Refazer

Welcome to Refazer Project

REFAZER is a technique for automatically generating program transformations. REFAZER builds on the observation that code edits performed by developers can be used as input-output examples for learning program transformations. Example edits may share the same structure but involve different variables and subexpressions, which must be generalized in a transformation at the right level of abstraction. To learn transformations, REFAZER leverages state-of-the-art programming-by-example methodology using the following key components: (a) a novel domain-specific language (DSL) for describing program transformations, (b) domain-specific deductive algorithms for efficiently synthesizing transformations in the DSL, and (c) functions for ranking the synthesized transformations.

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Python Study

We are working to get IRB approval for making the data available.

Transformations

Systematic changes git diff: here.

Characteristics

Systematic changes characterization: here.

Source Code

Refazer source code in Python: here.
Refazer source code in C#: here.