activity
20112022
most citedAdversarial Robustness of Deep Code Comment Generation

49 citations · 196 across the 14 of their papers we have counts for

collaborators

14 papers

cs.SE2022★ 1 cited

DRIVE: Dockerfile Rule Mining and Violation Detection

Yu Zhou, Weilin Zhan, Zi Li +3

A Dockerfile defines a set of instructions to build Docker images, which can then be instantiated to support containerized applications. Recent studies have revealed a considerable…

cs.SE2022

Towards Top-Down Automated Development in Limited Scopes: A Neuro-Symbolic Framework from Expressibles to Executables

Jian Gu, Harald C. Gall

Deep code generation is a topic of deep learning for software engineering (DL4SE), which adopts neural models to generate code for the intended functions. Since end-to-end neural m…

cs.SE2022

Continuous Deep Learning: A Workflow to Bring Models into Production

Janosch Baltensperger, Pasquale Salza, Harald C. Gall

Researchers have been highly active to investigate the classical machine learning workflow and integrate best practices from the software engineering lifecycle. However, deep learn…

cs.SE2022★ 1 cited

Synthetic End-User Testing: Modeling Realistic Agents Based on Behavioral Examples

Pasquale Salza, Marco Edoardo Palma, Harald C. Gall

For software interacting directly with real-world end-users, it is common practice to script scenario tests validating the system's compliance with a number of its features. Howeve…

cs.SE2022★ 4 cited

On-the-Fly Syntax Highlighting using Neural Networks

Marco Edoardo Palma, Pasquale Salza, Harald C. Gall

With the presence of online collaborative tools for software developers, source code is shared and consulted frequently, from code viewers to merge requests and code snippets. Typi…

cs.SE2022★ 1 cited

Toward Granular Automatic Unit Test Case Generation

Fabiano Pecorelli, Giovanni Grano, Fabio Palomba +2

Unit testing verifies the presence of faults in individual software components. Previous research has been targeting the automatic generation of unit tests through the adoption of…

cs.SE2022★ 2 cited

Assemble Foundation Models for Automatic Code Summarization

Jian Gu, Pasquale Salza, Harald C. Gall

Automatic code summarization is beneficial to daily software development since it could help reduce the requirement of manual writing. Currently, artificial intelligence is undergo…

cs.SE2021★ 39 cited

On the Effectiveness of Transfer Learning for Code Search

Pasquale Salza, Christoph Schwizer, Jian Gu +1

The Transformer architecture and transfer learning have marked a quantum leap in natural language processing, improving the state of the art across a range of text-based tasks. Thi…

cs.SE2021★ 49 cited

Adversarial Robustness of Deep Code Comment Generation

Yu Zhou, Xiaoqing Zhang, Juanjuan Shen +3

Deep neural networks (DNNs) have shown remarkable performance in a variety of domains such as computer vision, speech recognition, or natural language processing. Recently they als…

cs.SE2020★ 44 cited

Boosting API Recommendation with Implicit Feedback

Yu Zhou, Xinying Yang, Taolue Chen +3

Developers often need to use appropriate APIs to program efficiently, but it is usually a difficult task to identify the exact one they need from a vast of candidates. To ease the…

cs.SE2019★ 42 cited

User Review-Based Change File Localization for Mobile Applications

Yu Zhou, Yanqi Su, Taolue Chen +3

In the current mobile app development, novel and emerging DevOps practices (e.g., Continuous Delivery, Integration, and user feedback analysis) and tools are becoming more widespre…

cs.SE2014★ 1 cited

The Making of Cloud Applications An Empirical Study on Software Development for the Cloud

Jürgen Cito, Philipp Leitner, Thomas Fritz +1

Cloud computing is gaining more and more traction as a deployment and provisioning model for software. While a large body of research already covers how to optimally operate a clou…

cs.SE2014★ 12 cited

Cloud WorkBench - Infrastructure-as-Code Based Cloud Benchmarking

Joel Scheuner, Philipp Leitner, Jurgen Cito +1

To optimally deploy their applications, users of Infrastructure-as-a-Service clouds are required to evaluate the costs and performance of different combinations of cloud configurat…

cs.PL2011

A Study of Language Usage Evolution in Open Source Software

Siim Karus, Harald Gall

The use of programming languages such as Java and C in Open Source Software (OSS) has been well studied. However, many other popular languages such as XSL or XML have received mino…