activity
20202026
most citedAn Empirical Study on the Usage of Transformer Models for Code Completion

98 citations · 201 across the 13 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

cs.SE2021★ 98 cited

An Empirical Study on the Usage of Transformer Models for Code Completion

Matteo Ciniselli, Nathan Cooper, Luca Pascarella +5

Code completion aims at speeding up code writing by predicting the next code token(s) the developer is likely to write. Works in this field focused on improving the accuracy of the…

cs.CR2021

Mutation-based Evaluation of Cryptographic API Misuse Detectors

Amit Seal Ami, Scott Marsden, Kevin Moran +2

The correct use of cryptography is central to ensuring data security in modern software systems. Hence, several academic and commercial static analysis tools have been developed fo…

cs.SE2021

An Empirical Study on the Usage of BERT Models for Code Completion

Matteo Ciniselli, Nathan Cooper, Luca Pascarella +3

Code completion is one of the main features of modern Integrated Development Environments (IDEs). Its objective is to speed up code writing by predicting the next code token(s) the…

cs.SE2021

V2S: A Tool for Translating Video Recordings of Mobile App Usages into Replayable Scenarios

Madeleine Havranek, Carlos Bernal-Cárdenas, Nathan Cooper +3

Screen recordings are becoming increasingly important as rich software artifacts that inform mobile application development processes. However, the amount of manual effort required…

cs.SE2021★ 1 cited

Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks

Antonio Mastropaolo, Simone Scalabrino, Nathan Cooper +4

Deep learning (DL) techniques are gaining more and more attention in the software engineering community. They have been used to support several code-related tasks, such as automati…