Feedback-driven semi-supervised synthesis of program transformations

While editing code, it is common for developers to make multiple related repeated edits that are all instances of a more general program transformation. Since this process can be tedious and error-prone, we study the problem of automatically learning program transformations from past edits, which ca...

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Veröffentlicht in:	Proceedings of ACM on programming languages Jg. 4; H. OOPSLA; S. 1 - 30
Hauptverfasser:	Gao, Xiang, Barke, Shraddha, Radhakrishna, Arjun, Soares, Gustavo, Gulwani, Sumit, Leung, Alan, Nagappan, Nachiappan, Tiwari, Ashish
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY, USA ACM 13.11.2020
Schlagworte:	Artificial intelligence Automatic programming Computing methodologies Development frameworks and environments Integrated and visual development environments Software and its engineering Software creation and management Software development techniques Software maintenance tools Software notations and tools Programming by Example Program synthesis Refactoring Program transformation
ISSN:	2475-1421, 2475-1421
Online-Zugang:	Volltext
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