I am broadly interested in the area of Software Engineering, Programming Languages, Systems, Security, Machine Learning. I have been spending substantial efforts on deep learning of code, software mining, program analysis, code search & reuse, program comprehension & generation, aiming to provide practical techniques and tools for enhancing software reliability, increasing development productivity, reducing maintenance cost, and improving user experience.

Context-Aware Software Deep Learning, Mining, and Analysis

A general theme of my work is mining and analysis for software engineering, especially context-aware, multi-modal, large-scale detection of code clones, code query processing, detection of bugs, search for bug fixes, refactoring, search for better testing & debugging techniques, and protect user data in software. With the progress of recent deep learning techniques, my work also explores a new field in deep learning of software code.

The work is being carried out on large-scale, diverse, contextual data sources in addition to program code itself, such as code change histories, program bug databases, test suites, developer activities, user feedbacks, and socio-technical information pertaining to the complex interactions between people and technologies in both software development processes and real-world usage scenarios.

To effectively and efficiently encode, extract, analyze, reuse useful knowledge from large, diverse, contextual data sources, various methodologies and technologies are being employed, such as static & dynamic program analysis, code representations, software engineering methodologies, natural language processing, information retrieval, data mining, deep learning, and distributed computing techniques.

Publications

Scalable Code Clone Detection and Analysis

Our studies and others' have noticed that on average more than 20% of code in large programs is cloned code, which often leads to higher maintenance cost and subtle software defects. The goal of our research is to scalably and accurately detect various code clones, track their evolutions and migrations among large programs, and manage them properly to facilitate program understanding and reengineering. Many applications, such as code refactoring, bug detection, and plagiarism detection, can stem from code clone detection and analysis.

• DECKARD: A Code Clone and Clone-Related Bug Detection Tool based on our ICSE '07 paper and FSE '08 paper.
  • ACM SIGSOFT Impact Paper Award 2018: Keynote Slides at ESEC/FSE
  • Checkout the latest versions at git://github.com/skyhover/Deckard.git
  • The latest version in the git repository supports Java 7 syntax. Thanks for the contributions from Prof. Gail Kaiser and her students in the Programming Systems Lab at Columbia University. The git repository can be viewed at https://github.com/skyhover/Deckard
  • Or download a stable source package in the 7z format: version 1.2.3
  • Or try out a parallelized version that makes Deckard run faster on a multi-core machine and supports Java 7 syntax: version 1.3.1_Java7. Some firewalls block 7z files; then try downloading the zip version.
• EqMiner: A random-testing based tool for finding functionally equivalent code fragments, based on our ISSTA '09 paper.
  • Checkout the code at git://github.com/skyhover/dyclone.git
  • The git repository can also be viewed at https://github.com/skyhover/dyclone
  • The repository contains a brief readme file explaining how to install/use the tool. The tool depends on Ocaml 3.09 and a modified version of CIL 1.3.6 (included in the repository). Its front-end for C code chopping and compilation may be particularlly useful.
• CLCMiner: Detecting Cross-Language Clones without Intermediates, by Xiao CHENG, Zhiming PENG, Lingxiao JIANG, Hao ZHONG, Haibo YU, and Jianjun ZHAO. In IEICE Transaction on Information and Systems, 100-D(2):273-284, 2017. [on IEICE website, pdf]
• Mining Revision Histories to Detect Cross-Language Clones without Intermediates, by Xiao CHENG, Zhiming PENG, Lingxiao JIANG, Hao ZHONG, Haibo YU, and Jianjun ZHAO. In the proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering (ASE '16), Singapore, 2016. [on ACM DL, pdf]
• On the Feasibility of Detecting Cross-Platform Code Clones via Identifier Similarity, by Xiao CHENG, Lingxiao JIANG, Hao ZHONG, Haibo YU, and Jianjun ZHAO. In the proceedings of the 5th International Workshop on Software Mining (IWSM '16), Singapore, 2016. [on ACM DL, pdf]
• Scalable Detection of Missed Cross-Function Refactorings, by Narcisa Andreea MILEA, Lingxiao JIANG, and Siau-Cheng KHOO. In the proceedings of International Symposium on Software Testing and Analysis (ISSTA '14), San Jose, California, USA, 2014. [on ACM DL, pdf]
• Vector Abstraction and Concretization for Scalable Detection of Refactorings, by Narcisa Andreea MILEA, Lingxiao JIANG, and Siau-Cheng KHOO. In the proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE '14), Hong Kong, 2014. [on ACM DL, pdf]
• Understanding the Genetic Makeup of Linux Device Drivers, by Peter Senna TSCHUDIN, Laurent REVEILLERE, Lingxiao JIANG, David LO, Julia LAWALL, and Gilles MULLER. In the proceedings of the 7th Workshop on Programming Languages and Operating Systems (PLOS '13), Farmington, Pennsylvania, USA, 2013. [on ACM DL, pdf]
• Active Refinement of Clone Anomaly Reports, by Lucia, David LO, Lingxiao JIANG, and Aditya Budi. In the proceedings of the 34th International Conference on Software Engineering (ICSE '12), Zurich, Switzerland, 2012. [on IEEE Xplore and ACM DL, pdf]
• Automatic Mining of Functionally Equivalent Code Fragments via Random Testing, by Lingxiao JIANG and Zhendong SU. In the proceedings of the 18th International Conference on Software Testing and Analysis (ISSTA '09), Chicago, Illinois, USA, 2009. [PDF from ACM DL , on ACM DL, pdf, slides.pdf]
• Scalable Detection of Semantic Clones, by Mark GABEL, Lingxiao JIANG, and Zhendong SU. In the proceedings of the 30th International Conference on Software Engineering (ICSE '08), Leipzig, Germany, 2008. [PDF from ACM DL , on ACM DL, pdf, slides.pdf]
• Context-Based Detection of Clone-Related Bugs, by Lingxiao JIANG, Zhendong SU, and Edwin CHIU. In the proceedings of the 6th joint meeting of the 11th European Software Engineering Conference and the 15th ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE '07), Dubrovnik, Croatia, 2007. [PDF from ACM DL , on ACM DL, pdf, slides.pdf]
• DECKARD: Scalable and Accurate Tree-based Detection of Code Clones, by Lingxiao JIANG, Ghassan MISHERGHI, Zhendong SU, and Stephane GLONDU. In the proceedings of the 29th International Conference on Software Engineering (ICSE '07), Minneapolis, Minnesota, USA, 2007. [pdf, ps, slides.pdf, on IEEE Xplore and ACM DL]

