Patent · US Active

Feedback-driven semi-supervised synthesis of program transformations

US11513773B2 · kind B2 · utility

2Cited by
4References
19Claims
0Family size

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Key dates

Filing dateSep 30, 2020
Grant dateNov 29, 2022
Priority date
Expiry dateJan 29, 2041

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06N20/00
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

A synthesis procedure learns program transformations for a text document, on-the-fly during an edit session, from examples of concrete edits made during the edit session and from an unsupervised set of additional inputs. The additional inputs are derived from explicit feedback from the user and inferred feedback from the user's behavior during the edit session. A reward score, based on anti-unification and provenance analysis, is used to classify the additional inputs as either a positive input or a negative input. Outputs are generated for the positive inputs that are consistent with the existing examples and then used to synthesize a new program transformation. The program transformations are then used to generate code edit suggestions during the edit session.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.