Cover Image

BOMs Away! Inside the Minds of Stakeholders: A Comprehensive Study of Bills of Materials for Software Systems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Stalnaker, Trevor, Wintersgill, Nathan, Chaparro, Oscar, Di Penta, Massimiliano, German, Daniel M, Poshyvanyk, Denys
Format:	Preprint
Published:	2023
Subjects:	Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Prompting in Practice: Investigating Software Practitioners' Use of Generative AI Tools
by: Otten, Daniel, et al.
Published: (2025)

Developer Perspectives on Licensing and Copyright Issues Arising from Generative AI for Software Development
by: Stalnaker, Trevor, et al.
Published: (2024)

Developers' Perspectives on Software Licensing: Current Practices, Challenges, and Tools
by: Wintersgill, Nathan, et al.
Published: (2025)

"The Law Doesn't Work Like a Computer": Exploring Software Licensing Issues Faced by Legal Practitioners
by: Wintersgill, Nathan, et al.
Published: (2024)

An Empirical Analysis of Machine Learning Model and Dataset Documentation, Supply Chain, and Licensing Challenges on Hugging Face
by: Stalnaker, Trevor, et al.
Published: (2025)

"Don't Be Afraid, Just Learn": Insights from Industry Practitioners to Prepare Software Engineers in the Age of Generative AI
by: Otten, Daniel, et al.
Published: (2026)

Challenges and Practices in Quantum Software Testing and Debugging: Insights from Practitioners
by: Zappin, Jake, et al.
Published: (2025)

Bridging the Quantum Divide: Aligning Academic and Industry Goals in Software Engineering
by: Zappin, Jake, et al.
Published: (2025)

When Quantum Meets Classical: Characterizing Hybrid Quantum-Classical Issues Discussed in Developer Forums
by: Zappin, Jake, et al.
Published: (2024)

Augmenting Software Bills of Materials with Software Vulnerability Description: A Preliminary Study on GitHub
by: Fucci, Davide, et al.
Published: (2025)

A Path Less Traveled: Reimagining Software Engineering Automation via a Neurosymbolic Paradigm
by: Mastropaolo, Antonio, et al.
Published: (2025)

Semantic GUI Scene Learning and Video Alignment for Detecting Duplicate Video-based Bug Reports
by: Yan, Yanfu, et al.
Published: (2024)

Automated Refactoring of Non-Idiomatic Python Code: A Differentiated Replication with LLMs
by: Midolo, Alessandro, et al.
Published: (2025)

Machine Learning in the Wild: Early Evidence of Non-Compliant ML-Automation in Open-Source Software
by: Arshid, Zohaib, et al.
Published: (2026)

Towards Enabling An Artificial Self-Construction Software Life-cycle via Autopoietic Architectures
by: Rodriguez-Cardenas, Daniel, et al.
Published: (2026)

On the Generalizability of Transformer Models to Code Completions of Different Lengths
by: Cooper, Nathan, et al.
Published: (2025)

From Human to Machine Refactoring: Assessing GPT-4's Impact on Python Class Quality and Readability
by: Midolo, Alessandro, et al.
Published: (2026)

Towards Comprehensive Benchmarking Infrastructure for LLMs In Software Engineering
by: Rodriguez-Cardenas, Daniel, et al.
Published: (2026)

On Interpreting the Effectiveness of Unsupervised Software Traceability with Information Theory
by: Palacio, David N., et al.
Published: (2024)

Measuring Emergent Capabilities of LLMs for Software Engineering: How Far Are We?
by: O'Brien, Conor, et al.
Published: (2024)

A Taxonomy of Self-Admitted Technical Debt in Deep Learning Systems
by: Pepe, Federica, et al.
Published: (2024)

Software Bills of Materials in Maven Central
by: Gamage, Yogya, et al.
Published: (2025)

Toward Neurosymbolic Program Comprehension
by: Velasco, Alejandro, et al.
Published: (2025)

Do LLMs Provide Links to Code Similar to what they Generate? A Study with Gemini and Bing CoPilot
by: Bifolco, Daniele, et al.
Published: (2025)

How the Training Procedure Impacts the Performance of Deep Learning-based Vulnerability Patching
by: Mastropaolo, Antonio, et al.
Published: (2024)

Mapping the Trust Terrain: LLMs in Software Engineering -- Insights and Perspectives
by: Khati, Dipin, et al.
Published: (2025)

Future of Software Engineering Research: The SIGSOFT Perspective
by: Di Penta, Massimiliano, et al.
Published: (2026)

Towards More Trustworthy Deep Code Models by Enabling Out-of-Distribution Detection
by: Yan, Yanfu, et al.
Published: (2025)

Policy-driven Software Bill of Materials on GitHub: An Empirical Study
by: Novikov, Oleksii, et al.
Published: (2025)

"Let it be Chaos in the Plumbing!" Usage and Efficacy of Chaos Engineering in DevOps Pipelines
by: Fossati, Stefano, et al.
Published: (2025)

Rethinking Software Empirical Studies with Structural Causal Models
by: Rodriguez-Cardenas, Daniel, et al.
Published: (2026)

Unveiling ChatGPT's Usage in Open Source Projects: A Mining-based Study
by: Tufano, Rosalia, et al.
Published: (2024)

Evaluating the Impact of Post-Training Quantization on Large Language Models for Code Generation
by: Giagnorio, Alessandro, et al.
Published: (2025)

Optimizing Datasets for Code Summarization: Is Code-Comment Coherence Enough?
by: Vitale, Antonio, et al.
Published: (2025)

A Landscape Study of Open Source and Proprietary Tools for Software Bill of Materials (SBOM)
by: Mirakhorli, Mehdi, et al.
Published: (2024)

Which Syntactic Capabilities Are Statistically Learned by Masked Language Models for Code?
by: Velasco, Alejandro, et al.
Published: (2024)

Perspective of Software Engineering Researchers on Machine Learning Practices Regarding Research, Review, and Education
by: Mojica-Hanke, Anamaria, et al.
Published: (2024)

Developers and Generative AI: A Study of Self-Admitted Usage in Open Source Projects
by: Tufano, Rosalia, et al.
Published: (2026)

How are MLOps Frameworks Used in Open Source Projects? An Empirical Characterization
by: Zampetti, Fiorella, et al.
Published: (2026)

Automatic Categorization of GitHub Actions with Transformers and Few-shot Learning
by: Nguyen, Phuong T., et al.
Published: (2024)