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Abstract: A good model of a biological cell exposes secrets of the cell's signaling
mechanisms, explaining diseases and facilitating drug discovery. Modeling
cells is fundamentally a programming problem --- it's programming because
the model is a concurrent program that simulates the cell, and it's a
problem because it is hard to write a program that reproduces all
experimental observations of the cell faithfully.
In this talk, I will introduce solver-aided programming languages and show how they ease modeling biology as well as make programming accessible to non-programmers. Solver-aided languages come with constructs that delegate part of the programming problem to a constraint solver, which can be guided to synthesize parts of the program, localize its bugs, or act as a clairvoyant oracle. I will describe our work on synthesis of stem cell models in c. elegans and then show how our framework called Rosette can rapidly implement a solver aided language in several domains, from programming by demonstration to spatial parallel programming.
Speaker Bio: Ras is a professor of computer science at UC Berkeley. He works on various flavors of program synthesis, from programming by demonstration, to sketching, design of programmer-accessible oracles, and compilers for declarative languages. |
![]() | Don is a professor of computer science at the University of Texas at Austin, working on product-line architectures and automated software development to improved programmer productivity, product quality, reduced maintenance cost, and enhanced application performance. The keynote is titled Dark Knowledge and Graph Grammars in Automated Software Design. |