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Abstract: Understanding the behaviour of a system’s API can be hard. Giving users access to relevant examples of how an API behaves has been shown to make this easier for them. In addition, such examples can be used to verify expected behaviour or identify unwanted behaviours. Methods for automatically generating examples have existed for a long time. However, state-of-the-art methods rely on either white-b...
Abstract: Multi-core architectures have grown to be a popular choice for deploying Mixed Criticality Systems (MCS). The focus of research in MCS has been to provide timing assurances for jobs with different criticality levels. Due to their significant processing demands and energy-aware/constrained nature, energy conservation in these systems is becoming mandatory. This article presents, mcDVFS, an energy m...
Abstract: There is a growing body of knowledge on network intrusion detection, and several open data sets with network traffic and cyber-security threats have been released in the past decades. However, many data sets have aged, were not collected in a contemporary industrial communication system, or do not easily support research focusing on distributed anomaly detection. This paper presents the Westermo n...
Abstract: Autoencoder is a widely used deep learning method, which first extracts features from all data through unsupervised reconstruction, and then fine-tunes the network with labeled data. However, due to the limited number of labeled data samples, the network may lack sufficient generalization ability and is prone to overfitting. This article proposes a new semisupervised deep learning method called fe...
Abstract: Designing MMLA systems is a complex task requiring a wide range of considerations. In this paper, we identify key considerations that are essential for designing MMLA systems. These considerations include data management, human factors, sensors and modalities, learning scenarios, privacy and ethics, interpretation and feedback, and data collection. The implications of these considerations are twof...
Abstract: There is a growing number of network attacks and the data on the network is more exposed than ever with the increased activity on the Internet. Applying Machine Learning (ML) techniques for cyber-security is a popular and effective approach to address this problem. However, the data which is used by ML algorithms have to be protected. In this paper, we present a framework that combines autoencoder...
Abstract: Natural Language Processing (NLP) for Requirements Engineering (RE) (NLP4RE) seeks to apply NLP tools, techniques, and resources to the RE process to increase the quality of the requirements. There is little research involving the utilization of Generative AI-based NLP tools and techniques for requirements elicitation. In recent times, Large Language Models (LLM) like ChatGPT have gained significa...
Abstract: Mobile apps form a major proportion of the software marketplace and it is crucial to ensure that they meet both functional and nonfunctional quality thresholds. Automated test input generation can reduce the cost of the testing process. However, existing Android test generation approaches are focused on code coverage and cannot be customized to a tester's diverse goals---in particular, quality att...
Abstract: Hazard analysis for a single system focuses on identifying and evaluating potential hazards associated with the individual system, its components, and their interactions. There are well-established hazard analysis techniques that are widely used to identify hazards for single systems. However, unlike single systems, hazard analysis in a System of Systems (SoS) must focus on analyzing the potential...
Abstract: In this paper, we investigate the problem of modeling time-series as a process generated through (i) switching between several independent sub-models; (ii) where each sub-model has heteroskedastic noise, and (iii) a polynomial bias, describing nonlinear dependency on system input. First, we propose a generic nonlinear and heteroskedastic statistical model for the process. Then, we design Maximum L...
Abstract: This report describes how software professionals at the Norwegian public transport organization Entur use open source processes and tools to leverage digital transformation. Moving software acquisition from procurement to open source and in-house development can deliver value but also entails challenges....
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