9 citations · 10 across the 3 of their papers we have counts for
5 papers
INSPECT: Intrinsic and Systematic Probing Evaluation for Code Transformers
Anjan Karmakar, Romain Robbes
Pre-trained models of source code have recently been successfully applied to a wide variety of Software Engineering tasks; they have also seen some practical adoption in practice,…
JEMMA: An Extensible Java Dataset for ML4Code Applications
Anjan Karmakar, Miltiadis Allamanis, Romain Robbes
Machine Learning for Source Code (ML4Code) is an active research field in which extensive experimentation is needed to discover how to best use source code's richly structured info…
Codex Hacks HackerRank: Memorization Issues and a Framework for Code Synthesis Evaluation
Anjan Karmakar, Julian Aron Prenner, Marco D'Ambros +1
The Codex model has demonstrated extraordinary competence in synthesizing code from natural language problem descriptions. However, in order to reveal unknown failure modes and hid…
What do pre-trained code models know about code?
Anjan Karmakar, Romain Robbes
Pre-trained models of code built on the transformer architecture have performed well on software engineering (SE) tasks such as predictive code generation, code summarization, amon…
Mining Software Repositories with a Collaborative Heuristic Repository
Hlib Babii, Julian Aron Prenner, Laurin Stricker +3
Many software engineering studies or tasks rely on categorizing software engineering artifacts. In practice, this is done either by defining simple but often imprecise heuristics,…