Deep Learning of Code

• RecipeGen++: An automated trigger action programs generator, by Imam Nur Bani YUSUF, Diyanah Binte Abdul JAMAL, Lingxiao JIANG, David LO. In the proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE '22) Demo track, Singapore, 2022. [authors' draft pdf, on ACM DL]. Code available at https://github.com/imamnurby/RecipeGen.
• iTiger: An automatic issue title generation tool, by Ting ZHANG, Ivana Clairine IRSAN, Ferdian THUNG, DongGyun HAN, David LO, Lingxiao JIANG. In the proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE '22) Demo track, Singapore, 2022. [authors' draft pdf, on ACM DL]. Code available at https://github.com/soarsmu/iTiger.
• Accurate generation of trigger-action programs with domain-adapted sequence-to-sequence learning, by Imam Nur Bani YUSUF, Lingxiao JIANG, David LO. In the proceedings of the 30th IEEE/ACM International Conference on Program Comprehension (ICPC '22), Virtual Event, 2022. [authors' draft pdf, on ACM DL]
• On the effectiveness of pretrained models for API learning, by Mohammad Abdul HADI, Imam Nur Bani YUSUF, Ferdian THUNG, Kien Gia LUONG, Lingxiao JIANG, Fatemeh H. FARD, David LO. In the proceedings of the 30th IEEE/ACM International Conference on Program Comprehension (ICPC '22), Virtual Event, 2022. [authors' draft pdf, on ACM DL]
• Self-Supervised Contrastive Learning for Code Retrieval and Summarization via Semantic-Preserving Transformations, by Nghi Duy Quoc BUI, Yijun YU, and Lingxiao JIANG. In the proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '21), 2021. [authors' draft pdf, on ACM DL]
• InferCode: Self-Supervised Learning of Code Representations by Predicting Subtrees, by Nghi Duy Quoc BUI, Yijun YU, and Lingxiao JIANG. In the proceedings of the 43rd International Conference on Software Engineering (ICSE '21), 2021. [authors' draft pdf, on IEEE Xplore; code available: InferCode]
• TreeCaps: Tree-Based Capsule Networks for Source Code Processing, by Nghi Duy Quoc BUI, Yijun YU, and Lingxiao JIANG. In the proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI '21), 2021. [authors' draft pdf, on AAAI OJS; code available: TreeCaps]
• On the Generalizability of Neural Program Models with respect to Semantic-Preserving Program Transformations, by Md Rafiqul Islam Rabin, Nghi Duy Quoc Bui, Ke Wang, Yijun Yu, Lingxiao Jiang, Mohammad Amin Alipour. In Information and Software Technology (IST), 2021. [authors' draft pdf, on Elsevier ScienceDirect]
• Are the Code Snippets What We Are Searching for? A Benchmark and an Empirical Study on Code Search with Natural-Language Queries, by Shuhan YAN, Hang YU, Yuting CHEN, Beijun SHEN, and Lingxiao JIANG. In the proceedings of the 27th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER '20), London, ON, Canada, 2020. [authors' draft pdf, on IEEE Xplore]
• SAR: learning cross-language API mappings with little knowledge, by Nghi Duy Quoc BUI, Yijun YU, and Lingxiao JIANG. In Proceedings of the ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/SIGSOFT FSE '19), Tallinn, Estonia, 2019. [authors' draft pdf, on ACM DL]. Code available at SAR API Mappings
• AutoFocus: Interpreting Attention-Based Neural Networks by Code Perturbation, by Nghi Duy Quoc BUI, Yijun YU, and Lingxiao JIANG. In 34th IEEE/ACM International Conference on Automated Software Engineering (ASE '19), San Diego, CA, USA, 2019. [authors' draft pdf, on IEEE Xplore]
• Bilateral Dependency Neural Networks for Cross-Language Algorithm Classification, by Nghi Duy Quoc BUI, Yijun YU, and Lingxiao JIANG. In the proceedings of the 26th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER '19), Hangzhou, Zhejiang, China, 2019. [authors' draft pdf, on IEEE Xplore]
• TreeCaps: Tree-Structured Capsule Networks for Program Source Code Processing, by Vinoj JAYASUNDARA, Nghi Duy Quoc BUI, Lingxiao JIANG, and David LO. In Workshop on Machine Learning for Systems at the 33rd Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, 2019. [authors' draft pdf, on arXiv]
• SmartEmbed: A Tool for Clone and Bug Detection in Smart Contracts through Structural Code Embedding, by Zhipeng GAO, Vinoj JAYASUNDARA, Lingxiao JIANG, Xin XIA, David LO, and John C. GRUNDY. In IEEE International Conference on Software Maintenance and Evolution (ICSME '19), Cleveland, OH, USA, 2019. [authors' draft pdf, on IEEE Xplore; code available: SmartEmbed]
• Hierarchical learning of cross-language mappings through distributed vector representations for code, by Nghi Duy Quoc BUI and Lingxiao JIANG. In the proceedings of the 40th International Conference on Software Engineering (ICSE '18) New Ideas and Emerging Results (NIER), pages 33--36, Gothenburg, Sweden, 2018. [On ACM DL, pdf] (Won a Distinguished Paper Award).
• Cross-Language Learning for Program Classification Using Bilateral Tree-Based Convolutional Neural Networks, by Nghi Duy Quoc BUI, Lingxiao JIANG, and Yijun YU. In the proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI) Workshop on NLP for Software Engineering, New Orleans, Lousiana, USA, 2018. [authors' draft pdf].

