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Found 6 papers, 5 papers with code
Counterfactual Explanations for Models of Code
We integrate counterfactual explanation generation to models of source code in a real-world setting.
Neural Software Analysis
The resulting tools complement and outperform traditional program analyses, and are used in industrial practice.
Code Prediction by Feeding Trees to Transformers
We provide comprehensive experimental evaluation of our proposal, along with alternative design choices, on a standard Python dataset, as well as on a Python corpus internal to Facebook.
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Software Engineering
TypeWriter: Neural Type Prediction with Search-based Validation
Unfortunately, static type inference for dynamic languages is inherently limited, while probabilistic approaches suffer from imprecision.
Software Engineering
When Deep Learning Met Code Search
Our evaluation shows that: 1. adding supervision to an existing unsupervised technique can improve performance, though not necessarily by much; 2. simple networks for supervision can be more effective that more sophisticated sequence-based networks for code search; 3. while it is common to use docstrings to carry out supervision, there is a sizeable gap between the effectiveness of docstrings and a more query-appropriate supervision corpus.
Aroma: Code Recommendation via Structural Code Search
Such a tool could help programmers to extend partially written code snippets to completely implement necessary functionality, help to discover extensions to the partial code which are commonly done by other programmers, help to cross-check against similar code written by other programmers, or help to add extra code which would avoid common mistakes and errors.
Software Engineering
