The Three Pillars of Machine Programming
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Abstract (arXiv)
In this position paper, we describe our vision of the future of machine programming through a categorical examination of three pillars of research. Those pillars are: (i) intention, (ii) invention, and(iii) adaptation. Intention emphasizes advancements in the human-to-computer and computer-to-machine-learning interfaces. Invention emphasizes the creation or refinement of algorithms or core hardware and software building blocks through machine learning (ML). Adaptation emphasizes advances in the use of ML-based constructs to autonomously evolve software.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Mar 2018.
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Citing papers per year: 2021: 2; 2022: 4; 2023: 4; 2024: 0; 2025: 0; 2026: 2.
12 papers.
- 2022CrossBeam: Learning to Search in Bottom-Up Program Synthesiscited by 18
- 2021Toward Code Generation: A Survey and Lessons from Semantic Parsingcited by 8
- 2023PerfRL: A Small Language Model Framework for Efficient Code Optimizationcited by 8
- 2022Compositional Generalization and Decomposition in Neural Program Synthesiscited by 6
- 2023LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdascited by 6
- 2023MPI-rical: Data-Driven MPI Distributed Parallelism Assistance with Transformerscited by 5
- 2023Neural Machine Translation for Code Generationcited by 3
- 2022Synthesizing Programs with Continuous Optimizationcited by 2
- 2022Are Machine Programming Systems using Right Source-Code Measures to Select Code Repositories?cited by 1
- 2021Report of the Workshop on Program Synthesis for Scientific Computingcited by 0
- 2026ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translationcited by 0
- 2026Piece of CAKE: Adaptive Execution Engines via Microsecond-Scale Learningcited by 0
- 2026Piece of CAKE: Adaptive Execution Engines via Microsecond-Scale Learning4 Feb 2026
- 2026ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation7 Jan 2026
- 2023PerfRL: A Small Language Model Framework for Efficient Code Optimization9 Dec 2023
- 2023LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas3 Jun 2023
- 2023Neural Machine Translation for Code Generation22 May 2023
- 2023MPI-rical: Data-Driven MPI Distributed Parallelism Assistance with Transformers16 May 2023
- 2022Synthesizing Programs with Continuous Optimization2 Nov 2022
- 2022Are Machine Programming Systems using Right Source-Code Measures to Select Code Repositories?24 Sep 2022
- 2022Compositional Generalization and Decomposition in Neural Program Synthesis7 Apr 2022
- 2022CrossBeam: Learning to Search in Bottom-Up Program Synthesis20 Mar 2022
- 2021Toward Code Generation: A Survey and Lessons from Semantic Parsing26 Apr 2021
- 2021Report of the Workshop on Program Synthesis for Scientific Computing2 Feb 2021