Merlin: specification inference for explicit information flow problems
Proceedings of the 2009 ACM SIGPLAN conference on Programming language design and implementation
Effective Bayesian inference for stochastic programs
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Tuffy: scaling up statistical inference in Markov logic networks using an RDBMS
Proceedings of the VLDB Endowment
Probabilistic, modular and scalable inference of typestate specifications
Proceedings of the 32nd ACM SIGPLAN conference on Programming language design and implementation
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We give an account of our experiences working at the intersection of two fields: program analysis and machine learning. In particular, we show that machine learning can be used to infer annotations for program analysis tools, and that program analysis techniques can be used to improve the efficiency of machine learning tools.