UNIVERSITY PARK, Pa. — Gang Tan, associate professor of computer science and engineering at Penn State, and colleagues have been awarded two research grants to help them design a software tool chain — languages compilers and runtime systems — that will allow programmers to take advantage of modern memory features, including encrypted memory, transactional memory and scratchpad memory.

The National Science Foundation (NSF) CAPA: Collaborative Research: Lightweight Abstract Memory Feature grant, and the Office of Navy Research (ONR) grant, will support the researchers' project, "Semantics-Directed Binary Reverse Engineering and Transformation Validation."

Tan, who works in the School of Electrical Engineering and Computer Science, said that the NSF grant is a collaborative grant with Lehigh University and Arizona State University. The $2 million grant is jointly supported by the NSF and Intel, for three years. Tan and his team will receive $500,000 for their work.

“In terms of importance, the CAPA project allows my group to explore the design of a new language interface for programming modern memory features such as encrypted memory, recently included in Intel CPUs,” Tan said.

The three-year, $500,000 grant from the ONR will support Tan’s research in binary-level reverse engineering.

“Before we are able to perform analysis and transformation on an executable program, we must reverse engineer it to get its basic information, including its instructions, its control-flow graph, and basic dataflow information. Previous reverse-engineering techniques are often ad hoc and do not have a formal basis,” said Tan. “There is also no evaluation about what would be the best reverse-engineering algorithms in terms of precision and performance. We plan to construct a reverse-engineering tool that makes it easy for principled exploration of the design space of reverse-engineering algorithms.”

Tan received his bachelor’s of engineering degree in computer science from Tsinghua University in China and his doctorate in computer science from Princeton University. He is the recipient of an NSF Early Career Award.