Important Dates
Workshop/Tutorial proposals:
Nov. 15, 2018
Abstract submission:
Dec. 7, 2018
Full paper submission:
Dec. 21, 2018 12:00 AOE (firm)
Notification:
Feb. 15, 2019 (firm)
Final Paper and Registration:
Feb. 28, 2019 (firm)
Conference:
Apr 4 - 9, 2019
About The Conference:
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. However, 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. It
is, therefore, timely to provide 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. This is the aim of the IEEE conference on AI Testing.