Zobrazeno 1 - 10
of 91
pro vyhledávání: '"Shin, Donghwan"'
Typical autonomous driving systems are a combination of machine learning algorithms (often involving neural networks) and classical feedback controllers. Whilst significant progress has been made in recent years on the neural network side of these sy
Externí odkaz:
http://arxiv.org/abs/2402.05064
Autor:
Li, Ziyu, Shin, Donghwan
Large Language Models (LLMs) have shown remarkable capabilities in processing both natural and programming languages, which have enabled various applications in software engineering, such as requirement engineering, code generation, and software test
Externí odkaz:
http://arxiv.org/abs/2401.05940
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
In Machine Learning (ML)-enabled autonomous systems (MLASs), it is essential to identify the hazard boundary of ML Components (MLCs) in the MLAS under analysis. Given that such boundary captures the conditions in terms of MLC behavior and system cont
Externí odkaz:
http://arxiv.org/abs/2301.13807
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
Deep Neural Networks (DNNs) have been widely used to perform real-world tasks in cyber-physical systems such as Autonomous Driving Systems (ADS). Ensuring the correct behavior of such DNN-Enabled Systems (DES) is a crucial topic. Online testing is on
Externí odkaz:
http://arxiv.org/abs/2210.15432
Over recent decades, scenarios and scenario-based software/system engineering have been actively employed as essential tools to handle intricate problems, validate requirements, and support stakeholders' communication. However, despite the widespread
Externí odkaz:
http://arxiv.org/abs/2205.08290
Cyber-Physical Systems (CPS) continuously interact with their physical environments through software controllers that observe the environments and determine actions. Engineers can verify to what extent the CPS under analysis can achieve given goals b
Externí odkaz:
http://arxiv.org/abs/2204.06799
Publikováno v:
Empir Software Eng 27, 87 (2022)
Behavioral software models play a key role in many software engineering tasks; unfortunately, these models either are not available during software development or, if available, quickly become outdated as implementations evolve. Model inference techn
Externí odkaz:
http://arxiv.org/abs/2106.01987