Mining and Understanding Software Enclaves (MUSE)

Presented as part of the 2014 HCSS conference.

Abstract:

The Mining and Understanding Software Enclaves (MUSE) program at DARPA seeks to overcome the tremendous challenge of ensuring software correctness at scale.  It proposes to do so through the creation of a community infrastructure that incorporates a continuously operational specification-mining engine applied to a large corpus of open-source software.  The engine will leverage deep program analyses and foundational ideas underlying big data analytics to populate and refine a database containing inferences about the behavior and properties of programs inhabiting the corpus.  

The overarching goal of the program is to effect a paradigm shift in the way software is conceived and maintained.  This shift is realized by replacing the existing costly and laborious test/debug/validate cycle with ‘always on’ program analysis, mining, inspection and discovery over the constantly evolving corpus.  Among other outcomes, we envision the creation of scalable automated mechanisms that can identify and repair program errors, as well as tools to efficiently synthesize custom programs from existing components based on a description of desired properties. 

Presenter Bio:

Dr. Suresh Jagannathan joined DARPA in September 2013. His research interests include programming languages, compilers, program verification, and concurrent and distributed systems.

Prior to joining DARPA, Dr. Jagannathan was a professor of computer science at Purdue University. He has also served as visiting faculty at Cambridge University, where he spent a sabbatical year in 2010; and as a senior research scientist at the NEC Research Institute in Princeton, N.J.

Dr. Jagannathan has published more than 125 peer-reviewed conference and journal publications and has co-authored one textbook. He holds three patents. He serves on numerous program and steering committees, and is on the editorial boards of several journals.

Dr. Jagannathan holds Doctor of Philosophy and Master of Science degrees in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. He earned a Bachelor of Science degree in Computer Science from the State University of New York, Stony Brook.