About Us
At the ByteDance Software Engineering Lab, our mission is to accelerate the convergence and complementary of software engineering and intelligent technologies, and to promote technological progress in every aspect of software development. To achieve this goal, we bring together the best researchers and development engineers from different fields and backgrounds to promote the resolution of the challenges of ByteDance and the entire software engineering community.
Where are we?
- Beijing / Shenzhen / Hangzhou, Mainland China 🇨🇳
- San Jose, United States 🇺🇸
- Singapore 🇸🇬
Contact us
Teams
Code Intelligence
- Hyperscale Code Graph building
- Leading code intelligent capabilities with AI techs.
- Leading static analysis capabilities
We are hiring:
Several positions on GPT/LLM research and development are available in China and Singapore.
AI Applications
- AI solutions for engineering productivity.
- AI for Codebase, CI/CD, and DevOps.
Industrial Research
We also provide research intern positions and are looking for well-motivated current master students and PhD candidates to join our research group. Our research interests include:
- SE for AI and AI for SE.
- Software engineering and testing,
- Programming languages, compilers, program analysis, repair and synthesis,
Should you have any questions about internship opportunities, feel free to contact Dr. Chao Peng (email provided above).
Collaborated Universities
We have established cooperative relationship with top universities over the world.
Publications
- Liang, Xiaoyun, Jiayi Qi, Yongqiang Gao, Chao Peng, Ping Yang (2023). “AG3: Automated Game GUI Text Glitch Detection based on Computer Vision”. In Proceedings of ESEC/FSE 2023 (Industry Track). ACM, to appear.
- Jiang, Zongze, Ming Wen, Yixin Yang, Chao Peng, Ping Yang, Hai Jin (2023). “Effective Concurrency Testing for Go via Directional Primitive-constrained Interleaving Exploration”. In Proceedings of ASE 2023. IEEE, to appear.
- Wang, Siwei, Xue Mao, Ziguang Gao, Yujun Gao, Qucheng Shen, and Chao Peng (2023). “NxtUnit: Automated Unit Test Generation for Go”. In Proceedings of EASE 2023 (Industry Track). 2023. [pdf]
- Sun, Jingling, Ting Su, Kai Liu, Chao Peng, Zhao Zhang, Geguang Pu, Tao Xie, and Zhendong Su (2022). “Characterizing and Finding SystemSetting-Related Defects in Android Apps”. IEEE Transactions on Software Engineering. 2023. [pdf]
- Lv, Zhengwei, Chao Peng, Zhao Zhang, Ting Su, Kai Liu, and Ping Yang (2022). “Fastbot2: Reusable Automated Model-based GUI Testing for Android Enhanced by Reinforcement Learning”. In Proceedings of ASE 2022 (Industry Track). ACM, 2022. [pdf] [tool: Android] [tool: iOS]
- Peng, Chao, Yujun Gao, and Ping Yang (2022). “Automated Server Testing: an Industrial Experience Report”. In Proceedings of ICSME 2022 (Industry Track). IEEE, 2022. [pdf]
- Peng, Chao, Zhao Zhang, Zhengwei Lv, and Ping Yang (2022). “MUBot: Learning to Test Large-Scale Commercial Android Apps like a Human”. In Proceedings of ICSME 2022 (Industry Track). IEEE, 2022. [pdf]
- Wu, Qinyun, Huan Song and Ping Yang. “Real-World Clone-Detection in Go.” In Proceedings of MSR 2022 (Industry Track). ACM, 2022. [pdf]
- Peng, Chao, Ajitha Rajan, and Tianqin Cai. “CAT: Change-focused Android GUI Testing.” In Proceedings of the 2021 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 2021. [pdf]
- Cai, Tianqin, Zhao Zhang, and Ping Yang. “Fastbot: A Multi-Agent Model-Based Test Generation System Beijing Bytedance Network Technology Co., Ltd.” In Proceedings of the IEEE/ACM 1st International Conference on Automation of Software Test. 2020. [pdf]
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