Write a Blog >>
ICPC 2020
Mon 13 - Wed 15 July 2020
co-located with ICSE 2020
Tue 14 Jul 2020 08:30 - 08:42 at ICPC - Session 6: Artifacts Chair(s): Hironori Washizaki

Code completion, one of the most useful features in the Integrated Development Environments (IDEs), can accelerate software development by suggesting the libraries, APIs, and method names in real-time. Recent studies have shown that statistical language models can improve the performance of code completion tools through learning from large-scale software repositories. However, these models suffer from three major drawbacks: a) The hierarchical structural information of the programs is not fully utilized in the program’s representation; b) In programs, the semantic relationships can be very long. Existing recurrent neural networks based language models are not sufficient to model the long-term dependency. c) Existing approaches perform a specific task in one model, which leads to the underuse of the information from related tasks. To address these challenges, in this paper, we propose a selfattentional neural architecture for code completion with multi-task learning. To utilize the hierarchical structural information of the programs, we present a novel method that considers the path from the predicting node to the root node. To capture the long-term dependency in the input programs, we adopt a self-attentional architecture based network as the base language model. To enable the knowledge sharing between related tasks, we creatively propose a Multi-Task Learning (MTL) framework to learn two related tasks in code completion jointly. Experiments on three real-world datasets demonstrate the effectiveness of our model when compared with state-of-the-art methods.

Tue 14 Jul
Times are displayed in time zone: (UTC) Coordinated Universal Time change

08:30 - 09:30: Session 6: ArtifactsResearch / ERA at ICPC
Chair(s): Hironori WashizakiWaseda University
08:30 - 08:42
Paper
A Self-Attentional Neural Architecture for Code Completion with Multi-Task Learning
Research
Fang LiuPeking University, Ge LiPeking University, Bolin WeiPeking University, Xin XiaMonash University, Zhiyi FuPeking University, Zhi JinPeking University
Pre-print Media Attached
08:42 - 08:54
Paper
Knowledge Transfer in Modern Code Review
Research
Maria CauloUniversity of Basilicata, Bin LinUniversità della Svizzera italiana (USI), Gabriele BavotaUniversità della Svizzera italiana, Giuseppe ScannielloUniversity of Basilicata, Michele LanzaUniversita della Svizzera italiana (USI)
Pre-print Media Attached
08:54 - 09:06
Paper
How are Deep Learning Models Similar? An Empirical Study on Clone Analysis of Deep Learning Software
Research
Xiongfei WuUniversity of Science and Technology of China, Liangyu QinUniversity of Science and Technology of China, Bing YuKyushu University, Xiaofei XieNanyang Technological University, Lei MaKyushu University, Yinxing Xue, Yang LiuNanyang Technological University, Singapore, Jianjun ZhaoKyushu University
Media Attached
09:06 - 09:18
Paper
Unified Configuration Setting Access in Configuration Management Systems
Research
Markus RaabVienna University of Technology, Austria, Bernhard DennerThales, Stefan HanenbergUniversity of Duisburg-Essen, Jürgen CitoMIT
Media Attached
09:18 - 09:30
Paper
Inheritance software metrics on smart contracts
ERA
Ashish Rajendra SaiUniversity of Limerick, Conor HolmesUniversity of Limerick, Jim BuckleyLero - The Irish Software Research Centre and University of Limerick, Andrew LeGearHorizon Globex
Media Attached