Queries & Analysis of Software Data (Such as Code, Repositories, Bug Databases, Documents, User/Developer Interactions)

• Automating Arduino Programming: From Hardware Setups to Sample Source Code Generation, by Imam Nur Bani Yusuf; Diyanah Binte Abdul Jamal; Lingxiao Jiang. In the proceedings of the 20th International Conference on Mining Software Repositories (MSR '23), Melbourne, Australia, 2023. [To appear, author's draft pdf]
• Duplicate Bug Report Detection: How Far Are We?, by Ting Zhang; DongGyun Han; Venkatesh Vinayakarao; Ivana Clairine Irsan; Bowen Xu; Ferdian Thung; David Lo; Lingxiao Jiang. In ACM Transactions on Software Engineering and Methodology (TOSEM), 2023 (to appear). [author's draft pdf, on ACM DL]
• BlockScope: Detecting and Investigating Propagated Vulnerabilities in Forked Blockchain Projects, by Xiao Yi; Yuzhou Fang; Daoyuan Wu; Lingxiao Jiang. In the proceedings of the 30th Network and Distributed System Security Symposium (NDSS '23) , San Diego, California, USA, 2023. [authors' copy, on ndss-symposium.org]
• An empirical study of blockchain system vulnerabilities: modules, types, and patterns, by Xiao YI, Daoyuan WU, Lingxiao JIANG, Yuzhou FANG, Kehuan ZHANG, Wei ZHANG. In the proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE '22), Singapore, 2022. [authors' draft pdf, on ACM DL]
• DronLomaly: Runtime Detection of Anomalous Drone Behaviors via Log Analysis and Deep Learning, by Lwin Khin Shar, Wei Minn, Ta Nguyen Binh Duong, Jiani Fan, Lingxiao Jiang, Daniel Lim Wai Kiat. In the proceedings of the 29th Asia-pacific Software Engineering Conference (APSEC '22), Japan/Virtual, 2022. [authors' draft pdf, on IEEE Xplore]
• AndroEvolve: Automated Android API Update with Data Flow Analysis and Variable Denormalization, by Stefanus Agus HARYONO, Ferdian THUNG, David LO, Lingxiao JIANG, Julia Lawall, Hong Jin KANG, Lucas SERRANO, Gilles MULLER. In the Journal of Empirical Software Engineering (EMSE), vol. 27, no. 3, pp. 1-35, 2022. [author's draft pdf, on Springer Link]
• Right to Know, Right to Refuse: Towards UI Perception-Based Automated Fine-Grained Permission Controls for Android Apps, by Vikas Kumar MALVIYA, Chee Wei LEOW, Ashok KASTHURI, Yan Naing TUN, Lwin Khin SHAR, Lingxiao JIANG. In the proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering (ASE '22) New Ideas and Emerging Results (NIER) Track, Rochester, MI, USA, 2022. [author's draft pdf, on ACM DL]
• UIPDroid: Unrooted dynamic monitor of Android app UIs for fine-grained permission control, by Mulin DUAN, Lingxiao JIANG, Lwin Khin SHAR, Debin GAO. In the proceedings of the 44th International Conference on Software Engineering (ICSE '22) Demo Track, 2022. [author's draft pdf, on IEEE Xplore; code available: UIPDroid]
• Automatic Pull Request Title Generation, by Ting Zhang, Ivana Clairine Irsan, Ferdian Thung, DongGyun Han, David Lo, Lingxiao Jiang. In the proceedings of IEEE International Conference on Software Maintenance and Evolution (ICSME '22), 2022. [author's draft pdf, on IEEE Xplore; code available: PRTiger]
• AutoPRTitle: A Tool for Automatic Pull Request Title Generation, by Ivana Clairine Irsan, Ting Zhang, Ferdian Thung, David Lo, Lingxiao Jiang. In the proceedings of IEEE International Conference on Software Maintenance and Evolution (ICSME '22) Demo Track, 2022. [author's draft pdf, on IEEE Xplore; code available: AutoPRTitle]
• AndroEvolve: Automated Update for Android Deprecated-API Usages, by Stefanus Agus HARYONO, Ferdian THUNG, David LO, Lingxiao JIANG, Julia Lawall, Hong Jin KANG, Lucas SERRANO, Gilles MULLER. In the proceedings of the 43rd IEEE/ACM International Conference on Software Engineering (ICSE '21) Demo Track, 2021. [author's draft pdf, on ACM DL; code available: AndroEvolve]
