3 citations · 7 across the 5 of their papers we have counts for
5 papers
CASCADE: Detecting Inconsistencies between Code and Documentation with Automatic Test Generation
Tobias Kiecker, Jan Arne Sparka, Martin Reuter +2
Maintaining consistency between code and documentation is a crucial yet frequently overlooked aspect of software development. Even minor mismatches can confuse API users, introduce…
Bayesian Quantification with Black-Box Estimators
Albert Ziegler, Paweł Czyż
Understanding how different classes are distributed in an unlabeled data set is an important challenge for the calibration of probabilistic classifiers and uncertainty quantificati…
Follow-up Attention: An Empirical Study of Developer and Neural Model Code Exploration
Matteo Paltenghi, Rahul Pandita, Austin Z. Henley +1
Recent neural models of code, such as OpenAI Codex and AlphaCode, have demonstrated remarkable proficiency at code generation due to the underlying attention mechanism. However, it…
Productivity Assessment of Neural Code Completion
Albert Ziegler, Eirini Kalliamvakou, Shawn Simister +5
Neural code synthesis has reached a point where snippet generation is accurate enough to be considered for integration into human software development workflows. Commercial product…
The standard coder: a machine learning approach to measuring the effort required to produce source code change
Ian Wright, Albert Ziegler
We apply machine learning to version control data to measure the quantity of effort required to produce source code changes. We construct a model of a `standard coder' trained from…