Static analyzers allow programmers to bound and predict the behavior of software without ever running it.
Once used exclusively for program optimization, they are rapidly rising in prominence for areas like software security and automatic parallelization.
We'll take a tour of the landscape of static analysis through the lens of abstract interpretation.
With modern abstract interpretation, it is possible to systematically transform a (purely functional) interpreter for a language into a (purely functional) static analyzer for that language.
About Matt Might
Dr. Might is an Associate Professor in the School of Computing at the University of Utah, where he leads the U Combinator software systems research lab.
He has received research funding from the Department of Defense (DARPA), the National Science Foundation and the National Nuclear Security Administration to investigate automated security analysis, advanced performance optimization, next-generation programming languages and safety verification for medical robotics. His research extensively involves functional programming.
He has received a CAREER Award from the National Science Foundation, and in 2014, he was appointed one of five Presidential Scholars at the University of Utah. He received his Ph.D. in Computer Science from Georgia Tech in 2007. He regularly blogs at blog.might.net and tweets from @mattmight.
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