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Guang Yang

Learning && Loving

About Me

I am a PhD student in the College of Computer Science and Technology of Nanjing University of Aeronautics and Astronautics.

My research mainly focuses on software engineering:

  • Intelligent Software Engineering
  • Automatic Generation of Source Code
  • Automatic Generation of Code Comments
  • Mining Software Repositories

My advisor is Professor Yu Zhou (周宇) and Professor Xiang Chen (陈翔).

Education

2022.09- present

Nanjing University of Aeronautics and Astronautics, major in Software Engineering

2019.09- 2022.06

Nantong University, major in Computer Technology

2015.9 - 2019.6

Nantong University, major in Software Engineering

Visiting Scholar

  • Singapore Management University, SOAR（SOftware Analytics Research）group, Singapore, 2024-2025. Visiting Professor David Lo.（新加坡管理大学计算与信息系统学院资助）

Selected Publications (first/co-first author)

CCF A or SCI Q1

  1. [TOSEM 2023] How Important are Good Method Names in Neural Code Generation? A Model Robustness Perspective.
  2. [KBS 2022] CCGIR: Information Retrieval-based Code Comment Generation Method for Smart Contracts.

CCF B or SCI Q2

  1. [EMSE 2023] A Syntax-Guided Multi-Task Learning Approach for Turducken-Style Code Generation.
  2. [JSS 2023] ExploitGen: Template-Augmented Exploit Code Generation Based on CodeBERT.
  3. [SANER 2022] DualSC: Automatic Generation and Summarization of ShellCode via Transformer and Dual Learning.
  4. [SANER 2022] SOTitle: A Transformer-based Post Title Generation Approach for Stack Overflow.
  5. [ICSME 2022] BASHEXPLAINER: Retrieval-Augmented Bash Code Comment Generation based on Fine-tuned CodeBERT.

CCF C or SCI Q3

  1. [Internetware 2022] EL-CodeBert: Better Exploiting CodeBert to Support Source Code-Related Classification Tasks.
  2. [APSEC 2021] Fine-grained Pseudo-code Generation Method via Code Feature Extraction and Transformer.
  3. [SEKE 2021] DeepSCC: Source Code Classification Based on Fine-Tuned RoBERTa.

三大学报

  1. [计算机研究与发展 2024] CodeScore-R：用于评估代码合成功能准确性的自动化鲁棒指标.
  2. [软件学报 2021] 代码注释自动生成方法综述.

Reviewers

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