Dr. Jeff Lei has received two awards from NIST for his project on Combinatorial Testing

Sep. 17, 2012

Dr. Jeff Lei
Dr. Jeff Lei

Dr. Jeff Lei (PI) has received two awards from NIST for his project on Combinatorial Testing $400K.

Associate professor Dr. Jeff Lei (PI) got two grant award from NIST for his research on "Combinatorial Testing for Complex Systems" and "Combinatorial Testing for Healthcare Systems" with a total amount of $400K.

Combinatorial Testing for Complex Systems

Combinatorial testing has been shown to be a very practical and efficient testing strategy. However, before combinatorial testing can be applied to a complex system, the input space of the system, in terms of parameters, values, relations, and constraints, must be modeled properly. The quality of an input parameter model determines, to a large extent, the effectiveness of combinatorial testing.

This project addresses the problem of how to effectively model the input space of complex systems. In particular, the research team will develop input space modeling techniques that derive input space models by analyzing the specification, design, and source code of a complex system, if available. Specification-based techniques can be used in a black-box manner and are often the only choice for system and 3rd-party testing. Design and source code-based techniques can be used by the developers at the development stage. This project is an important step towards our vision to make combinatorial testing part of the toolbox of every software practitioner. The priority of this project is not only placed on abstract research problems, but also on practical problems that are encountered by practitioners.

Combinatorial Testing for Complex Systems

Healthcare information technology has the promise to significantly reduce the cost of healthcare while improving its quality. However, due to the sensitive nature of healthcare, there are major concerns about the reliability, security and privacy of healthcare systems. One important approach to overcoming such concerns is to ensure that healthcare systems conform to standards. Conformance to standards can significantly increase confidence towards adoption of healthcare information technology. Moreover, it is the key to achieving interoperability between different healthcare systems.

The goal of this project is to explore the use of combinatorial testing for conformance and interoperability testing of healthcare systems. Combinatorial testing has been shown to be a very practical and efficient testing strategy, and has several features that are particularly suited for conformance and interoperability testing. In this project, we will focus our effort on three priority areas, including Meaningful Use Test Generation, Healthcare Test Message Generation, and Medical Device Test Generation. We will build software tools to automate the test generation process. The software tools will be designed such that they can be seamlessly integrated with the NIST Healthcare IT Test Infrastructure System.