H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 30 Citations 5,545 251 World Ranking 8905 National Ranking 149

Overview

What is he best known for?

The fields of study he is best known for:

  • Software
  • Operating system
  • Artificial intelligence

His primary scientific interests are in Software, Software quality, Data mining, Software engineering and Predictive modelling. His study in Code extends to Software with its themes. His work in the fields of Software quality, such as Software metric, intersects with other areas such as Eclipse.

The various areas that Kenichi Matsumoto examines in his Data mining study include Quality, Random forest and Artificial neural network. His Software engineering research integrates issues from Software analytics, Software sizing, Personal software process, Software verification and validation and Software construction. His Predictive modelling study which covers Software quality assurance that intersects with Context model, Data modeling, Software bug, Machine learning and Artificial intelligence.

His most cited work include:

  • Automated parameter optimization of classification techniques for defect prediction models (215 citations)
  • An Empirical Comparison of Model Validation Techniques for Defect Prediction Models (201 citations)
  • Software quality analysis by code clones in industrial legacy software (148 citations)

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

The scientist’s investigation covers issues in Software, Software development, Software engineering, Data mining and Source code. The concepts of his Software study are interwoven with issues in Empirical research and Artificial intelligence. His Software engineering study combines topics in areas such as Software project management, Team software process, Software development process, Software system and Project management.

His research integrates issues of Predictive modelling, Machine learning, Collaborative filtering and Estimation in his study of Data mining. His research in Source code intersects with topics in World Wide Web, Database and Code. Specifically, his work in Software quality is concerned with the study of Software metric.

He most often published in these fields:

  • Software (29.35%)
  • Software development (23.37%)
  • Software engineering (22.55%)

What were the highlights of his more recent work (between 2018-2021)?

  • Source code (14.13%)
  • Software (29.35%)
  • Software development (23.37%)

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

Source code, Software, Software development, Code and Code review are his primary areas of study. Kenichi Matsumoto interconnects Program comprehension, Data mining, Categorization, Software quality and Data science in the investigation of issues within Source code. His work on Software quality assurance as part of general Software quality research is often related to Exploratory research, thus linking different fields of science.

Kenichi Matsumoto specializes in Software, namely Technical debt. His Software development research includes elements of Team effectiveness, World Wide Web, Human–computer interaction and Process management. His research on Code also deals with topics like

  • Identification together with Java and Computer security,
  • Software engineering that intertwine with fields like Static program analysis.

Between 2018 and 2021, his most popular works were:

  • The Impact of Automated Parameter Optimization on Defect Prediction Models (101 citations)
  • The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction Models (59 citations)
  • The impact of human factors on the participation decision of reviewers in modern code review (17 citations)

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

  • Software
  • Operating system
  • Artificial intelligence

Kenichi Matsumoto mainly focuses on Source code, Software, Empirical research, Software quality and World Wide Web. Kenichi Matsumoto has researched Source code in several fields, including Domain, Natural language processing, Categorization, Java and Technical debt. His research investigates the connection with Java and areas like Software system which intersect with concerns in Code and Data mining.

In general Software, his work in Software analytics is often linked to Externalization linking many areas of study. Kenichi Matsumoto mostly deals with Software quality assurance in his studies of Software quality. His Artificial intelligence research includes themes of Context and Predictive modelling.

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

Software quality analysis by code clones in industrial legacy software

A. Monden;D. Nakae;T. Kamiya;S. Sato;S. Sato.
ieee international software metrics symposium (2002)

223 Citations

An Empirical Comparison of Model Validation Techniques for Defect Prediction Models

Chakkrit Tantithamthavorn;Shane McIntosh;Ahmed E. Hassan;Kenichi Matsumoto.
IEEE Transactions on Software Engineering (2017)

204 Citations

Automated parameter optimization of classification techniques for defect prediction models

Chakkrit Tantithamthavorn;Shane McIntosh;Ahmed E. Hassan;Kenichi Matsumoto.
international conference on software engineering (2016)

202 Citations

Who should review my code? A file location-based code-reviewer recommendation approach for Modern Code Review

Patanamon Thongtanunam;Chakkrit Tantithamthavorn;Raula Gaikovina Kula;Norihiro Yoshida.
ieee international conference on software analysis evolution and reengineering (2015)

192 Citations

Analyzing individual performance of source code review using reviewers' eye movement

Hidetake Uwano;Masahide Nakamura;Akito Monden;Ken-ichi Matsumoto.
eye tracking research & application (2006)

188 Citations

Revisiting common bug prediction findings using effort-aware models

Yasutaka Kamei;Shinsuke Matsumoto;Akito Monden;Ken-ichi Matsumoto.
international conference on software maintenance (2010)

180 Citations

The Effects of Over and Under Sampling on Fault-prone Module Detection

Y. Kamei;A. Monden;S. Matsumoto;T. Kakimoto.
empirical software engineering and measurement (2007)

162 Citations

A practical method for watermarking Java programs

A. Monden;H. Iida;K. Matsumoto;K. Inoue.
computer software and applications conference (2000)

161 Citations

The Impact of Automated Parameter Optimization on Defect Prediction Models

Chakkrit Tantithamthavorn;Shane McIntosh;Ahmed E. Hassan;Kenichi Matsumoto.
IEEE Transactions on Software Engineering (2019)

158 Citations

Dynamic Software Birthmarks to Detect the Theft of Windows Applications

Haruaki Tamada;Keiji Okamoto;Masahide Nakamura;Akito Monden.
International Symposium on Future Software Technology 2004 (ISFST 2004) (2004)

146 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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