NFM 2024 - NASA Formal Methods 2024
Date: Jun 04, 2024 8:00 am – Jun 06, 2024 5:00 pm
Location: Moffett Field, CA
Important Dates
Abstract submission: December 1, 2023
Full paper submission: December 8, 2023
Notification, February 16, 2024
Final version: March 15, 2024
Conference: June 4-6 2024
Call for Papers
The widespread use and increasing complexity of mission-critical and safety-critical systems at NASA and in the aerospace industry requires advanced technologies to address their specification, design, verification, validation, and certification processes. There is an increasing need for autonomous systems in deep space systems including NASA’s Moon to Mars exploration plans. The NASA Formal Methods Symposium is a forum to foster collaboration between theoreticians and practitioners from NASA, academia, and industry, with the goal of identifying challenges and providing solutions towards achieving assurance for such critical systems.
Topics of Interest:
We encourage submissions on cross-cutting approaches that bring together formal methods and techniques from other domains such as probabilistic reasoning, machine learning, control theory, robotics, and quantum computing among others.
Advances in Formal Methods
- Formal verification, model checking, and static analysis
- Interactive and automated theorem proving
- Program and specification synthesis, code transformation and generation
- Run-time verification and test case generation
- Techniques and algorithms for scaling formal methods
- Design for verification and correct-by-design techniques
- Requirements generation, specification, and validation
Integration of Formal Methods
- Use of machine learning techniques in formal methods
- Integration of formal methods and software engineering
- Integration of diverse formal methods techniques
- Combination of formal methods with simulation and analysis techniques
Formal Methods in Practice
- Experience reports of application of formal methods in industry
- Use of formal methods in education
- Applications of formal methods in:
- concurrent and distributed systems
- fault-detection, diagnostics, and prognostics systems
- human-machine interaction analysis
Safety Assurance of Autonomous Systems
- Verification of machine learning (ML) enabled systems
- Runtime monitoring or model checking to ensure safe operation
- Formal specifications and modeling of ML enabled systems
- Case-studies/experience reports exploring the application of formal methods in autonomous safety-critical, cyber-physical and hybrid systems
- Using formal evidence for certification of ML enabled systems
Formal Methods for Digital Transformation
- Applications related to Digital Twin & Digital Thread
- Verification for integrated design and manufacturing
- AI digital assistants for system design
- Run-time monitoring for Smart Campus & Smart Cities
Accessibility for New Industries
- “New Space” markets
- Advanced Air Mobility and Startup Aviation
- Formal Methods as a Service
Submit
{ Coming Soon }
Committees
Conference Chairs
Nathan Benz, NASA Ames
Divya Gopinath, KBR / NASA Ames
Nija Shi, NASA Ames
Submitted by Jason Gigax
on
Important Dates
Abstract submission: December 1, 2023
Full paper submission: December 8, 2023
Notification, February 16, 2024
Final version: March 15, 2024
Conference: June 4-6 2024
Call for Papers
The widespread use and increasing complexity of mission-critical and safety-critical systems at NASA and in the aerospace industry requires advanced technologies to address their specification, design, verification, validation, and certification processes. There is an increasing need for autonomous systems in deep space systems including NASA’s Moon to Mars exploration plans. The NASA Formal Methods Symposium is a forum to foster collaboration between theoreticians and practitioners from NASA, academia, and industry, with the goal of identifying challenges and providing solutions towards achieving assurance for such critical systems.
Topics of Interest:
We encourage submissions on cross-cutting approaches that bring together formal methods and techniques from other domains such as probabilistic reasoning, machine learning, control theory, robotics, and quantum computing among others.
Advances in Formal Methods
- Formal verification, model checking, and static analysis
- Interactive and automated theorem proving
- Program and specification synthesis, code transformation and generation
- Run-time verification and test case generation
- Techniques and algorithms for scaling formal methods
- Design for verification and correct-by-design techniques
- Requirements generation, specification, and validation
Integration of Formal Methods
- Use of machine learning techniques in formal methods
- Integration of formal methods and software engineering
- Integration of diverse formal methods techniques
- Combination of formal methods with simulation and analysis techniques
Formal Methods in Practice
- Experience reports of application of formal methods in industry
- Use of formal methods in education
- Applications of formal methods in:
- concurrent and distributed systems
- fault-detection, diagnostics, and prognostics systems
- human-machine interaction analysis
Safety Assurance of Autonomous Systems
- Verification of machine learning (ML) enabled systems
- Runtime monitoring or model checking to ensure safe operation
- Formal specifications and modeling of ML enabled systems
- Case-studies/experience reports exploring the application of formal methods in autonomous safety-critical, cyber-physical and hybrid systems
- Using formal evidence for certification of ML enabled systems
Formal Methods for Digital Transformation
- Applications related to Digital Twin & Digital Thread
- Verification for integrated design and manufacturing
- AI digital assistants for system design
- Run-time monitoring for Smart Campus & Smart Cities
Accessibility for New Industries
- “New Space” markets
- Advanced Air Mobility and Startup Aviation
- Formal Methods as a Service
Submit
{ Coming Soon }
Committees
Conference Chairs
Nathan Benz, NASA Ames
Divya Gopinath, KBR / NASA Ames
Nija Shi, NASA Ames