Storm: program reduction for testing and debugging probabilistic programming systems
Saikat Dutta, Wenxian Zhang, Zixin Huang, Saša Misailovíc · 2019
Probabilistic programming languages offer an intuitive way to model uncertainty by representing complex probability models as simple probabilistic programs. Probabilistic programming systems (PP systems) hide the complexity of inference algorithms away from the program developer. Unfortunately, if a failure occurs during the run of a PP system, a developer typically has very little support in finding the part of the probabilistic program that causes the failure in the system.