Reading List

Configuration


SOSP
2011

• Z. Yin, X. Ma, J. Zheng, Y. Zhou, L. N. Bairavasundaram, and S. Pasu- pathy. An Empirical Study on Configuration Errors in Commercial and Open Source Systems.
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SOSP
2013

• T. Xu, J. Zhang, P. Huang, J. Zheng, T. Sheng, D. Yuan, Y. Zhou, and S. Pasupathy. Do not blame users for misconfigurations.
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OSDI
2016

• Tianyin Xu, Xinxin Jin, Peng Huang, Yuanyuan Zhou, Shan Lu, Long Jin, and Shankar Pasupathy. Early detection of configuration errors to reduce failure damage.
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ISSTA
2015

• S. Zhang and M. D. Ernst. Proactive Detection of Inadequate Diagnostic Messages for Software Configuration Errors.
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ASPLOS
2018

• S. Wang, C. Li, H. Hoffmann, S. Lu, W. Sentosa, and A. I. Kistijantoro. Understanding and Auto-Adjusting Performance-Sensitive Configurations.
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Bug Detection


PLDI
2011

• Guoliang Jin, Linhai Song, Wei Zhang, Shan Lu, and Ben Liblit. Automated atomicity-violation fixing.
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OSDI
2012

• Ding Yuan, Soyeon Park, Peng Huang, Yang Liu, Michael M. Lee, Xiaoming Tang, Yuanyuan Zhou, and Stefan Savage. Be conservative: enhancing failure diagnosis with proactive logging.
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ICSE
2012

• Ding Yuan, Soyeon Park, and Yuanyuan Zhou. Characterizing logging practices in open-source software.
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SOSP
2019

• Guangpu Li, Shan Lu, Madanlal Musuvathi, Suman Nath, and Rohan Padhye. Efficient scalable thread-safety-violation detection: finding thousands of concurrency bugs during testing.
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Code Representations


CSUR
2018

• Allamanis, M., Barr, E.T., Devanbu, P.T., & Sutton, C. A Survey of Machine Learning for Big Code and Naturalness.
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FINDINGS
2020

• Feng, Z., Guo, D., Tang, D., Duan, N., Feng, X., Gong, M., Shou, L., Qin, B., Liu, T., Jiang, D., & Zhou, M. CodeBERT: A Pre-Trained Model for Programming and Natural Languages.
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POPL
2019

• Alon, U., Zilberstein, M., Levy, O., & Yahav, E. code2vec: learning distributed representations of code.
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FINDINGS
2021

• Bianchi, F., & Hovy, D. On the Gap between Adoption and Understanding in NLP.
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ArXiv
2021

• Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G. Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing.
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Code Search


ASE
2015

• F. Lv, H. Zhang, J.-g. Lou, S. Wang, D. Zhang, and J. Zhao. Codehow:Effective code search based on api understanding and extended boolean model.
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ICSE
2018

• X. Gu, H. Zhang, and S. Kim. Deep code search.
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FSE
2019

• Jose Cambronero, Hongyu Li, Seohyun Kim, Koushik Sen, and Satish Chandra. When deep learning met code search.
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ASE
2019

• Yao Wan, Jingdong Shu, Yulei Sui, Guandong Xu, Zhou Zhao, Jian Wu, and Philip S. Yu. Multi-modal attention network learning for semantic source code retrieval.
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ICSE
2021

• K. Cao, C. Chen, S. Baltes, C. Treude and X. Chen. Automated Query Reformulation for Efficient Search Based on Query Logs From Stack Overflow.
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