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ICPC 2020
Mon 13 - Wed 15 July 2020
co-located with ICSE 2020
Tue 14 Jul 2020 07:15 - 07:30 at ICPC - Session 5: For Researchers Chair(s): Bin Lin

Searching and reusing existing code from a large-scale codebase, e.g, GitHub, can help developers complete a programming task efficiently. Recently, Gu et al. proposed a deep learning-based model (i.e., DeepCS), which significantly outperformed prior models. The DeepCS embedded codebase and natural language queries into vectors by two LSTM (long and short-term memory) models separately, and returned developers the code with higher similarity to a code search query. However, such embedding method learned two isolated representations for code and query but ignored their internal semantic correlations. As a result, the learned isolated representations of code and query may limit the effectiveness of code search. To address the aforementioned issue, we propose a co-attentive representation learning model, i.e., Co-Attentive Representation Learning Code Search-CNN (CARLCS-CNN). CARLCS-CNN learns interdependent representations for the embedded code and query with a co-attention mechanism. Generally, such mechanism learns a correlation matrix between embedded code and query, and coattends their semantic relationship via row/column-wise max-pooling. In this way, the semantic correlation between code and query can directly affect their individual representations. We evaluate the effectiveness of CARLCS-CNN on Gu et al.’s dataset with 10k queries. Experimental results show that the proposed CARLCS-CNN model significantly outperforms DeepCS by 26.72% in terms of MRR (mean reciprocal rank). Additionally, CARLCS-CNN is five times faster than DeepCS in model training and four times in testing.

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

07:00 - 08:00: Session 5: For ResearchersResearch / ERA / Tool Demonstration at ICPC
Chair(s): Bin LinUniversità della Svizzera italiana (USI)
07:00 - 07:15
Paper
Research
Thazin Win Win AungUniversity of Technology Sydney, Yulei SuiUniversity of Technology Sydney, Australia, Huan HuoUniversity of Technology Sydney
Media Attached
07:15 - 07:30
Paper
Research
Jianhang ShuaiSchool of Big Data & Software Engineering, Chongqing University, Ling XuSchool of Big Data & Software Engineering, Chongqing University, Chao LiuZhejiang University, Meng YanSchool of Big Data & Software Engineering, Chongqing University, Xin XiaMonash University, Yan LeiSchool of Big Data & Software Engineering, Chongqing University
Media Attached
07:30 - 07:45
Paper
Tool Demonstration
Valentina LenarduzziLUT University, Fabio PalombaUniversity of Salerno, Davide TaibiTampere University, Damian Andrew TamburriJheronimus Academy of Data Science
Media Attached
07:45 - 08:00
Paper
ERA
Akira Fujimoto Osaka University, Yoshiki HigoOsaka University, Junnosuke Matsumoto, Shinji KusumotoOsaka University
Media Attached