Karim Elish
Florida Polytechnic University, USA
Organizing Chair
About ASSURE-AI
AI-assisted software engineering is becoming integral to software analysis, evolution, maintenance, and reengineering. Developers increasingly rely on coding assistants and agentic tools to inspect code, review pull requests, generate patches, repair defects, refactor systems, update dependencies, write tests, and explain vulnerabilities. While these tools can improve productivity, they can also introduce vulnerabilities, produce incomplete fixes, or create unwarranted confidence in insecure software.
ASSURE-AI advances security assurance for AI-assisted software engineering by examining the evidence, methods, and validation processes needed to determine whether AI-generated or AI-modified software is ready for review, integration, or deployment. The workshop welcomes research and experience on vulnerability analysis, code review, patch validation, regression analysis, security testing, provenance, auditability, compliance, benchmarks, datasets, and human-in-the-loop validation across both agentic and non-agentic AI tools.
Motivation
Productivity gains from AI-assisted development do not, by themselves, establish that the resulting software is secure or ready for deployment. ASSURE-AI addresses this gap by focusing on security claims supported by concrete evidence, such as static and dynamic analysis, security testing, manual review, compliance mappings, repository history, and reproducible benchmarks.
A key concern is false assurance: situations in which an AI tool, agent, review assistant, benchmark result, or explanation gives developers unwarranted confidence that software is secure without sufficient supporting evidence.
Topics of Interest
We welcome submissions on topics including, but not limited to:
- Security assurance for AI-generated code
- AI-assisted vulnerability analysis
- Secure code review
- Patch validation and safe repair
- AI-supported security testing
- Evidence models for security claims
- False assurance and overconfidence
- Secure AI-assisted refactoring
- Secure dependency updates
- Benchmarks, datasets, and metrics
- Provenance and audit trails
- Compliance and secure maintenance
- Human-in-the-loop validation
- Industry experience with AI agents
Call for Submissions
ASSURE-AI solicits original submissions that advance research and practice in security assurance for AI-assisted software engineering. We welcome research contributions, short and position papers, tool and dataset papers, benchmark papers, and industry experience reports.
| Submission Type | Page Limit | Scope |
|---|---|---|
| Full papers | Up to 8 pages | Original research on security assurance for AI-assisted software engineering |
| Short and position papers | Up to 4 pages | Early results, focused empirical studies, emerging ideas, and research agendas |
| Tool, dataset, and benchmark papers | Up to 4 pages | Tools, datasets, evaluation frameworks, benchmarks, and replication packages |
| Industry experience reports | Up to 4 pages | Practical experiences with validating AI-generated or AI-modified software changes |
Submission Guidelines
All submissions must be written in English and submitted in PDF format. Submissions must follow the official SANER workshop submission instructions and IEEE conference proceedings format. Full papers may be up to 8 pages. All other submission types may be up to 4 pages. Page limits exclude references unless otherwise specified by the official SANER workshop instructions.
Submissions must be original and not under review elsewhere. Each submission will be reviewed by at least three program committee members and evaluated for relevance, clarity, novelty, technical quality, and potential to stimulate workshop discussion.
Publication Statement
Accepted papers are expected to be included in the SANER companion proceedings, following the official SANER workshop requirements.
Important Dates
All deadlines are AoE (UTC-12h), unless otherwise stated by SANER.
Abstract submissionOctober 19, 2026
Paper submissionOctober 23, 2026
Author notificationDecember 8, 2026
Camera-ready submissionJanuary 8, 2027
Workshop dateMarch 9, 2027
Workshop Format
ASSURE-AI is planned as a full-day interactive workshop. The program will combine invited and peer-reviewed content with structured discussions to encourage community building around evidence-based security assurance for AI-assisted software engineering.
- Opening and workshop framing
- Invited keynote talk
- Presentations of accepted research, position, tool, dataset, benchmark, and industry papers
- Industry/practice panel on assurance in deployed AI-assisted development workflows
- Structured breakout discussion on evidence and benchmark gaps
- Closing synthesis to identify community priorities and collaboration opportunities
Organizing Committee
Hamoud Aljamaan
King Fahd University of Petroleum and Minerals, Saudi Arabia
Organizing Co-chair
& Proceedings Chair
Willy Susilo
University of Wollongong, Australia
Steering Committee Member
David Mohaisen
University of Central Florida, USA
Steering Committee Member
Mohammad Hammoudeh
King Fahd University of Petroleum and Minerals, Saudi Arabia
Steering Committee Member
Xiaokui Shu
IBM Research, USA
Organizing Co-chair
Program Committee
Coming soon …
Contact
For questions about ASSURE-AI, please contact: kelish@floridapoly.edu.