Alex Aiken – Communications of the ACM

Research and Advances Feb 1 2016

By encoding constraints of transformation correctness as terms in a cost function, and using a Markov Chain Monte Carlo sampler to explore the space of all possible code sequences, we are able to generate aggressively optimized versions of a given target code sequence.

Computing Applications

Stochastic Program Optimization, illustration

Author Archives

Research and Advances Dec 1 2012

An Introduction to Data Representation Synthesis

We consider the problem of specifying combinations of data structures with complex sharing in a manner that is declarative and results in provably correct code.

Computing Applications

Research and Advances Aug 1 2010

Reasoning About the Unknown in Static Analysis

Static program analysis techniques cannot know certain values, such as the value of user input or network state, at analysis time. While such unknown values need to be treated as nondeterministic choices made by the program's execution environment, it is still possible to glean very useful information about how such statically unknown values may or must influence computation.

Computing Applications

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