H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 51 Citations 12,036 194 World Ranking 2770 National Ranking 29

Overview

What is he best known for?

The fields of study he is best known for:

  • Programming language
  • Software
  • Software engineering

His scientific interests lie mostly in Software, Software engineering, Software evolution, Code refactoring and Programming language. His Software research is multidisciplinary, incorporating perspectives in Dependency, Dependency network and JavaScript. The study incorporates disciplines such as Resilience, Software maintenance, Software development and Taxonomy in addition to Software engineering.

His Software evolution study combines topics from a wide range of disciplines, such as Domain, Software artifacts, Range, Software aging and Data science. His Code refactoring research incorporates elements of Object-oriented programming, Graph rewriting, Formal specification and Software quality, Code smell. His work in Software quality covers topics such as Reverse engineering which are related to areas like Extract class.

His most cited work include:

  • A survey of software refactoring (969 citations)
  • A Taxonomy of Model Transformation (746 citations)
  • A state-of-the-art survey on software merging (437 citations)

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

Tom Mens mainly investigates Software engineering, Software, Software development, Software evolution and Programming language. As a part of the same scientific study, Tom Mens usually deals with the Software engineering, concentrating on Software quality and frequently concerns with Engineering management. He usually deals with Software and limits it to topics linked to Dependency and Data mining.

His Software development study frequently draws connections between adjacent fields such as Software system. His Software evolution research integrates issues from Software development process, Reverse engineering and Systems engineering. His work is connected to Unified Modeling Language, Code refactoring, Graph rewriting, Object-oriented programming and Executable, as a part of Programming language.

He most often published in these fields:

  • Software engineering (35.25%)
  • Software (31.19%)
  • Software development (22.71%)

What were the highlights of his more recent work (between 2013-2021)?

  • Software (31.19%)
  • Software engineering (35.25%)
  • Software development (22.71%)

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

His primary areas of investigation include Software, Software engineering, Software development, Empirical research and Ecosystem. His Software research incorporates themes from Dependency, Dependency network, Data science and JavaScript. He carries out multidisciplinary research, doing studies in Software engineering and Eclipse.

The concepts of his Software development study are interwoven with issues in Software system and Knowledge management. His Empirical research research is multidisciplinary, relying on both Java and World Wide Web. His Software quality research includes elements of Maintainability and Cloud computing.

Between 2013 and 2021, his most popular works were:

  • On the variation and specialisation of workload--A case study of the Gnome ecosystem community (78 citations)
  • The Ecology of Software Ecosystems (65 citations)
  • On the impact of security vulnerabilities in the npm package dependency network (60 citations)

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

  • Programming language
  • Software
  • Software engineering

Tom Mens focuses on Software, Software engineering, Software development, Empirical research and Ecosystem. His work in the fields of Software bug overlaps with other areas such as Order. He interconnects Software versioning, Lag, Software system and Software quality in the investigation of issues within Software engineering.

His Software development study integrates concerns from other disciplines, such as Test and Data science. His work deals with themes such as Representativeness heuristic, Software ecosystem, World Wide Web and Scope, which intersect with Empirical research. Tom Mens combines subjects such as Software peer review and Social software engineering with his study of Software analytics.

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

A survey of software refactoring

T. Mens;T. Tourwe.
IEEE Transactions on Software Engineering (2004)

1588 Citations

A Taxonomy of Model Transformation

Tom Mens;Pieter Van Gorp.
generative programming and component engineering (2006)

1445 Citations

A state-of-the-art survey on software merging

T. Mens.
IEEE Transactions on Software Engineering (2002)

691 Citations

Introduction and Roadmap: History and Challenges of Software Evolution

Tom Mens.
Software Evolution (2008)

486 Citations

Towards a taxonomy of software change

Jim Buckley;Tom Mens;Matthias Zenger;Awais Rashid.
Journal of Software Maintenance and Evolution: Research and Practice (2005)

409 Citations

Software Evolution

Tom Mens;Serge Demeyer.
Software Evolution 1st (2010)

355 Citations

Challenges in software evolution

T. Mens;M. Wermelinger;S. Ducasse;S. Demeyer.
international workshop on principles of software evolution (2005)

352 Citations

Using Description Logic to Maintain Consistency between UML Models

Ragnhild Van Der Straeten;Tom Mens;Jocelyn Simmonds;Viviane Jonckers.
Lecture Notes in Computer Science (2003)

266 Citations

Identifying refactoring opportunities using logic meta programming

T. Tourwe;T. Mens.
european software engineering conference (2003)

248 Citations

Detecting model inconsistency through operation-based model construction

Xavier Blanc;Isabelle Mounier;Alix Mougenot;Tom Mens.
international conference on software engineering (2008)

231 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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