495 citations · 2.3k across the 36 of their papers we have counts for
9 papers · 1 filter
How Often Do Single-Statement Bugs Occur? The ManySStuBs4J Dataset
Rafael-Michael Karampatsis, Charles Sutton
Program repair is an important but difficult software engineering problem. One way to achieve acceptable performance is to focus on classes of simple bugs, such as bugs with single…
Maybe Deep Neural Networks are the Best Choice for Modeling Source Code
Rafael-Michael Karampatsis, Charles Sutton
Statistical language modeling techniques have successfully been applied to source code, yielding a variety of new software development tools, such as tools for code suggestion and…
Deep Learning to Detect Redundant Method Comments
Annie Louis, Santanu Kumar Dash, Earl T. Barr +1
Comments in software are critical for maintenance and reuse. But apart from prescriptive advice, there is little practical support or quantitative understanding of what makes a com…
A Survey of Machine Learning for Big Code and Naturalness
Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu +1
Research at the intersection of machine learning, programming languages, and software engineering has recently taken important steps in proposing learnable probabilistic models of…
Tailored Mutants Fit Bugs Better
Miltiadis Allamanis, Earl T. Barr, René Just +1
Mutation analysis measures test suite adequacy, the degree to which a test suite detects seeded faults: one test suite is better than another if it detects more mutants. Mutation a…
Parameter-Free Probabilistic API Mining across GitHub
Jaroslav Fowkes, Charles Sutton
Existing API mining algorithms can be difficult to use as they require expensive parameter tuning and the returned set of API calls can be large, highly redundant and difficult to…