24 citations · 28 across the 2 of their papers we have counts for
7 papers
TypeWriter: Neural Type Prediction with Search-based Validation
Michael Pradel, Georgios Gousios, Jason Liu +1
Maintaining large code bases written in dynamically typed languages, such as JavaScript or Python, can be challenging due to the absence of type annotations: simple data compatibil…
Debugging Crashes using Continuous Contrast Set Mining
Rebecca Qian, Yang Yu, Wonhee Park +3
Facebook operates a family of services used by over two billion people daily on a huge variety of mobile devices. Many devices are configured to upload crash reports should the app…
Neural Code Search Evaluation Dataset
Hongyu Li, Seohyun Kim, Satish Chandra
There has been an increase of interest in code search using natural language. Assessing the performance of such code search models can be difficult without a readily available eval…
When Deep Learning Met Code Search
Jose Cambronero, Hongyu Li, Seohyun Kim +2
There have been multiple recent proposals on using deep neural networks for code search using natural language. Common across these proposals is the idea of co…
Getafix: Learning to Fix Bugs Automatically
Johannes Bader, Andrew Scott, Michael Pradel +1
Static analyzers help find bugs early by warning about recurring bug categories. While fixing these bugs still remains a mostly manual task in practice, we observe that fixes for a…
Aroma: Code Recommendation via Structural Code Search
Sifei Luan, Di Yang, Celeste Barnaby +2
Programmers often write code that has similarity to existing code written somewhere. A tool that could help programmers to search such similar code would be immensely useful. Such…