Concepts in Testing of Autonomous Systems: Academic Literature and Industry Practice
This work addresses the need for better testing methods in safety-critical autonomous systems, but it is incremental as it primarily reviews and synthesizes existing knowledge without introducing new techniques.
The paper tackles the problem of testing autonomous systems by synthesizing academic literature with industry insights to conceptualize these systems and classify testing challenges and practices. The result is a framework identifying gaps that require more research to improve quality and safety.
Testing of autonomous systems is extremely important as many of them are both safety-critical and security-critical. The architecture and mechanism of such systems are fundamentally different from traditional control software, which appears to operate in more structured environments and are explicitly instructed according to the system design and implementation. To gain a better understanding of autonomous systems practice and facilitate research on testing of such systems, we conducted an exploratory study by synthesizing academic literature with a focus group discussion and interviews with industry practitioners. Based on thematic analysis of the data, we provide a conceptualization of autonomous systems, classifications of challenges and current practices as well as of available techniques and approaches for testing of autonomous systems. Our findings also indicate that more research efforts are required for testing of autonomous systems to improve both the quality and safety aspects of such systems.