Associate Professor Zhenchang Xing
Areas of expertise
- Software Engineering 080309
- Natural Language Processing 080107
- Pattern Recognition And Data Mining 080109
- Neural, Evolutionary And Fuzzy Computation 080108
Biography
Dr. Zhenchang Xing is an Associate Professor in the Research School of Computer Science, Australian National University. Previously, he was an Assistant Professor in the School of Computer Science and Engineering, Nanyang Technological University, Singapore, from 2012-2016. Before joining NTU, Dr. Xing was a Lee Kuan Yew Research Fellow in the School of Computing, National University of Singapore from 2009-2012. Dr. Xing obtained his Master of Engineering from Nankai University, Tianjin, China in 2001, and his PhD degree from the University of Alberta, Canada in 2008.
Dr. Xing’s main research area is software engineering, applied data analytics, and human-computer interaction. He has published expertise in traditional areas of software engineering such as software differencing, clone analysis and feature location. In his most recent work, Dr. Xing has focused on designing domain-specific data-mining techniques and recommendation systems for the timely and serendipitous discovery of software engineering information on the internet.
Dr. Xing has over 70 publications in refereed journals and conference proceedings. His research work has been published in top software engineering venues such as ICSE, FSE, ASE, ICSME, SANER, MSR, TSE, EMSE. Four of his research papers have won Best Paper awards in ICSM2006, ICSM2011, SANER2016, ASE2016 ToolDemo. Three others have won nominations for Best Paper awards in ASE2005, ICSM2014, and SANER2015. Dr. Xing regularly referees papers and serves on the program committees of the top software engineering conferences (e.g., ICSE, ASE, ICSME). He has won AUD$800,000 in industry and government funding and has industrial collaborations with Rolls-Royce, Insigma Hengtian.
Dr. Xing has graduated five phd students, two of which work in academics, one in MSRA Suzhou, one in SUTD as postdoctural fellow, and one in Tencent AI lab. He currently supervise 5 PhD students, 5 Master students and several undergraduate Honours projects.
Researcher's projects
The overarching goal of Dr. Xing's research is to design and develop data science methods for improving software development productivity and software quality. Dr. Xing and his research team has been actively working on the following research projects:
- Software Engineering: Semantic clone analysis, Software graph embedding and reasoning, Code search and generation
- Human-Computer Interaction: Policy assurance bot, UI design critics and generation, Domain-specific dialogue systems
- Knowledge Graph: Entity and relation extraction in software text, Software weaknesses and vulnerabilities representation learning
- Deep Learning in SE: Question answering and chatbot, Software development knowledge and behavior tracing, Multi-modal (e.g, code, text, image) embedding and retrieval
Available student projects
API recognition and linking in informal Q&A discussions
Junitor bot for Stack Overflow
Software development knowledge graph construction
Software feature-code graph embedding
Software weakeness representation learning and reasoning
Software vulnerabilities (CVEs) severity multi-task prediction
Across-modal (e.g., code, text, UI image, data visualization) retrieval
Programming behavior tracing and captioning (e.g., youtube programming vidoes)
Neural Machine Translation for UI design-to-implementation
Publications
- Zhao, X, Xing, Z, Kabir, M et al 2017, 'HDSKG: Harvesting Domain Specific Knowledge Graph from Content of Webpages', 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering, SANER 2017, ed. G Bavota, M Pinzger and A Marcus, IEEE, Piscataway, New Jersey, US, pp. 56-67pp.
- Xia, X, Bao, L, Lo, D et al 2017, 'What do developers search for on the web?', Empirical Software Engineering, pp. 1-37pp.
- Chen, C, Xing, Z & Wang, X 2017, 'Unsupervised software-specific morphological forms inference from informal discussions', 39th IEEE/ACM International Conference on Software Engineering, ICSE 2017, Institute of Electrical and Electronics Engineers (IEEE Inc), Piscataway, USA, pp. 450-461.
- Jiang, Q, Peng, X, Wang, H et al 2017, 'Understanding systematic and collaborative code changes by evolutionary trajectory patterns', Journal of Software: Evolution and Process, vol. 29, no. 3.
- Ye, D, Xing, Z & Kapre, N 2017, 'The Structure and Dynamics of Knowledge Network in Programming-Specific Q&A Sites: A Case Study of Stack Overflow', Empirical Software Engineering, vol. 22, no. 1, pp. 375-406pp.
