ICSE 2021 (series) / Journal-First Papers / Deep Learning Based Program Generation from Requirements Text: Are We There Yet?
Deep Learning Based Program Generation from Requirements Text: Are We There Yet?Journal-First
Thu 27 May 2021 10:20 - 10:40 at Blended Sessions Room 2 - 3.1.2. Deep Neural Networks: Supporting SE Tasks #2 Chair(s): Sira Vegas
Thu 27 May 2021 22:20 - 22:40 at Blended Sessions Room 2 - 3.1.2. Deep Neural Networks: Supporting SE Tasks #2
Thu 27 May 2021 22:20 - 22:40 at Blended Sessions Room 2 - 3.1.2. Deep Neural Networks: Supporting SE Tasks #2
Thu 27 MayDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
Thu 27 May
Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
10:00 - 11:00 | 3.1.2. Deep Neural Networks: Supporting SE Tasks #2SEIP - Software Engineering in Practice / Journal-First Papers / Technical Track at Blended Sessions Room 2 +12h Chair(s): Sira Vegas Universidad Politecnica de Madrid | ||
10:00 20mPaper | NNStreamer: Efficient and Agile Development of On-Device AI SystemsSEIP SEIP - Software Engineering in Practice MyungJoo Ham Samsung Electronics, Jijoong Moon Samsung Electronics, Geunsik Lim Samsung Research, Samsung Electronics, Jaeyun Jung Samsung Electronics, Hyoungjoo Ahn Samsung Electronics, Wook Song Samsung Electronics, Sangjung Woo Samsung Electronics, Parichay Kapoor Samsung Electronics, Dongju Chae Samsung Electronics, Gichan Jang Samsung Electronics, Yongjoo Ahn Samsung Electronics, Jihoon Lee Samsung Electronics Pre-print Media Attached | ||
10:20 20mPaper | Deep Learning Based Program Generation from Requirements Text: Are We There Yet?Journal-First Journal-First Papers Hui Liu Beijing Institute of Technology, Mingzhu Shen Beijing Institute of Technology, Jiaqi Zhu Beijing Institute of Technology, Nan Niu University of Cincinnati, Ge Li Peking University, Lu Zhang Peking University, China Link to publication DOI Pre-print Media Attached | ||
10:40 20mPaper | Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related TasksTechnical Track Technical Track Antonio Mastropaolo Università della Svizzera italiana, Simone Scalabrino University of Molise, Nathan Cooper William & Mary, David Nader Palacio William and Mary, Denys Poshyvanyk College of William & Mary, Rocco Oliveto University of Molise, Gabriele Bavota Software Institute, USI Università della Svizzera italiana Pre-print Media Attached |
22:00 - 23:00 | 3.1.2. Deep Neural Networks: Supporting SE Tasks #2Technical Track / SEIP - Software Engineering in Practice / Journal-First Papers at Blended Sessions Room 2 | ||
22:00 20mPaper | NNStreamer: Efficient and Agile Development of On-Device AI SystemsSEIP SEIP - Software Engineering in Practice MyungJoo Ham Samsung Electronics, Jijoong Moon Samsung Electronics, Geunsik Lim Samsung Research, Samsung Electronics, Jaeyun Jung Samsung Electronics, Hyoungjoo Ahn Samsung Electronics, Wook Song Samsung Electronics, Sangjung Woo Samsung Electronics, Parichay Kapoor Samsung Electronics, Dongju Chae Samsung Electronics, Gichan Jang Samsung Electronics, Yongjoo Ahn Samsung Electronics, Jihoon Lee Samsung Electronics Pre-print Media Attached | ||
22:20 20mPaper | Deep Learning Based Program Generation from Requirements Text: Are We There Yet?Journal-First Journal-First Papers Hui Liu Beijing Institute of Technology, Mingzhu Shen Beijing Institute of Technology, Jiaqi Zhu Beijing Institute of Technology, Nan Niu University of Cincinnati, Ge Li Peking University, Lu Zhang Peking University, China Link to publication DOI Pre-print Media Attached | ||
22:40 20mPaper | Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related TasksTechnical Track Technical Track Antonio Mastropaolo Università della Svizzera italiana, Simone Scalabrino University of Molise, Nathan Cooper William & Mary, David Nader Palacio William and Mary, Denys Poshyvanyk College of William & Mary, Rocco Oliveto University of Molise, Gabriele Bavota Software Institute, USI Università della Svizzera italiana Pre-print Media Attached |