Reading List
Below is an abbreviated listed of papers (and some videos) I recommend students who are interested in working with me read (or watch). Most of these works are specific to machine programming (MP), but not all. To make ordering simple, I've ordered them by year and alphabetically. This ordering doesn't denote the paper's relative importance to me. I've highlighted the ones I think are most important for MP. Although everything on the below list I think is generally important.
This section is under major construction. Please pardon the incompleteness -- work in progress. :)
2019
"Aroma: code recommendation via structural code search" OOPSLA '19 Distinguished Paper
"From System 1 Deep Learning to System 2 Deep Learning" NeurIPS '19 keynote address
"Learning Fitness Functions for Genetic Algorithms" arxiv '19
"Learning to Optimize Halide with Tree Search and Random Programs" SIGGRAPH '19
"Neo: A Learned Query Optimizer" VLDB '19
"A Zero-Positive Learning Approach for Diagnosing Software Performance Regressions" NeurIPS '19
2018
"The Case for Learned Index Structures" SIGMOD '18
"Precision and Recall for Time Series" NeurIPS '18, spotlight
"The Three Pillars of Machine Programming" MAPL '18Â
2017
"DeepCoder: Learning to Write Programs" ICLR '17
"Making Neural Programming Architectures Generalize via Recursion" ICLR '17
2016
"Automatically Scheduling Halide Image Processing Pipelines" SIGGRAPH '18