- Bao, L, Li, J, Xing, Z et al 2017, 'Extracting and analyzing time-series HCI data from screen-captured task videos', Empirical Software Engineering, vol. 22, no. 1, pp. 134-174pp.
- Ye, D, Xing, Z, Li, J et al 2016, 'Software-specific Part-of-Speech Tagging: An Experimental Study on Stack Overflow', ACM Symposium on Applied Computing, SAC16, Association for Computing Machinery (ACM), TBC, pp. 1378-1385.
- Ye, D, Xing, Z, Foo, C et al 2016, 'Learning to Extract API Mentions from Informal Natural Language Discussions', 2016 IEEE International Conference on Software Maintenance and Evolution, IEEE, Los Alamitos CA 90720, pp. 389-399.
- Chen, C & Xing, Z 2016, 'SimilarTech: automatically recommend analogical libraries across different programming languages', 31st IEEE/ACM International Conference on Automated Software Engineering (ASE), ACM, New York, pp. 834-839.
- Li, J, Bao, L, Xing, Z et al 2016, 'BPMiner: Mining Developers' Behavior Patterns from Screen-Captured Task Videos', ACM Symposium on Applied Computing, SAC16, Association for Computing Machinery (ACM), TBC, pp. 1371-1377.
- Chen, C & Xing, Z 2016, 'Mining Technology Landscape from Stack Overflow', 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM16), ACM, New York.
- Xu, B, Xing, Z, Xia, X et al 2016, 'Domain-Specific Cross-Language Relevant Question Retrieva', International conference on Mining Software Repositories MSR 2016, ed. Miryung Kim, ACM, New York, pp. 413-424.
- Chen, C, Chen, G, Xing, Z et al 2016, 'Learning a Dual-Language Vector Space for Domain-Specific Cross-Lingual Question Retrieval', 31st IEEE/ACM International Conference on Automated Software Engineering (ASE), ACM, New York.
- Ye, D, Xing, Z, Foo, C et al 2016, 'Software-specific Named Entity Recognition in Software Engineering Social Content', International Conference on Software Analysis, Evolution, and Re-engineering SANER16, ed. A.E Hassan, T. Zimmermann, M. Di Penta, IEEE Computer Society, Los Alamitos, pp. 90-101.
- Kabir, M, Han, J, Coleman, A et al 2016, 'Engineering Socially-Aware Systems and Applications', 21st International Conference on Engineering of Complex Computer Systems, IEEE, unknown, pp. 81-90.
- Chen, C, Xing, Z & Han, L 2016, 'TechLand: Assisting Technology Landscape Inquiries with Insights from Stack Overflow', International Conference on Software Maintenance and Evolution ICSME 2016, ed. unknown, IEEE Computer Society, Piscataway, New Jersey.
- Xu, B, Ye, D, Xing, Z et al 2016, 'Predicting Semantically Linkable Knowledge in Developer Online Forums via Convolutional Neural Network', 31st IEEE/ACM International Conference on Automated Software Engineering (ASE), ACM, New York, pp. 51-62.
- Chen, C & Xing, Z 2016, 'Towards Correlating Search on Google and Asking on Stack Overflow', Computer Software and Applications Conference COMPSAC 2016, IEEE Computer Society, Los Alamitos CA 90720, pp. 83-92.
- Li, J, Xing, Z, Ye, D et al 2016, 'From Discussion to Wisdom: Web Resource Recommendation for Hyperlinks in Stack Overflow', ACM Symposium on Applied Computing, SAC16, Association for Computing Machinery (ACM), TBC, pp. 1127-1133.
- Chen, C, Gao, S & Xing, Z 2016, 'Mining Analogical Libraries in Q&A Discussions - Incorporating Relational and Categorical Knowledge into Word Embedding', International Conference on Software Analysis, Evolution, and Re-engineering SANER16, ed. A.E Hassan, T. Zimmermann, M. Di Penta, IEEE Computer Society, Los Alamitos, pp. 338-348.
Projects and Grants
Grants information is drawn from ARIES. To add or update Projects or Grants information please contact your College Research Office.
- Software Engineering for AI-driven systems (Primary Investigator)
- Clinical Decision Support (Primary Investigator)
