Related papers: Building an Open AIBOM Standard in the Wild

Software Bills of Materials (SBOMs) have emerged as tools to facilitate the management of software dependencies, vulnerabilities, licenses, and the supply chain. While significant effort has been devoted to increasing SBOM awareness and…

Ensuring the security of software supply chains requires reliable identification of upstream dependencies. We present the Automatic Bill of Materials, or ABOM, a technique for embedding dependency metadata in binaries at compile time.…

Background. The Software Bill of Materials (SBOM) is a machine-readable list of all the software dependencies included in a software. SBOM emerged as way to assist securing the software supply chain. However, despite mandates from…

Empirical Standards are natural-language models of a scientific community's expectations for a specific kind of study (e.g. a questionnaire survey). The ACM SIGSOFT Paper and Peer Review Quality Initiative generated empirical standards for…

Software Bills of Materials (SBOMs) are essential to ensure the transparency and integrity of the software supply chain. There is a growing body of work that investigates the accuracy of SBOM generation tools and the challenges for…

The SolarWinds attack, which exploited weaknesses in a software update mechanism, highlights the critical need for organizations to have better visibility into their software dependencies and potential vulnerabilities associated with them.…

A Software Bill of Materials (SBOM) is a key component for the transparency of software supply chain; it is a structured inventory of the components, dependencies, and associated metadata of a software artifact. However, an SBOM often…

Large language models (LLMs) for code generation are becoming integral to modern software development, but their real-world prevalence and security impact remain poorly understood. We present the first large-scale empirical study of…

Software Quality Assurance (SQA) is critical for delivering reliable, secure, and efficient software products. The Software Quality Assurance Process aims to provide assurance that work products and processes comply with predefined…

Modern networked systems rely on complex software stacks, which often conceal vulnerabilities arising from intricate interdependencies. A Software Bill of Materials (SBOM) is effective for identifying dependencies and mitigating security…

Despite the widespread adoption of agile methods, achieving true agility at scale remains elusive. Large-scale agile frameworks remain largely human-centric and manual, relying on coordination meetings, artifact synchronization, and…

AI-based systems are software systems with functionalities enabled by at least one AI component (e.g., for image- and speech-recognition, and autonomous driving). AI-based systems are becoming pervasive in society due to advances in AI.…

AI-based systems leverage recent advances in the field of AI/ML by combining traditional software systems with AI components. Applications are increasingly being developed in this way. Software engineers can usually rely on a plethora of…

Current software development takes advantage of many external libraries, but it entails security and copyright risks. While the use of the Software Bill of Materials (SBOM) has been encouraged to cope with this problem, its adoption is…

Privacy regulations mandate that developers must provide authentic and comprehensive privacy notices, e.g., privacy policies or labels, to inform users of their apps' privacy practices. However, due to a lack of knowledge of privacy…

The Software Bill of Materials (SBOM) is a critical tool for securing the software supply chain (SSC), but its practical utility is undermined by inaccuracies in both its generation and its application in vulnerability scanning. This paper…

As Artificial Intelligence (AI) tools are increasingly employed in diverse real-world applications, there has been significant interest in regulating these tools. To this end, several regulatory frameworks have been introduced by different…

Although AI is transforming the world, there are serious concerns about its ability to behave and make decisions responsibly. Many ethical regulations, principles, and frameworks for responsible AI have been issued recently. However, they…

Adopting shared data resources requires scientists to place trust in the originators of the data. When shared data is later used in the development of artificial intelligence (AI) systems or machine learning (ML) models, the trust lineage…

In the era of advanced artificial intelligence, highlighted by large-scale generative models like GPT-4, ensuring the traceability, verifiability, and reproducibility of datasets throughout their lifecycle is paramount for research…