• Characterization and Automatic Updates of Deprecated Machine-Learning API Usages, by Stefanus Agus HARYONO, Ferdian THUNG, David LO, Julia Lawall, Lingxiao JIANG. In the proceedings of IEEE International Conference on Software Maintenance and Evolution (ICSME '21), 2021. [author's draft pdf, on IEEE Xplore]
• MLCatchUp: Automated Update of Deprecated Machine-Learning APIs in Python, by Stefanus Agus HARYONO, Ferdian THUNG, David LO, Julia Lawall, Lingxiao JIANG. In the proceedings of IEEE International Conference on Software Maintenance and Evolution (ICSME '21) Demo Track, 2021. [author's draft pdf, on IEEE Xplore; code available: MLCatchUp]
• Sentiment analysis for software engineering: How far can pre-trained transformer models go?, by Ting ZHANG, Bowen XU, Ferdian THUNG, Stefanus Agus HARYONO, David LO, Lingxiao JIANG. In the proceedings of the 36th IEEE International Conference on Software Maintenance and Evolution (ICSME '20), Adelaide, Australia, 2020. [authors' draft pdf, on IEEE Xplore]
• AUSearch: Accurate API Usage Search in GitHub Repositories with Type Resolution, by Muhammad Hilmi ASYROFI, Ferdian THUNG, David LO, and Lingxiao JIANG. In the proceedings of the 27th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER '20), London, ON, Canada, 2020. [authors' draft pdf, on IEEE Xplore]
• Semantic Patches for Java Program Transformation (Experience Report), by Hong Jin KANG, Ferdian THUNG, Julia LAWALL, Gilles MULLER, Lingxiao JIANG, and David LO. In the proceedings of the 33rd European Conference on Object-Oriented Programming (ECOOP '19), London, United Kingdom, 2019. [authors' draft pdf, on DROPS Dagstuhl Research Online Publication Server]. The artufact is also available in Dagstuhl Artifacts Series (DARTS) 5(2), 2019.
• Towards Generating Transformation Rules without Examples for Android API Replacement, by Ferdian THUNG, Hong Jin KANG, Lingxiao JIANG, and David LO. In IEEE International Conference on Software Maintenance and Evolution (ICSME '19), Cleveland, OH, USA, 2019. [authors' draft pdf, on IEEE Xplore]
• API recommendation for event-driven Android application development, by Weizhao YUAN, Hoang Huu NGUYEN, Lingxiao JIANG, Yuting CHEN, Jianjun ZHAO, and Haibo YU. In Journal of Information and Software Technology, Volume 107, Pages 30--47, March 2019. [authors' draft pdf, on Elsevier ScienceDirect]
• LibraryGuru: An API recommendation engine for Android application developers, by Weizhao YUAN, Hoang Huu NGUYEN, Lingxiao JIANG, and Yuting CHEN. In the proceedings of the 40th International Conference on Software Engineering (ICSE '18) Posters, pages 364--365, Gothenburg, Sweden, 2018. Tool available at http://libraryguru.info. [On ACM DL, pdf]
• AutoQuery: Automatic Construction of Dependency Queries for Code Search, by Shaowei WANG, David LO, and Lingxiao JIANG. In the journal of Automated Software Engineering, Volume 23, Issue 3, pages 393--425, 2016. [authors' draft pdf, on Springer Link].
• Scalable Parallelization of Specification Mining using Distributed Computing, by Shaowei WANG, David LO, Lingxiao JIANG, Shahar MAOZ, and Aditya BUDI. In the book of The Art and Science of Analyzing Software Data edited by Christian BIRD, Tim MENZIES, and Thomas ZIMMERMANN, pp 623-648, Elsevier, 2015. [authors' draft pdf, camera-ready pdf on Elsevier ScienceDirect]
• The Knowledge Accumulation and Transfer in Open-Source Software (OSS) Development, by Youngsoo KIM and Lingxiao JIANG. In the proceedings of the 48th Hawaii International Conference on System Sciences (HICSS '15), Kauai, Hawaii, USA, 2015. [pdf, on IEEE Xplore]
• The Learning Curves in Open-Source Software (OSS) Development Network, by Youngsoo KIM and Lingxiao JIANG. In the proceedings of the 16th International Conference on Electronic Commerce (ICEC '14), Philadelphia, Pennsylvania, USA, 2014. [pdf, on ACM DL]
• Active Code Search: incorporating User Feedback to Improve Code Search Relevance, by Shaowei WANG, David LO, and Lingxiao JIANG. In the proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering (ASE '14), Vasteras, Sweden, 2014. [pdf, on ACM DL]
• Got Issues? Who Cares About It? A Large Scale Investigation of Issue Trackers from GitHub, by Tegawende F. BISSYANDE, David LO, Lingxiao JIANG, Laurent REVEILLERE, Jacques KLEIN, and Yves Le TRAON. In the proceedings of the IEEE 24th International Symposium on Software Reliability Engineering (ISSRE '13), Pasadena, California, USA, 2013. [on IEEE Xplore, pdf]
• Popularity, Interoperability, and Impact of Programming Languages in 100,000 Open Source Projects, by Tegawende F. BISSYANDE, Ferdian THUNG, David LO, Lingxiao JIANG, and Laurent REVEILLERE. In the proceedings of the 37th Annual International Computer Software & Applications Conference (COMPSAC '13), Kyoto, Japan, 2013. [on IEEE Xplore, pdf]
• Orion: A Software Project Search Engine with Integrated Diverse Software Artifacts, by Tegawende F. BISSYANDE, Ferdian THUNG, David LO, Lingxiao JIANG, and Laurent REVEILLERE. In the proceedings of the 18th IEEE International Conference on Engineering of Complex Computer Systems (ICECCS '13), Singapore, 2013. [on IEEE Xplore, pdf]
• Understanding Widespread Changes: A Taxonomic Study, by Shaowei WANG, David LO, and Lingxiao JIANG. In the proceedings of the 17th European Conference on Software Maintenance and Reengineering (CSMR '13), Genova, Italy, 2013. [on IEEE Xplore, pdf]
• Network Structure of Social Coding in GitHub, by Ferdian THUNG, Tegawende F. BISSYANDE, David LO, and Lingxiao JIANG. In the proceedings of the 17th European Conference on Software Maintenance and Reengineering (CSMR '13), Genova, Italy, 2013. [on IEEE Xplore, pdf]
• An Empirical Study on Developer Interactions in StackOverflow, by Shaowei WANG, David LO, and Lingxiao JIANG. In the proceedings of the 28th ACM Symposium on Applied Computing (SAC '13), Coimbra, Portugal, 2013. [on ACM DL, pdf]
• Diffusion of Software Features: An Exploratory Study, by Ferdian THUNG, David LO, and Lingxiao JIANG. In the proceedings of the 19th Asia-Pacific Software Engineering Conference (APSEC '12), Hong Kong, 2012. [on IEEE Xplore, pdf]
• Detecting Similar Applications With Collaborative Tagging, by Ferdian THUNG, David LO, and Lingxiao JIANG. In the proceedings of the 28th IEEE International Conference on Software Maintenance (ICSM '12), Riva del Garda, Trento, Italy, 2012. [pdf, on IEEE Xplore]
• Inferring Semantically Related Software Terms and Their Taxonomy By Leveraging Collaborative Tagging, by Shaowei WANG, David LO, and Lingxiao JIANG. In the proceedings of the 28th IEEE International Conference on Software Maintenance (ICSM '12), Riva del Garda, Trento, Italy, 2012. [pdf, on IEEE Xplore]
• Automated Detection of Likely Design Flaws in Layered Architectures, by Aditya BUDI, Lucia, David LO, Lingxiao JIANG, and Shaowei WANG. In the proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering (SEKE '11), Miami Beach, USA, 2011. [pdf, demo on YouTube]
• Code Search via Topic-Enriched Dependence Graph Matching, by Shaowei WANG, David LO, and Lingxiao JIANG. In the proceedings of the 18th Working Conference on Reverse Engineering (WCRE '11 on facebook), Limerick, Ireland, 2011. [pdf, on IEEE Xplore]
• Concern Localization Using Information Retrieval: An Empirical Study on Linux Kernel, by Shaowei WANG, David LO, Zhenchang XING, and Lingxiao JIANG. In the proceedings of the 18th Working Conference on Reverse Engineering (WCRE '11 on facebook), Limerick, Ireland, 2011. [pdf, on IEEE Xplore]

