Artificial intelligence systems have played important roles in many fields such as image recognition, speech recognition, machine translation, and intrusion detection. At present, artificial intelligence systems have an increased role in safety-critical systems, which makes its correctness and reliability crucial. The intelligent characteristics and learning capability of artificial intelligence systems bring a new failure type that traditional software does not have. Therefore, it is necessary to put forward suitable and effective testing techniques and reliability assurance methods for artificial intelligence systems.
This workshop seeks to bring together researchers and practitioners working toward the improvement of reliability for intelligent systems by discussing recent developments and current challenges and exchanging their research findings and experiences. The workshop welcomes papers and presentations in the field of artificial intelligence systems, dealing with intelligent software reliability and testing.
The list of topics includes, but is not limited to:
Authors are invited to submit original unpublished research papers as well as industrial practice papers. Simultaneous submissions to other conferences are not permitted. Detailed instructions for electronic paper submission, panel proposals, and review process can be found at QRS submission.
Each submission can have a maximum of ten pages. It should include a title, the name and affiliation of each author, a 300-word abstract, and up to 6 keywords. Shorter version papers (up to six pages) are also allowed.
All papers must conform to the QRS conference proceedings format (PDF | Word DOCX | Latex) and Submission Guideline set in advance by QRS 2025. At least one of the authors of each accepted paper is required to pay the full registration fee and present the paper at the workshop. Submissions must be in PDF format and uploaded to the conference submission site. Arrangements are being made to publish extended version of top-quality papers in selected SCI journals.
SubmissionName | Affiliation | Geographic Region |
---|---|---|
Jun Ai | Beihang University | China |
Minyan Lu | Beihang University | China |
Lingzhong Meng | Institute of Software, Chinese Academy of Sciences | China |