2016 - ACM Senior Member
Lu Zhang focuses on Artificial intelligence, Machine learning, Software, Test case and Artificial neural network. Lu Zhang usually deals with Machine learning and limits it to topics linked to Test and Maintenance engineering, Correctness, Blocking and Integer programming. His Software study focuses on Software bug in particular.
His Test case study combines topics in areas such as Reliability engineering, Process, Regression testing and Fault detection and isolation. His work investigates the relationship between Reliability engineering and topics such as Test Management Approach that intersect with problems in Code coverage. His biological study spans a wide range of topics, including Empirical research and Data mining.
His main research concerns Artificial intelligence, Software, Data mining, Programming language and Test case. His Artificial intelligence research is multidisciplinary, relying on both Machine learning, Set and Natural language processing. His studies in Software integrate themes in fields like Java, Software engineering and Source code.
As a part of the same scientific family, he mostly works in the field of Data mining, focusing on Software development and, on occasion, Software system and Information retrieval. His work is dedicated to discovering how Programming language, Code are connected with Computer engineering and other disciplines. Lu Zhang interconnects Reliability engineering, Debugging and Regression testing in the investigation of issues within Test case.
His primary areas of study are Artificial intelligence, Programming language, Artificial neural network, Debugging and Code. He combines subjects such as Machine learning, Natural language processing, Source code, Graph classification and Pattern recognition with his study of Artificial intelligence. As a part of the same scientific study, he usually deals with the Programming language, concentrating on Commit and frequently concerns with Domain.
His Debugging study deals with Data mining intersecting with Range. His work carried out in the field of Software bug brings together such families of science as Software system, Test case and Software testing. The concepts of his Software study are interwoven with issues in Java, Construct and Software engineering.
His scientific interests lie mostly in Debugging, Software, Artificial intelligence, Software system and Test. His Debugging research incorporates elements of Range, Distributed computing, Data mining and Leverage. His Software research includes elements of Correctness and Software engineering.
His study looks at the intersection of Artificial intelligence and topics like Machine learning with Software quality, Software testing and Test suite. His Software system research incorporates elements of Supervised learning, Code coverage, Dimension and Scope. His Test research also works with subjects such as
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
An approach to detecting duplicate bug reports using natural language and execution information
Xiaoyin Wang;Lu Zhang;Tao Xie;John Anvik.
international conference on software engineering (2008)
Searches for electroweak production of charginos, neutralinos, and sleptons decaying to leptons and W, Z, and Higgs bosons in pp collisions at 8 TeV
V. Khachatryan;A. M. Sirunyan;A. Tumasyan;W. Adam.
European Physical Journal C (2014)
MAPO: Mining and Recommending API Usage Patterns
Hao Zhong;Tao Xie;Lu Zhang;Jian Pei.
european conference on object oriented programming (2009)
Convolutional neural networks over tree structures for programming language processing
Lili Mou;Ge Li;Lu Zhang;Tao Wang.
national conference on artificial intelligence (2016)
Natural Language Inference by Tree-Based Convolution and Heuristic Matching
Lili Mou;Rui Men;Ge Li;Yan Xu.
meeting of the association for computational linguistics (2016)
SNIAFL: Towards a static noninteractive approach to feature location
Wei Zhao;Lu Zhang;Yin Liu;Jiasu Sun.
ACM Transactions on Software Engineering and Methodology (2006)
Inferring Resource Specifications from Natural Language API Documentation
Hao Zhong;Lu Zhang;Tao Xie;Hong Mei.
automated software engineering (2009)
Precise condition synthesis for program repair
Yingfei Xiong;Jie Wang;Runfa Yan;Jiachen Zhang.
international conference on software engineering (2017)
CMS Physics : Technical Design Report Volume 1: Detector Performance and Software
G L Bayatian;A Korablev;A Soha;O Sharif.
CERN-LHCC-2006-001, CMS-TDR-008-1 (2006)
Time-aware test-case prioritization using integer linear programming
Lu Zhang;Shan-Shan Hou;Chao Guo;Tao Xie.
international symposium on software testing and analysis (2009)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: