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Autor:
Lazzari G, Benevento I, Montagna A, D'Andrea B, De Marco G, Castaldo G, Bianculli A, Tucciariello R, Metallo V, Solazzo AP
Publikováno v:
Breast Cancer: Targets and Therapy, Vol Volume 16, Pp 359-367 (2024)
Grazia Lazzari,1 Ilaria Benevento,1 Antonietta Montagna,1 Barbara D’Andrea,1 Giuseppina De Marco,2 Giovanni Castaldo,1 Antonella Bianculli,3 Raffaele Tucciariello,3 Vito Metallo,1 Angela Pia Solazzo1 1Radiation Oncology Unit, IRCCS, CROB, Rionero i
Externí odkaz:
https://doaj.org/article/045012a1700845d092cd84e89d53c80a
Log-based anomaly detection has been widely studied in the literature as a way to increase the dependability of software-intensive systems. In reality, logs can be unstable due to changes made to the software during its evolution. This, in turn, degr
Externí odkaz:
http://arxiv.org/abs/2406.07467
Metamorphic testing (MT) has proven to be a successful solution to automating testing and addressing the oracle problem. However, it entails manually deriving metamorphic relations (MRs) and converting them into an executable form; these steps are ti
Externí odkaz:
http://arxiv.org/abs/2401.17019
Publikováno v:
ACM Trans. Softw. Eng. Methodol. 33, 3, Article 77 (March 2024), 32 pages
Data entry forms use completeness requirements to specify the fields that are required or optional to fill for collecting necessary information from different types of users. However, some required fields may not be applicable for certain types of us
Externí odkaz:
http://arxiv.org/abs/2311.13517
Growth in system complexity increases the need for automated techniques dedicated to different log analysis tasks such as Log-based Anomaly Detection (LAD). The latter has been widely addressed in the literature, mostly by means of a variety of deep
Externí odkaz:
http://arxiv.org/abs/2307.16714
Publikováno v:
Empir Software Eng 29, 139 (2024)
Software systems log massive amounts of data, recording important runtime information. Such logs are used, for example, for log-based anomaly detection, which aims to automatically detect abnormal behaviors of the system under analysis by processing
Externí odkaz:
http://arxiv.org/abs/2305.15897
Publikováno v:
Empir Software Eng 29, 105 (2024)
With the increasing complexity and scope of software systems, their dependability is crucial. The analysis of log data recorded during system execution can enable engineers to automatically predict failures at run time. Several Machine Learning (ML)
Externí odkaz:
http://arxiv.org/abs/2303.07230
Publikováno v:
ACM Trans. Softw. Eng. Methodol. 33, 2, Article 35 (February 2024), 58 pages
Cyber-Physical Systems (CPSs) are often safety-critical and deployed in uncertain environments. Identifying scenarios where CPSs do not comply with requirements is fundamental but difficult due to the multidisciplinary nature of CPSs. We investigate
Externí odkaz:
http://arxiv.org/abs/2302.13913
Publikováno v:
ACM Trans. Softw. Eng. Methodol. 33, 4, Article 95 (May 2024), 39 pages
Models such as finite state automata are widely used to abstract the behavior of software systems by capturing the sequences of events observable during their execution. Nevertheless, models rarely exist in practice and, when they do, get easily outd
Externí odkaz:
http://arxiv.org/abs/2211.16587
Publikováno v:
IEEE Transactions on Software Engineering, vol. 49, no. 5, pp. 3131-3154, 1 May 2023
Most of the trace-checking tools only yield a Boolean verdict. However, when a property is violated by a trace, engineers usually inspect the trace to understand the cause of the violation; such manual diagnostic is time-consuming and error-prone. Ex
Externí odkaz:
http://arxiv.org/abs/2206.04024