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Users use Issue Tracking Systems to keep track and manage issue reports in their repositories. An issue is a rich source of software information that contains different reports including a problem, a request for new features, or merely a…
The adequate testing of stateful software systems is a hard and costly activity. Failures that result from complex stateful interactions can be of high impact, and it can be hard to replicate failures resulting from erroneous stateful…
The enhanced efficiency of hardware accelerators, including Single Instruction Multiple Data (SIMD) architectures and Coarse-Grained Reconfigurable Architectures (CGRAs), is driving significant advancements in Artificial Intelligence and…
Sensor systems are extremely popular today and vulnerable to sensor data attacks. Due to possible devastating consequences, counteracting sensor data attacks is an extremely important topic, which has not seen sufficient study. This paper…
This research investigates the variety and complexity of situational impairment events (SIE) that are being experienced by users of smartphone technology of all abilities. The authors have created a classification system to help describe…
The rapidly evolving field of autonomous driving systems (ADSs) is full of promise. However, in order to fulfil these promises, ADSs need to be safe in all circumstances. This paper introduces ISS-Scenario, an autonomous driving testing…
AI agents are increasingly autonomous in their interactions with human users and tools, leading to increased interactional safety risks. We present HAICOSYSTEM, a framework examining AI agent safety within diverse and complex social…
An Application Specific Instruction set Processor (ASIP) is an important component in designing embedded systems. One of the problems in designing an instruction set for such processors is determining the number of registers is needed in…
This paper presents a novel, structured decision support framework that systematically aligns diverse artificial intelligence (AI) agent architectures, reactive, cognitive, hybrid, and learning, with the comprehensive National Institute of…
AI-based systems, currently driven largely by LLMs and tool-using agentic harnesses, are increasingly discussed as a possible threat to software engineering. Foundation models get stronger, agents can plan and act across multiple steps, and…
Sixth generation (6G) wireless technology is anticipated to introduce Integrated Sensing and Communication (ISAC) as a transformative paradigm. ISAC unifies wireless communication and RADAR or other forms of sensing to optimize spectral and…
This paper investigates whether large-scale GNSS spoofing activity can be inferred from maritime Automatic Identification System (AIS) position reports. A data-processing framework, called SeaSpoofFinder, available here:…
As Artificial Intelligence (AI) techniques have become more powerful and easier to use they are increasingly deployed as key components of modern software systems. While this enables new functionality and often allows better adaptation to…
Explainable AI (XAI) can greatly enhance user trust and satisfaction in AI-assisted decision-making processes. Recent findings suggest that a single explainer may not meet the diverse needs of multiple users in an AI system; indeed, even…
The Artificial intelligence in critical sectors-healthcare, finance, and public safety-has made system integrity paramount for maintaining societal trust. Current verification methods for AI systems lack comprehensive lifecycle assurance,…
We develop and study new adversarial perturbations that enable an attacker to gain control over decisions in generic Artificial Intelligence (AI) systems including deep learning neural networks. In contrast to adversarial data modification,…
Safety alignment -- training large language models (LLMs) to refuse harmful requests while remaining helpful -- is critical for responsible deployment. Prior work established that safety behaviors are governed by low-rank structures,…
Functional programs typically interact with stateful libraries that hide state behind typed abstractions. One particularly important class of applications are data structure implementations that rely on such libraries to provide a level of…
We present LISA, an agentic smart contract vulnerability detection framework that combines rule-based and logic-based methods to address a broad spectrum of vulnerabilities in smart contracts. LISA leverages data from historical audit…
To effectively address potential harms from AI systems, it is essential to identify and mitigate system-level hazards. Current analysis approaches focus on individual components of an AI system, like training data or models, in isolation,…