On the Way to SBOMs: Investigating Design Issues and Solutions in Practice
April 26, 2023 Β· Declared Dead Β· π ACM Transactions on Software Engineering and Methodology
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Tingting Bi, Boming Xia, Zhenchang Xing, Qinghua Lu, Liming Zhu
arXiv ID
2304.13261
Category
cs.SE: Software Engineering
Citations
34
Venue
ACM Transactions on Software Engineering and Methodology
Last Checked
4 months ago
Abstract
The Software Bill of Materials (SBOM) has emerged as a promising solution, providing a machine-readable inventory of software components used, thus bolstering supply chain security. This paper presents an extensive study concerning the practical aspects of SBOM practice. Leveraging an analysis of 4,786 GitHub discussions from 510 SBOM-related projects, our research delineates key topics, challenges, and solutions intrinsic to the effective utilization of SBOMs. Furthermore, we shed light on commonly used tools and frameworks for generating SBOMs, exploring their respective strengths and limitations. Our findings underscore the pivotal role SBOMs play in ensuring resilient software development practices and underscore the imperative of their widespread integration to bolster supply chain security. The insights accrued from our study hold significance as valuable input for prospective research and development in this crucial domain.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted