H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 42 Citations 6,466 203 World Ranking 4057 National Ranking 104

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Operating system
  • Software

Xin Xia mainly investigates Data mining, Artificial intelligence, Software, Software bug and Machine learning. The study incorporates disciplines such as Bug tracking system, Source lines of code and Software regression, Software quality in addition to Data mining. Many of his studies on Artificial intelligence involve topics that are commonly interrelated, such as Software maintenance.

Xin Xia combines subjects such as Code, Debugging, World Wide Web and Source code with his study of Software. His Software bug research integrates issues from Information retrieval, Component and Word embedding. His study on Precision and recall and Active learning is often connected to Cost effectiveness as part of broader study in Machine learning.

His most cited work include:

  • Deep code comment generation (186 citations)
  • Deep Learning for Just-in-Time Defect Prediction (138 citations)
  • HYDRA: Massively Compositional Model for Cross-Project Defect Prediction (128 citations)

What are the main themes of his work throughout his whole career to date?

Xin Xia mostly deals with Software, Artificial intelligence, Code, Empirical research and Source code. His Software study combines topics in areas such as Debugging and Software engineering. His Artificial intelligence research includes elements of Machine learning, Software maintenance, Data mining and Natural language processing.

His Machine learning study incorporates themes from Classifier, Software system and Task. His Code study integrates concerns from other disciplines, such as Quality, Program comprehension, Theoretical computer science, Word and Information retrieval. Xin Xia has included themes like Java and Executable in his Source code study.

He most often published in these fields:

  • Software (33.86%)
  • Artificial intelligence (29.13%)
  • Code (20.47%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (29.13%)
  • Code (20.47%)
  • Software (33.86%)

In recent papers he was focusing on the following fields of study:

Xin Xia mainly focuses on Artificial intelligence, Code, Software, Deep learning and Empirical research. The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Natural language processing. His Code research includes themes of Program comprehension, Java, Information retrieval, Source code and Software engineering.

Xin Xia studies Software, focusing on Software development in particular. The concepts of his Deep learning study are interwoven with issues in Software maintenance, Theoretical computer science, Feature learning and Leverage. In his study, Maintenance engineering is strongly linked to Software bug, which falls under the umbrella field of Task analysis.

Between 2019 and 2021, his most popular works were:

  • Perceptions, Expectations, and Challenges in Defect Prediction (42 citations)
  • Deep code comment generation with hybrid lexical and syntactical information (29 citations)
  • How does Machine Learning Change Software Development Practices (26 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Operating system
  • Software

Artificial intelligence, Deep learning, Software bug, Software and Empirical research are his primary areas of study. His Software development research extends to the thematically linked field of Artificial intelligence. Xin Xia has researched Deep learning in several fields, including Stability, Software maintenance, Theoretical computer science and Leverage.

While the research belongs to areas of Software maintenance, Xin Xia spends his time largely on the problem of Java, intersecting his research to questions surrounding Source code, Code, Code smell, Usability and Quality. His research in Software bug intersects with topics in Maintenance engineering, Task analysis, Commit and Knowledge management. The study incorporates disciplines such as Data modeling, Machine learning, Debugging and Information retrieval in addition to Software.

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.

Top Publications

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)

216 Citations

Deep code comment generation

Xing Hu;Ge Li;Xin Xia;David Lo.
international conference on program comprehension (2018)

186 Citations

HYDRA: Massively Compositional Model for Cross-Project Defect Prediction

Xin Xia;David Lo;Sinno Jialin Pan;Nachiappan Nagappan.
IEEE Transactions on Software Engineering (2016)

178 Citations

Tag recommendation in software information sites

Xin Xia;David Lo;Xinyu Wang;Bo Zhou.
mining software repositories (2013)

160 Citations

Practitioners' expectations on automated fault localization

Pavneet Singh Kochhar;Xin Xia;David Lo;Shanping Li.
international symposium on software testing and analysis (2016)

155 Citations

Accurate developer recommendation for bug resolution

Xin Xia;David Lo;Xinyu Wang;Bo Zhou.
working conference on reverse engineering (2013)

140 Citations

Predicting semantically linkable knowledge in developer online forums via convolutional neural network

Bowen Xu;Deheng Ye;Zhenchang Xing;Xin Xia.
automated software engineering (2016)

122 Citations

TLEL: A two-layer ensemble learning approach for just-in-time defect prediction

Xinli Yang;David Lo;Xin Xia;Jianliang Sun.
Information & Software Technology (2017)

110 Citations

What do developers search for on the web

Xin Xia;Xin Xia;Lingfeng Bao;David Lo;Pavneet Singh Kochhar.
Empirical Software Engineering (2017)

108 Citations

Improving Automated Bug Triaging with Specialized Topic Model

Xin Xia;David Lo;Ying Ding;Jafar M. Al-Kofahi.
IEEE Transactions on Software Engineering (2017)

100 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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Contact us

Top Scientists Citing Xin Xia

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Singapore Management University

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North Carolina State University

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Hong Kong Polytechnic University

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Nanyang Technological University

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Tegawendé F. Bissyandé

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University of Luxembourg

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Hongyu Zhang

Hongyu Zhang

University of Newcastle Australia

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Xiao-Yuan Jing

Xiao-Yuan Jing

Wuhan University

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Baowen Xu

Baowen Xu

Nanjing University

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Chanchal K. Roy

Chanchal K. Roy

University of Saskatchewan

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Jacques Klein

Jacques Klein

University of Luxembourg

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Gabriele Bavota

Gabriele Bavota

Universita della Svizzera Italiana

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Foutse Khomh

Foutse Khomh

Polytechnique Montréal

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Emad Shihab

Emad Shihab

Concordia University

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