Automated Testing

• Detecting C++ Compiler Front-End Bugs via Grammar Mutation and Differential Testing, by Haoxin Tu, He Jiang, Zhide Zhou, Yixuan Tang, Zhilei Ren, Lei Qiao, Lingxiao Jiang. IEEE Transactions on Reliability (TR), vol. 72, no. 1, pp. 343-357, 2023. [authors' draft pdf, on IEEE Xplore]
• RemGen: remanufacturing a random program generator for compiler testing, by Haoxin Tu, He Jiang, Xiaochen Li, Zhide Zhou, Lingxiao Jiang. In the proceedings of the 33rd IEEE International Symposium on Software Reliability Engineering (ISSRE '22), Charlotte, North Carolina, USA, 2022. [authors' draft pdf, on IEEE Xplore]
• SmartFuzz: An automated smart fuzzing approach for testing SmartThings apps, by Lwin Khin SHAR, TA Nguyen Binh Duong, Lingxiao JIANG, David LO, WEI Minn, Glenn YEO Kiah Yong, Eugene KIM. In the proceedings of the 27th Asia-pacific Software Engineering Conference (APSEC '20), Singapore, 2020. [authors' draft pdf, on IEEE Xplore]
• CrossASR: Efficient differential testing of automatic speech recognition via text-to-speech, by Muhammad Hilmi ASYROFI, Ferdian THUNG, David LO, Lingxiao JIANG. In the proceedings of the International Conference on Software Maintenance and Evolution (ICSME '20), Adelaide, Australia, 2020. [authors' draft pdf, on IEEE Xplore]
• Android Repository Mining for Detecting Publicly Accessible Functions Missing Permission Checks, by Hoang H. NGUYEN, Lingxiao JIANG, and Tho T. QUAN. In the proceedings of the 25th IEEE International Conference on Program Comprehension (ICPC '17), Buenos Aires, Argentina, 2017. [authors' draft pdf]
• Whole-System Analysis for Understanding Publicly Accessible Functions in Android, by Hoang H. NGUYEN, Lingxiao JIANG, and Tho T. QUAN. In the proceedings of the 11th South-East Asean Technical University Consortium Symposium (SEATUC '17), Ho Chi Minh City, Vietnam, 2017. [pdf]
• Graph-Aided Directed Testing of Android Applications for Checking Runtime Privacy Behaviours, by Joseph CHAN Joo Keng, Lingxiao JIANG, William TAN Kiat Wee, and Rajesh Krishna BALAN. In the proceedings of the 11th International Workshop on Automation of Software Test (AST '16), Austin, Texas, USA, 2016. [on ACM DL, pdf]
• An Empirical Study of Adoption of Software Testing in Open Source Projects, by Pavneet Singh KOCHHAR, Tegawende F. BISSYANDE, David LO, and Lingxiao JIANG. In the proceedings of the 13th International Conference on Quality Software (QSIC '13), Nanjing, China, 2013. [on IEEE Xplore, pdf]. A preliminary version of this paper appeared as Adoption of Software Testing in Open Source Projects---A Preliminary Study on 50,000 Projects, by Pavneet Singh KOCHHAR, Tegawende F. BISSYANDE, David LO, and Lingxiao JIANG. In the proceedings of the 17th European Conference on Software Maintenance and Reengineering (CSMR '13), Genova, Italy, 2013. [pdf]
• kb^e-Anonymity: Test Data Anonymization for Evolving Programs, by Lucia, David LO, Lingxiao JIANG, and Aditya BUDI. In the proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering (ASE '12), Essen, Germany, 2012. [on ACM DL, pdf]
• kb-Anonymity: A Model for Anonymized Behavior-Preserving Test and Debugging Data, by Aditya BUDI, David LO, Lingxiao JIANG, and Lucia. In the proceedings of the 32nd ACM SIGPLAN conference on Programming Language Design and Implementation (PLDI '11), San Jose, California, USA, 2011. [PDF from ACM DL , on ACM DL, pdf, slides.pdf]
• Profile-Guided Program Simplification for Effective Testing and Analysis, by Lingxiao JIANG and Zhendong SU. In the proceedings of the 16th ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE '08), Atlanta, Georgia, 2008. [PDF from ACM DL , on ACM DL, pdf, slides.pdf]

