Call For Papers
Artificial Intelligence (AI) technologies are widely used in computer applications to perform tasks such as monitoring, forecasting, recommending, prediction, and statistical reporting. They are deployed in a variety of systems including driverless vehicles, robot controlled warehouses, financial forecasting applications, and security enforcement and are increasingly integrated with cloud/fog/edge computing, big data analytics, robotics, Internet-of-Things, mobile computing, smart cities, smart homes, intelligent healthcare, etc. In spite of this dramatic progress, the quality assurance of existing AI application development processes is still far from satisfactory and the demand for being able to show demonstrable levels of confidence in such systems is growing. Software testing is a fundamental, effective and recognized quality assurance method which has shown its cost-effectiveness to ensure the reliability of many complex software systems. However, the adaptation of software testing to the peculiarities of AI applications remains largely unexplored and needs extensive research to be performed. On the other hand, the availability of AI technologies provides an exciting opportunity to improve existing software testing processes, and recent years have shown that machine learning, data mining, knowledge representation, constraint optimization, planning, scheduling, multi-agent systems, etc. have real potential to positively impact on software testing. Recent years have seen a rapid growth of interests in testing AI applications as well as application of AI techniques to software testing. This conference provides an international forum for researchers and practitioners to exchange novel research results, to articulate the problems and challenges from practices, to deepen our understanding of the subject area with new theories, methodologies, techniques, processes models, etc., and to improve the practices with new tools and resources.
The conference invites papers of original research on AI testing and reports of the best practices in the industry as well as the challenges in practice and research. Topics of interest include (but are not limited to) the following:
We welcome submissions of both regular research papers (limited to 8 pages), that describe original and significant work or report on case studies and empirical research, and short papers (limited to 2 pages) that describe late-breaking research results or work in progress with timely and innovative ideas.
The AI Testing in Practice Track provides a forum for networking, exchanging ideas and innovative or experimental practices to address SE research that impacts directly on practice on software testing for AI.
The tool track provides a forum to present and demonstrate innovative tools and/or new benchmarking datasets in the context of software testing for AI.
All papers must be submitted electronically in PDF format using the IEEE Computer Society Proceedings format (two columns, single-spaced, 10pt font). Papers must not be accepted for publication, or be under submission to another conference or journal. Each paper will be reviewed by at least three members of the Program Committee, using a single-blind reviewing procedure. At least one author of the accepted paper must register for the conference and confirm that she/he will present the paper in person.