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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Vydáno v:	Proceedings of ACM on programming languages Ročník 4; číslo OOPSLA; s. 1 - 30
Hlavní autoři:	Gao, Xiang, Barke, Shraddha, Radhakrishna, Arjun, Soares, Gustavo, Gulwani, Sumit, Leung, Alan, Nagappan, Nachiappan, Tiwari, Ashish
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York, NY, USA ACM 13.11.2020
Témata:	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
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