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ICPC 2020
Mon 13 - Wed 15 July 2020
co-located with ICSE 2020
Tue 14 Jul 2020 01:30 - 01:45 at ICPC - Session 4: Summalization Chair(s): Venera Arnaoudova

Automatic source code summarization is the task of generating natural language descriptions for source code. Automatic code summarization is a rapidly expanding research area, especially as the community has taken greater advantage of advances in neural network and AI technologies. In general, source code summarization techniques use the source code as input and outputs a natural language description. Yet a strong consensus is developing that using structural information as input leads to improved performance. The first approaches to use structural information flattened the AST into a sequence. Recently, more complex approaches based on random AST paths or graph neural networks have improved on the models using flattened ASTs. However, the literature still does not describe the using a graph neural network together with source code sequence as separate inputs to a model. Therefore, in this paper, we present an approach that uses a graph-based neural architecture that better matches the default structure of the AST to generate these summaries. We evaluate our technique using a data set of 2.1 million Java method-comment pairs and show improvement over four baseline techniques, two from the software engineering literature, and two from machine learning literature.

Tue 14 Jul

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01:30 - 02:30
Session 4: SummalizationResearch / ERA at ICPC
Chair(s): Venera Arnaoudova Washington State University
01:30
15m
Paper
Improved Code Summarization via a Graph Neural Network
Research
Alexander LeClair University Of Notre Dame, Sakib Haque University of Notre Dame, Lingfei Wu IBM Research, Collin McMillan University of Notre Dame
Pre-print Media Attached
01:45
15m
Paper
BugSum: Deep Context Understanding for Bug Report Summarization
Research
Haoran Liu National University of Defense Technology, Yue Yu College of Computer, National University of Defense Technology, Changsha 410073, China, Shanshan Li National University of Defense Technology, Yong Guo National University of Defense Technology, Deze Wang National University of Defense Technology, Xiaoguang Mao National University of Defense Technology
Media Attached
02:00
15m
Paper
A Human Study of Comprehension and Code Summarization
Research
Sean Stapleton University of Michigan, Yashmeet Gambhir University of Michigan, Alexander LeClair University Of Notre Dame, Zachary Eberhart , Westley Weimer University of Michigan, USA, Kevin Leach University of Michigan, Yu Huang University of Michigan
Pre-print Media Attached
02:15
15m
Paper
Linguistic Documentation of Software History
ERA
Miroslav Tushev Louisiana State University, Nash Mahmoud Louisiana State University
Media Attached