What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Software
Hongyu Zhang focuses on Data mining, Source code, Software bug, Database and Code.
His biological study spans a wide range of topics, including Intersection and Software quality.
His Software bug study integrates concerns from other disciplines, such as Data quality, Mining software repositories and Measure.
His biological study spans a wide range of topics, including Software system, Software and Cluster analysis.
His Code study integrates concerns from other disciplines, such as Search problem and Natural language, Artificial intelligence, Benchmark.
His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning, Information retrieval and XML.
His most cited work include:
- Where should the bugs be fixed? - more accurate information retrieval-based bug localization based on bug reports (347 citations)
- Deep API learning (268 citations)
- ReLink: recovering links between bugs and changes (230 citations)
What are the main themes of his work throughout his whole career to date?
Data mining, Software, Software engineering, Artificial intelligence and Source code are his primary areas of study.
His research on Data mining also deals with topics like
- Software system, which have a strong connection to Software quality,
- Software bug which connect with Compiler.
His Software study combines topics in areas such as Service and Crash.
His Software engineering study combines topics from a wide range of disciplines, such as Programming language, Debugging and XML.
His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Natural language processing.
His study in Source code is interdisciplinary in nature, drawing from both Software regression, Database and Code.
He most often published in these fields:
- Data mining (22.39%)
- Software (18.41%)
- Software engineering (17.91%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (15.42%)
- Software (18.41%)
- Code (11.94%)
In recent papers he was focusing on the following fields of study:
Hongyu Zhang mainly investigates Artificial intelligence, Software, Code, Deep learning and Data mining.
His study in the field of Software system is also linked to topics like Work.
Hongyu Zhang has researched Software system in several fields, including Software bug, Performance prediction, Speedup and Task.
His studies deal with areas such as Java, Artificial neural network, Set and Natural language as well as Code.
The various areas that he examines in his Natural language study include Semantics and Source code.
His work in the fields of Data mining, such as Anomaly detection, overlaps with other areas such as Input reduction.
Between 2018 and 2021, his most popular works were:
- A novel neural source code representation based on abstract syntax tree (87 citations)
- Robust log-based anomaly detection on unstable log data (44 citations)
- On the Multiple Sources and Privacy Preservation Issues for Heterogeneous Defect Prediction (36 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Software
- Programming language
His main research concerns Artificial intelligence, Artificial neural network, Software, Empirical research and Data mining.
His Artificial intelligence study frequently draws connections to adjacent fields such as Code.
His Code study incorporates themes from Source code and Natural language, Natural language processing.
His research in Software intersects with topics in Correctness, Oracle and Obfuscation.
His Empirical research research integrates issues from Service system, Incident management and Incident management.
His Data mining research incorporates themes from Performance prediction, Baseline and Feedforward neural network.
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.
