H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 30 Citations 4,802 154 World Ranking 8684 National Ranking 366

Overview

What is he best known for?

The fields of study he is best known for:

  • Software
  • Operating system
  • Programming language

Foutse Khomh spends much of his time researching Software quality, Software engineering, Context, Software and Code smell. In his work, Software release life cycle and Release engineering is strongly intertwined with Quality, which is a subfield of Software quality. Borrowing concepts from Empirical research, Foutse Khomh weaves in ideas under Software engineering.

Foutse Khomh interconnects Software maintenance, Class, Spaghetti code, Artificial intelligence and Machine learning in the investigation of issues within Code smell. His research investigates the connection between Software maintenance and topics such as Software evolution that intersect with issues in Software design, Process management and Software design pattern. His work on Bayesian network, Bayesian probability, Decision tree and Naive Bayes classifier is typically connected to Restructuring as part of general Artificial intelligence study, connecting several disciplines of science.

His most cited work include:

  • Is it a bug or an enhancement?: a text-based approach to classify change requests (275 citations)
  • An exploratory study of the impact of antipatterns on class change- and fault-proneness (242 citations)
  • An Exploratory Study of the Impact of Code Smells on Software Change-proneness (204 citations)

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

Foutse Khomh focuses on Software engineering, Software, Empirical research, Software quality and Software system. The various areas that Foutse Khomh examines in his Software engineering study include Quality, Context, Software maintenance, Task and Software design pattern. His research integrates issues of Computer security, Documentation, Java and Artificial intelligence in his study of Software.

His study in Software quality focuses on Code smell in particular. His Code smell research integrates issues from Machine learning and Functional requirement. The study incorporates disciplines such as Anti-pattern, Deep learning and Code refactoring in addition to Software system.

He most often published in these fields:

  • Software engineering (33.65%)
  • Software (31.25%)
  • Empirical research (20.67%)

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

  • Software (31.25%)
  • Software engineering (33.65%)
  • Empirical research (20.67%)

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

His primary scientific interests are in Software, Software engineering, Empirical research, Software quality and Code. His studies deal with areas such as Java, Cyber-physical system, Documentation and Database as well as Software. His Software engineering study integrates concerns from other disciplines, such as Software design, Software system, Software design pattern, Code refactoring and Code smell.

His Code smell study combines topics from a wide range of disciplines, such as Functional requirement and Commit. His Software quality study frequently involves adjacent topics like Context. The concepts of his Code study are interwoven with issues in Buffer overflow, Stack overflow, Type safety and Class.

Between 2019 and 2021, his most popular works were:

  • On testing machine learning programs (22 citations)
  • Automatic Mining of Opinions Expressed About APIs in Stack Overflow (11 citations)
  • Understanding How and Why Developers Seek and Analyze API-Related Opinions (9 citations)

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

  • Software
  • Operating system
  • Artificial intelligence

Foutse Khomh mostly deals with Empirical research, Software, Artificial intelligence, Machine learning and World Wide Web. Software is closely attributed to Database in his study. His Artificial intelligence study incorporates themes from Baseline and Code smell.

His Code smell research incorporates themes from Key, Software metric, Rank and Software evolution. His World Wide Web research includes themes of Java, Commit and Code reuse. His studies in Application programming interface integrate themes in fields like Context and Software quality.

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

Is it a bug or an enhancement?: a text-based approach to classify change requests

Giuliano Antoniol;Kamel Ayari;Massimiliano Di Penta;Foutse Khomh.
conference of the centre for advanced studies on collaborative research (2008)

420 Citations

An exploratory study of the impact of antipatterns on class change- and fault-proneness

Foutse Khomh;Massimiliano Di Penta;Yann-Gaël Guéhéneuc;Giuliano Antoniol.
Empirical Software Engineering (2012)

356 Citations

An Exploratory Study of the Impact of Code Smells on Software Change-proneness

Foutse Khomh;Massimiliano Di Penta;Yann-Gael Gueheneuc.
working conference on reverse engineering (2009)

317 Citations

An Empirical Study of the Impact of Two Antipatterns, Blob and Spaghetti Code, on Program Comprehension

Marwen Abbes;Foutse Khomh;Yann-Gael Gueheneuc;Giuliano Antoniol.
conference on software maintenance and reengineering (2011)

307 Citations

A Bayesian Approach for the Detection of Code and Design Smells

Foutse Khomh;Stéphane Vaucher;Yann-Gaël Guéhéneuc;Houari Sahraoui.
international conference on quality software (2009)

241 Citations

Do faster releases improve software quality?: an empirical case study of Mozilla Firefox

Foutse Khomh;Tejinder Dhaliwal;Ying Zou;Bram Adams.
mining software repositories (2012)

173 Citations

BDTEX: A GQM-based Bayesian approach for the detection of antipatterns

Foutse Khomh;Stephane Vaucher;Yann-Gaël Guéhéneuc;Houari Sahraoui.
Journal of Systems and Software (2011)

149 Citations

Do Design Patterns Impact Software Quality Positively

F. Khomh;Y.-G. Gueheneuc.
conference on software maintenance and reengineering (2008)

125 Citations

Do code review practices impact design quality? A case study of the Qt, VTK, and ITK projects

Rodrigo Morales;Shane McIntosh;Foutse Khomh.
ieee international conference on software analysis evolution and reengineering (2015)

114 Citations

On rapid releases and software testing: a case study and a semi-systematic literature review

Mika V. Mäntylä;Bram Adams;Foutse Khomh;Emelie Engström.
Empirical Software Engineering (2015)

105 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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