Automated Debugging

• MANDO-HGT: Heterogeneous Graph Transformers for Smart Contract Vulnerability Detection, by Hoang Huu Nguyen; Nhat Minh Nguyen; Chunyao Xie; Zahra Ahmadi; Daniel Kudenko; Thanh-Nam Doan; Lingxiao Jiang. In the proceedings of the 20th International Conference on Mining Software Repositories (MSR '23), Melbourne, Australia, 2023. [To appear, author's draft pdf]
• MANDO-GURU: Vulnerability detection for smart contract source code by heterogeneous graph embeddings, by Hoang Huu Nguyen; Nhat Minh Nguyen; Hong-Phuc Doan; Zahra Ahmadi; Thanh-Nam Doan; Lingxiao Jiang. In the proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE '22) Demo Track, Singapore, 2022. [author's draft pdf, on ACM DL]. Code available at https://github.com/MANDO-Project/ge-sc-machine.
• MANDO: Multi-level heterogeneous graph embeddings for fine-grained detection of smart contract vulnerabilities, by Hoang Huu Nguyen; Nhat Minh Nguyen; Chunyao Xie; Zahra Ahmadi; Daniel Kudenko; Thanh-Nam Doan; Lingxiao Jiang. In the proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics (DSAA '22), Virtual Event, 2022. [author's draft pdf, on arXiv]
• Checking smart contracts with structural code embedding, by Zhipeng GAO, Lingxiao JIANG, Xin XIA, David LO, John GRUNDY. In IEEE Transactions on Software Engineering (TSE), vol. 47, no. 12, pp. 2874-2891, 2021. [author's draft pdf, on IEEE Xplore]
• SPINFER: Inferring semantic patches for the Linux kernel, by Lucas SERRANO, Van-Anh NGUYEN, Ferdian THUNG, Lingxiao JIANG, David LO, Julia LAWALL, Gilles MULLER. In the proceedings of the USENIX Annual Technical Conference (USENIX ATC '20), 2020. [author's draft pdf, on USENIX.org]
• Automatic Android deprecated-API usage update by learning from single updated example, by Stefanus A. HARYONO, Ferdian THUNG, KANG Hong Jin, Lucas SERRANO, Gilles MULLER, Julia LAWALL, David LO, Lingxiao JIANG. In the proceedings of the 28th International Conference on Program Comprehension (ICPC '20), 2020. [author's draft pdf, on ACM DL]
• Automated Deprecated-API Usage Update for Android Apps: How Far are We?, by Ferdian THUNG, Stefanus A. Haryono, Lucas SERRANO, Gilles MULLER, Julia LAWALL, David LO, and Lingxiao JIANG. In the proceedings of the 27th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER '20), London, ON, Canada, 2020. [authors' draft pdf, on IEEE Xplore]
• Diversity Maximization Speedup for Localizing Faults in Single-Fault and Multi-Fault Programs, by Xin XIA, Liang GONG, Tien-Duy Buy LE, David LO, Lingxiao JIANG, and Hongyu ZHANG. In the journal of Automated Software Engineering, Volume 23, Issue 1, pages 43--75, 2016. [authors' draft pdf, on Springer Link]. This is an extended version of this conference version: Diversity Maximization Speedup for Fault Localization, by Liang GONG, David LO, Lingxiao JIANG, and Hongyu ZHANG. In the proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering (ASE '12), Essen, Germany, 2012. [pdf, on ACM DL]
• Extended Comprehensive Study of Association Measures for Fault Localization, by Lucia, David LO, Lingxiao JIANG, Ferdian THUNG, and Aditya BUDI. In Journal of Software: Evolution and Process, Volume 26, Issue 2, pages 172-219, 2014. [authors' draft pdf, camera-ready pdf on Wiley Online Library]. This is an extended version of this conference version: Comprehensive Evaluation of Association Measures for Fault Localization, by Lucia, David LO, Lingxiao JIANG, and Aditya BUDI. In the proceedings of the 26th IEEE International Conference on Software Maintenance (ICSM '10), Timisoara, Romania, 2010. [pdf, dataset, on IEEE Xplore]
• Automatic Recovery of Root Causes from Bug-Fixing Changes, by Ferdian THUNG, David LO, and Lingxiao JIANG. In the proceedings of the 20th Working Conference on Reverse Engineering (WCRE '13), Koblenz, Germany, 2013. [on IEEE Xplore, pdf]
• Empirical Evaluation of Bug Linking, by Tegawende F. BISSYANDE, Ferdian THUNG, Shaowei WANG, David LO, Lingxiao JIANG, and Laurent REVEILLERE. In the proceedings of the 17th European Conference on Software Maintenance and Reengineering (CSMR '13), Genova, Italy, 2013. [on IEEE Xplore, pdf]
• An Empirical Study of Bugs in Machine Learning Systems, by Ferdian THUNG, Shaowei WANG, David LO, and Lingxiao JIANG. In the proceedings of the 23rd IEEE International Symposium on Software Reliability Engineering (ISSRE '12), Dallas, Texas, USA, 2012. [on IEEE Xplore, pdf]. Test-of-Time Award in ISSRE '22 [talk slides].
• Automatic Defect Categorization, by Ferdian THUNG, David LO, and Lingxiao JIANG. In the proceedings of the 19th Working Conference on Reverse Engineering (WCRE '12), Kingston, Ontario, Canada, 2012. [pdf, on IEEE Xplore]
• When Would This Bug Get Reported? By Ferdian THUNG, David LO, Lingxiao JIANG, Lucia, Foyzur RAHMAN, and Prem DEVANBU. In the proceedings of the 28th IEEE International Conference on Software Maintenance (ICSM '12), Riva del Garda, Trento, Italy, 2012. [pdf, on IEEE Xplore]
• Interactive Fault Localization By Leveraging Simple User Feedbacks, by Liang GONG, David LO, Lingxiao JIANG, and Hongyu ZHANG. In the proceedings of the 28th IEEE International Conference on Software Maintenance (ICSM '12), Riva del Garda, Trento, Italy, 2012. [pdf, on IEEE Xplore]
• Are Faults Localizable? By Lucia, Ferdian THUNG, David LO, and Lingxiao JIANG. In the proceedings of the 9th Working Conference on Mining Software Repositories (MSR '12), Zurich, Switzerland, 2012. [pdf, on IEEE Xplore]
• Search-Based Fault Localization, by Shaowei WANG, David LO, Lingxiao JIANG, Lucia, and Hoong Chuin LAU. In the proceedings of the 26th IEEE/ACM International Conference on Automated Software Engineering (ASE '11), Lawrence, Kansas, USA, 2011. [pdf, slides.pdf, on IEEE Xplore]
• Context-Aware Statistical Debugging: From Bug Predictors to Faulty Control Flow Paths, by Lingxiao JIANG and Zhendong SU. In the proceedings of the 22nd IEEE/ACM International Conference on Automated Software Engineering (ASE '07), Atlanta, Georgia, USA, 2007. [PDF from ACM DL , on ACM DL, pdf, slides.pdf]

