Mathematical Analysis of Programs

  • Sriram Sankaranarayanan | Stanford University

Numerical programs are imperative programs over integer and real quantities. Such programs are ubiquitous. Common examples include scientific and systems programs, models of control systems such as timed and hybrid automata, and models of biological systems such as biochemical reaction mechanisms and gene regulatory networks. Static analyses of these programs automatically infer properties about the systems’ runtime behaviours, for example, the reachability of a target set of states, deadlock freedom, and bounds on variables.

In this talk, I demonstrate powerful analyses for both linear and nonlinear numerical programs using computational tools from algebra and geometry.

I first consider analyses for linear systems. Traditional polyhedra-based analyses do not scale due to the high complexity of polyhedral operations. I present a scalable polynomial time analysis that works by posing many linear programming queries, which can be solved by algorithms such as Simplex. The resulting analysis is precise and scales well on benchmark examples.

Next, I present an analysis for nonlinear systems. Using computational tools from algebraic geometry such as Groebner bases, the method infers invariants for many classes of nonlinear systems, including hybrid systems. I demonstrate the technique and its applications on a few examples.

Speaker Details

Sriram Sankaranarayanan grew up in Calcutta, India. He received a Bachelor of Technology degree in Computer Science from the Indian Institute of Technology (IIT) Kharagpur in 2000. Since then, he has been a PhD candidate in computer science at Stanford University working with Professor Zohar Manna. He received a M.S. in Computer Science in 2002. His research interests include program analysis, verfication, formal systems, and symbolic logic. He is a recipient of the president’s gold medal from IIT Kharagpur for the class of 2000, and the Siebel Scholarship for the academic year 2004-2005.

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