During its life, a legacy system is subjected to many maintenance activities, which cause degradation of the quality of the system: When this degradation exceeds a critical threshold, the legacy system needs to be reengineered. In order to preserve the asset represented by the legacy system, the familiarity with it gained by the system's maintainers and users, and the continuity of execution of current operations during the reengineering process, the system needs to be reengineered gradually. Moreover, each program needs to be reengineered within a short period of time. The paper proposes a reengineering process model, which is applied to an in-use legacy system to confirm that the process satisfies previous requirements and to measure its effectiveness. The reengineered system replaced the legacy one to the satisfaction of all the stakeholders; the reengineering process also had a satisfactory impact on the quality of the system. Finally, this paper contributes to validate the cause-effect relationship between the reengineering process and overcoming the aging symptoms of a software system.
The diffusion of embedded and portable communication devices on modern vehicles entails new security risks since in-vehicle communication protocols are still insecure and vulnerable to attacks. Increasing interest is being given to the implementation of automotive cybersecurity systems. In this work we propose an efficient and high-performing intrusion detection system based on an unsupervised Kohonen Self-Organizing Map (SOM) network, to identify attack messages sent on a Controller Area Network (CAN) bus. The SOM network found a wide range of applications in intrusion detection because of its features of high detection rate, short training time, and high versatility. We propose to extend the SOM network to intrusion detection on in-vehicle CAN buses. Many hybrid approaches were proposed to combine the SOM network with other clustering methods, such as the k-means algorithm, in order to improve the accuracy of the model. We introduced a novel distance-based procedure to integrate the SOM network with the K-means algorithm and compared it with the traditional procedure. The models were tested on a car hacking dataset concerning traffic data messages sent on a CAN bus, characterized by a large volume of traffic with a low number of features and highly imbalanced data distribution. The experimentation showed that the proposed method greatly improved detection accuracy over the traditional approach.
Software systems are affected by degradation as an effect of continuous change. Since late interventions are too much onerous, software degradation should be detected early in the software lifetime. Software degradation is currently detected by using many different complexity metrics, but their use to monitor maintenance activities is costly. These metrics are difficult to interpret, because each emphasizes a particular aspect of degradation and the aspects shown by different metrics are not orthogonal. The purpose of our research is to measure the entropy of a software system to assess its degradation. In this paper, we partially validate the entropy class of metrics by a case study, replicated on successive releases of a set of software systems. The validity is shown through direct measures of software quality such as the number of detected defects, the maintenance effort and the number of slipped defects.
This paper examines the cloud computing for education (CCE) literature, and analyzes if the research is developing scientifically with adequate empirical validation. All aspects of empirical investigations covered in the literature are shown as weak, hence, the necessary scientific development of CCE requires extending its scope of interest, and involving scholars synergistically to create and maintain a "common research agenda."Background: A need to develop research on CCE has been recognized, and considerable efforts made to create an accurate understanding of the development of its scope of interest, in terms of supporting pedagogical developments and processes for better quality of studies.Research Questions: This paper has three main aims: 1) to evaluate the scope of interest in the literature for CCE with specific reference to pedagogy and educational processes; 2) to analyze the characteristics of papers, specifically empirical studies, from the various points of view of the daily improvement activities of teachers and learners at all levels of education; and 3) to identify eventual research gaps to consider and stimulate new topics or further investigations.Methodology: This systematic mapping study review followed a rigorous, replicable process to collect and analyze representative studies of CCE.Findings: Differences are found across geographic areas in applying CCE infrastructure and technologies in educational institutions; few studies address CCE's impact on pedagogic processes. The scope of interest in CCE is only partially covered; with empirical research being very shallow. Suggestions are made for more effective research on concerning the production and use of content.
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