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Colloquium
Computer Science

What Program Analysis Can and Cannot Do for You

by David Van Horn
CRA Postdoctoral Fellow
from Northeastern University
when Thursday, March 10, 2011
Time: 4:00 PM to 5:00 PM
where 102 Keck Hall 
Rice University
6100 Main St
Houston, Texas, USA
abstract Work on software engineering, compiler optimizations, program parallelization, system verification, and security assurance depends on program analysis, a ubiquitous and central theme of programming language research. At the same time, the production of modern software systems employs expressive, higher-order programming languages, e.g., Java, JavaScript, Python, Ruby, etc., implying a growing need for fast, precise, and scalable higher-order program analyses.

For thirty years, the research community has expended a tremendous amount of effort designing effective, scalable analysis for higher-order programming languages. These past approaches, however, call for whole-program analyses, demand polynomial (or worse!) resources, and require complex constructions and correctness arguments. In this talk I will describe how these limitations can be overcome and provide new insights into the potential of higher-order program analysis. These ideas enable a new approach to analysis that meets the scalability challenge of modern systems. I will sketch how to leverage these new ideas in order to create a straightforward derivation process, thereby lowering verification costs, accommodating sophisticated language features and program properties, and reasoning about modular, i.e., incomplete, programs. In the long run, my foundational results should open several new directions for program analysis and its applications, and I will conclude my talk with a sketch of these possibilities.

speaker bio David Van Horn's research interests include all aspects of reliable software construction. He obtained his PhD from Brandeis in 2009 and has been a post-doctoral researcher at the Northeastern University Programming Research Lab for the last two years, supported by a CRA Computing Innovation Fellowship. During this time, he has investigated the computational complexity of important program analysis problems, resolved misunderstandings between the object-oriented and functional language communities, and used these insights to develop better approaches to analysis design.






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