Optimization and Quality Assurance

• FastKLEE: faster symbolic execution via reducing redundant bound checking of type-safe pointers, by Haoxin TU, Lingxiao JIANG, Xuhua DING, He JIANG. In the proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE '22) Demo track, Singapore, 2022. [authors' draft pdf, on ACM DL]. Code available at https://github.com/haoxintu/FastKLEE.
• Right to Know, Right to Refuse: Towards UI Perception-Based Automated Fine-Grained Permission Controls for Android Apps, by Vikas Kumar MALVIYA, Chee Wei LEOW, Ashok KASTHURI, Yan Naing TUN, Lwin Khin SHAR, Lingxiao JIANG. In the proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering (ASE '22) New Ideas and Emerging Results (NIER) Track, Rochester, MI, USA, 2022. [author's draft pdf, on ACM DL]
• ADVISER+: Toward a Usable Web-based Algorithm Portfolio Deviser, by Hoong Chuin LAU, Mustafa MISIR, Xiang LI, and Lingxiao JIANG. In the proceeedings of the 12th Metaheuristics International Conference (MIC '17), Barcelona, Spain, 2017. [authors' draft pdf, on SMU InK Library]
• Leveraging Automated Privacy Checking For Design of Mobile Privacy Protection Mechanisms, by Joseph CHAN Joo Keng, Lingxiao JIANG, William TAN Kiat Wee, and Rajesh Krishna BALAN. In the workshop on Bridging the Gap between Privacy by Design and Privacy in Practice @ CHI, San Jose, CA, USA, 2016. [pdf]
• To What Extent Could We Detect Field Defects? An Extended Empirical Study of False Negatives in Static Bug Finding Tools, by Ferdian THUNG, Lucia, David LO, Lingxiao JIANG, Foyzur RAHMAN, and Prem DEVANBU. In the Journal of Automated Software Engineering (ASE), Volume 22, Issue 4, pages 561-602, 2015. [authors' draft pdf, camera-ready pdf on SpringerLink]. This is an extended version of this conference version: To What Extent Could We Detect Field Defects? An Empirical Study of False Negatives in Static Bug Finding Tools, by Ferdian THUNG, Lucia, David LO, Lingxiao JIANG, Foyzur RAHMAN, and Prem DEVANBU. In the proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering (ASE '12), Essen, Germany, 2012. [pdf, on ACM DL]
• The Case for Mobile Forensics of Private Data Leaks: Towards Large-Scale User-Oriented Privacy Protection, by Joseph CHAN Joo Keng, William TAN Kiat Wee, Lingxiao JIANG, and Rajesh Krishna BALAN. In the proceedings of the 4th Asia-Pacific Workshop on Systems (APSYS '13), Singapore, 2013. [on ACM DL, pdf]
• Real-time Trip Information Service For A Large Taxi Fleet, by Rajesh Krishna BALAN, Khoa Xuan NGUYEN, and Lingxiao JIANG. In the proceedings of the 9th International Conference on Mobile Systems, Applications, and Services (MobiSys '11), Washington, DC, USA, 2011. [PDF from ACM DL , on ACM DL, pdf]
• Static Validation of C Preprocessor Macros, by Andreas SAEBJOERNSEN, Lingxiao JIANG, Daniel QUINLAN, and Zhendong SU. In the proceedings of the 24th IEEE/ACM International Conference on Automated Software Engineering (ASE '09), Auckland, New Zealand, 2009. [pdf, on IEEE Xplore and ACM DL]
• Osprey: A Practical Type System for Validating Dimensional Unit Correctness of C Programs, by Lingxiao JIANG and Zhendong SU. In the proceedings of the 28th International Conference on Software Engineering (ICSE '06), Shanghai, China, 2006. [PDF from ACM DL , on ACM DL, pdf, slides.pdf]