know how the situation will evolve and, in particular, if a bike is going to arrive (and vice versa when the arrival station is full)
Adopting a Machine Learning Approach in the Design of Smart Transportation Systems
Full text linkWe have applied a machine learning approach to both implement and assess new services for the users of a bike-sharing system. The aim is to predict the destination station of a bike in use, given information on its pick up details
Requirements elicitation and refinement in collaborative research projects
No full textEuropean Union (EU) projects are means of the European Commission for funding research activities. Such projects address challenging research objectives by involving both academic and industrial partners, from several countries. Information and communication technologies–related projects often undertake to deliver a software system prototype. In such a context, most of the typical issues of global requirements engineering may emerge. Partners can have different background and expertise, needs are not sharply defined, and communication is hampered by linguistic and cultural differences. If these issues are not carefully taken into account from the beginning, problems frequently emerge during project execution. This paper presents the experience of applying a customized elicitation and refinement approach in the context of the Learn PAd EU project, which involved about 50 people. The approach combines collaborative elicitation and wiki-based refinement sessions to come to a set of consolidated requirements. Lessons learnt are discussed as a guidance for researchers dealing with analogous issues in similar contexts. Some of the major observations refer to the importance of initial face-to-face meetings when combined with asynchronous remote interactions; the role of moderators that have to encourage collaboration and foster a shared understanding; and the definition of guidelines to select wiki-based platforms
Inconsistency Detection in Natural Language Requirements using ChatGPT: a Preliminary Evaluation
No full textWith the rapid advancement of tools based on Artificial Intelligence, it is interesting to assess their usefulness in requirements engineering. In early experiments, we have seen that ChatGPT can detect inconsistency defects in natural language (NL) requirements, that traditional NLP tools cannot identify or can identify with difficulties even after domain-focused training. This study is devoted to specifically measuring the performance of ChatGPT in finding inconsistency in requirements. Positive results in this respect could lead to the use of ChatGPT to complement existing requirements analysis tools to automatically detect this important quality criterion. For this purpose, we consider GPT-3.5, the Generative Pretrained Transformer language model developed by OpenAI. We evaluate its ability to detect inconsistency by comparing its predictions with those obtained from expert judgments by students with a proven knowledge of RE issues on a few example requirements documents
Context transformations for goal models
No full textThis paper proposes a technique to support the requirements engineer in transforming existing models into new models to address the customer\u27s needs. In particular, we identify a set of possible categories of context change that indicate in which direction the original model needs to evolve. Furthermore, we associate a transformation to each category, and we formalise it in terms of graph grammars. Our results are a generalisation of an experimental evaluation based on 10 models retrieved from the literature and 25 scenarios of context change. This work represents a step forward in the formalisation of requirements models since it provides the foundations of a tool to support the automatic transformation of models, and employs graph grammars to provide a formal layer to the approach
Using Clustering to Improve the Structure of Natural Language Requirements Documents
No full text[Context and motivation] System requirements are normally provided in the form of natural language documents. Such documents need to be properly structured, in order to ease the overall uptake of the requirements by the readers of the document. A structure that allows a proper understanding of a requirements document shall satisfy two main quality attributes: (i) requirements relatedness: each requirement is conceptually connected with the requirements in the same section; (ii) sections independence: each section is conceptually separated from the others. [Question/Problem] Automatically identifying the parts of the document that lack requirements relatedness and sections independence may help improve the document structure. [Principal idea/results] To this end, we define a novel clustering algorithm named Sliding Head-Tail Component (S-HTC). The algorithm groups together similar requirements that are contiguous in the requirements document. We claim that such algorithm allows discovering the structure of the document in the way it is perceived by the reader. If the structure originally provided by the document does not match the structure discovered by the algorithm, hints are given to identify the parts of the document that lack requirements relatedness and sections independence. [Contribution] We evaluate the effectiveness of the algorithm with a pilot test on a requirements standard of the railway domain (583 requirements)
Natural Language Requirements Processing: A 4D Vision
Full text linkThe future evolution of the application of natural language processing technologies in requirements engineering can be viewed from four dimensions: discipline, dynamism, domain knowledge, and datasets
Modelling Dynamic Software Architectures using Typed Graph Grammars
No full textSeveral recent research efforts have focused on the dynamic aspects of software architectures providing suitable models and techniques for handling the run-time modification of the structure of a system. A large number of heterogeneous proposals for addressing dynamic architectures at many different levels of abstraction have been provided, such as programmable, ad-hoc, self-healing and self-repairing among others. It is then important to have a clear picture of the relations among these proposals by formulating them into a uniform framework and contrasting the different verification aspects that can be reasonably addressed by each proposal. Our work is a contribution in this line. In particular, we map several notions of dynamicity into the same formal framework in order to distill the similarities and differences among them. As a result we explain different styles of architectural dynamisms in term of graph grammars and get some better insights on the kinds of formal properties that can be naturally associated to such different specification styles. We take a simple automotive scenario as a running example to illustrate main ideas
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