# Report of the Workshop on Program Synthesis for Scientific Computing

arXiv: https://arxiv.org/abs/2102.01687 · HTML: https://mlsanity.com/paper/2102.01687/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 19 of its 108 references that are in the map.
- First posted on arXiv 2 Feb 2021.

## Builds on (most cited first, 19 of 19)

- [Unsupervised Translation of Programming Languages](https://mlsanity.com/paper/2006.03511/) (2020)
- [Neural Code Comprehension: A Learnable Representation of Code Semantics](https://mlsanity.com/paper/1806.07336/) (2018)
- [LambdaNet: Probabilistic Type Inference using Graph Neural Networks](https://mlsanity.com/paper/2005.02161/) (2020)
- [Parsl: Pervasive Parallel Programming in Python](https://mlsanity.com/paper/1905.02158/) (2019)
- [TypeWriter: Neural Type Prediction with Search-based Validation](https://mlsanity.com/paper/1912.03768/) (2019)
- [Aroma: Code Recommendation via Structural Code Search](https://mlsanity.com/paper/1812.01158/) (2018)
- [The Three Pillars of Machine Programming](https://mlsanity.com/paper/1803.07244/) (2018)
- [Hazelnut: A Bidirectionally Typed Structure Editor Calculus](https://mlsanity.com/paper/1607.04180/) (2016)
- [Live Functional Programming with Typed Holes](https://mlsanity.com/paper/1805.00155/) (2018)
- [Autotuning Search Space for Loop Transformations](https://mlsanity.com/paper/2010.06521/) (2020)
- [A Zero-Positive Learning Approach for Diagnosing Software Performance Regressions](https://mlsanity.com/paper/1709.07536/) (2017)
- [ControlFlag: A Self-Supervised Idiosyncratic Pattern Detection System for Software Control Structures](https://mlsanity.com/paper/2011.03616/) (2020)
- [Automatically Leveraging MapReduce Frameworks for Data-Intensive Applications](https://mlsanity.com/paper/1801.09802/) (2018)
- [Toward Semantic Foundations for Program Editors](https://mlsanity.com/paper/1703.08694/) (2017)
- [Characterizing the Roles of Contributors in Open-source Scientific Software Projects](https://mlsanity.com/paper/2003.10572/) (2020)
- [HPAT: High Performance Analytics with Scripting Ease-of-Use](https://mlsanity.com/paper/1611.04934/) (2016)
- [Report on the performance portability demonstrated for the relevant Weather & Climate Dwarfs](https://mlsanity.com/paper/1908.06094/) (2019)
- [Reasoning About Recursive Tree Traversals](https://mlsanity.com/paper/1910.09521/) (2019)
- [FPDetect: Efficient Reasoning About Stencil Programs Using Selective Direct Evaluation](https://mlsanity.com/paper/2004.04359/) (2020)

## Abstract (arXiv)

Program synthesis is an active research field in academia, national labs, and industry. Yet, work directly applicable to scientific computing, while having some impressive successes, has been limited. This report reviews the relevant areas of program synthesis work for scientific computing, discusses successes to date, and outlines opportunities for future work. This report is the result of the Workshop on Program Synthesis for Scientific Computing was held virtually on August 4-5 2020 (https://prog-synth-science.github.io/2020/).