Data mining, Software, Software system, Artificial intelligence and World Wide Web are his primary areas of study. His Data mining research integrates issues from Software bug, Set, Software regression, Debugging and Root cause. The various areas that David Lo examines in his Software study include Mean reciprocal rank, Optimization problem, Software engineering and Support vector machine.
His Software system research includes elements of Software quality, Information retrieval and Database. His Artificial intelligence research is multidisciplinary, relying on both Program comprehension and Machine learning. The concepts of his World Wide Web study are interwoven with issues in Android, Software development and Fork.
David Lo focuses on Software, Data mining, Artificial intelligence, Machine learning and Information retrieval. David Lo has included themes like Software engineering, World Wide Web and Java in his Software study. His Software engineering research is multidisciplinary, incorporating elements of Software maintenance and Software quality.
His Data mining research integrates issues from Process, Software system, Set, Debugging and Specification mining. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Identification, Empirical research and Natural language processing. His Information retrieval study incorporates themes from Stack overflow, Code, Natural language and Source code.
David Lo mainly focuses on Artificial intelligence, Code, Software, Empirical research and Software engineering. His research integrates issues of Stability, Machine learning, Structure and Natural language processing in his study of Artificial intelligence. His Code research includes elements of Identification, Java, Information retrieval, Task and Source code.
David Lo focuses mostly in the field of Software, narrowing it down to topics relating to Knowledge management and, in certain cases, Software development. The various areas that he examines in his Empirical research study include README, Open source, World Wide Web and Key. His Software engineering study which covers Android that intersects with Readability.
David Lo mainly investigates Software, Code, Artificial intelligence, Software engineering and Software bug. He studies Software, namely Software development. The concepts of his Code study are interwoven with issues in Java, Information retrieval, Blockchain, Commit and Source code.
His research in Artificial intelligence intersects with topics in Machine learning and Identification. His Software engineering research incorporates themes from Feature engineering, Program transformation, Android and Smart contract. His Software bug study combines topics in areas such as Contrast, Applied psychology and Interval.
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.
Where should the bugs be fixed? - more accurate information retrieval-based bug localization based on bug reports
Jian Zhou;Hongyu Zhang;David Lo.
international conference on software engineering (2012)
A discriminative model approach for accurate duplicate bug report retrieval
Chengnian Sun;David Lo;Xiaoyin Wang;Jing Jiang.
international conference on software engineering (2010)
Towards more accurate retrieval of duplicate bug reports
Chengnian Sun;David Lo;Siau-Cheng Khoo;Jing Jiang.
automated software engineering (2011)
Classification of software behaviors for failure detection: a discriminative pattern mining approach
David Lo;Hong Cheng;Jiawei Han;Siau-Cheng Khoo.
knowledge discovery and data mining (2009)
History Driven Program Repair
Xuan Bach D. Le;David Lo;Claire Le Goues.
ieee international conference on software analysis evolution and reengineering (2016)
Duplicate bug report detection with a combination of information retrieval and topic modeling
Anh Tuan Nguyen;Tung Thanh Nguyen;Tien N. Nguyen;David Lo.
automated software engineering (2012)
Deep Learning for Just-in-Time Defect Prediction
Xinli Yang;David Lo;Xin Xia;Yun Zhang.
2015 IEEE International Conference on Software Quality, Reliability and Security (2015)
Network Structure of Social Coding in GitHub
F. Thung;T. F. Bissyande;D. Lo;Lingxiao Jiang.
conference on software maintenance and reengineering (2013)
SMArTIC: towards building an accurate, robust and scalable specification miner
David Lo;Siau-Cheng Khoo.
foundations of software engineering (2006)
Version history, similar report, and structure: putting them together for improved bug localization
Shaowei Wang;David Lo.
international conference on program comprehension (2014)
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